{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f7c29af3",
   "metadata": {},
   "source": [
    "# FORMULA 1 - 2021 SEASON ANALYSIS\n",
    "\n",
    "### Created by Doğan Yiğit Yenigün (a.k.a ToUpperCase78)"
   ]
  },
  {
   "attachments": {
    "f1_logo_present.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "94c8bb73",
   "metadata": {},
   "source": [
    "![f1_logo_present.png](attachment:f1_logo_present.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6dff7f4",
   "metadata": {},
   "source": [
    "## WELCOME TO THE DATA ANALYSIS OF FORMULA 1 2021 SEASON!\n",
    "\n",
    "Welcome to the data analysis of F1 2021 Season! We all have experienced an immensely action-packed, thrilling, and fabulous season that has already made itself in the history! The main elements, without any doubt, were the Red Bull driver **Max Verstappen** and the Mercedes driver **Lewis Hamilton**. Their challange to each other has been started since the very first race of the season and sustained until the last race! While watching the sessions (no matter it was practice, qualifying, or race) in weekends, we always wondered how these would be resulted, what kind of strategies could be applied in order to get ahead of the rivals, or if any unexpected things would happen; especially for these aformentioned two drivers, as well as the others and teams when they found important opportunities and lived the superior moments in some races of the championship.\n",
    "\n",
    "In the meantime, **the effects of Covid-19 pandemic** continued throughout the season, hence some popular races have been cancelled and removed from the initial calendar, replaced with others to keep the number of races high. Plus, some drivers got caught by the virus before some race weekend and that made them impossible to attend to the grid! We can clarify that you might not be surprised if the fans in the grandstands, the drivers themselves, the team personnels and any F1 authoritatives wore masks all the time as the rules were very strict to maintain the overall health in the race environment with no problem.\n",
    "\n",
    "By all manner of means, this season will be remembered **mostly for struggles between Verstappen and Hamilton**, including **their teams Red Bull and Mercedes** with many highs and lows. But, as for the rules, there was **only one winner** to take the championship title of drivers and constructors. That's why, this analysis notebook encompasses lots of explanations for how the season has been progressed till the end, iconic moments of several races to remind ourselves and tables/visualizations to better understand the outcomes in all aspects. I totally believe that you will not regret while reading all of them below! _If you're ready, let's put the five red lights out, and away we go for the analyses and discussions!_\n",
    "\n",
    "**For this purpose, let's import the necessary modules, load the data related to F1 2021 Season for the analyses, in addition to a method implementation that helps assign the correct colors for the drivers and teams when it comes to data visualization.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ad8e81f0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import math\n",
    "from datetime import timedelta\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "33dccb0e",
   "metadata": {},
   "outputs": [],
   "source": [
    "calendar = pd.read_csv('formula1_2021season_calendar.csv')\n",
    "calendar.set_index('Round', inplace=True)\n",
    "drivers = pd.read_csv('formula1_2021season_drivers.csv')\n",
    "drivers.set_index('Abbreviation', inplace=True)\n",
    "teams = pd.read_csv('formula1_2021season_teams.csv')\n",
    "teams.index = range(1,11)\n",
    "sprintQualiResults = pd.read_csv('formula1_2021season_sprintQualifyingResults.csv')\n",
    "raceResults = pd.read_csv('formula1_2021season_raceResults.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f23cd04d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def assign_color(val_type, values):\n",
    "    cl = []\n",
    "    for val in values:\n",
    "        if val_type == 'drivers':  abbr = val.split()[1].upper()[0:3]\n",
    "        elif val_type == 'teams':  abbr = val[0:4].upper()\n",
    "        if abbr in ['ALFA','RAI','GIO','KUB']:   cl.append('#900000')\n",
    "        elif abbr in ['HAAS','SCH','MAZ']:       cl.append('#ffffff')\n",
    "        elif abbr in ['ASTO','VET','STR']:       cl.append('#006f62')\n",
    "        elif abbr in ['WILL','RUS','LAT']:       cl.append('#0072ff')\n",
    "        elif abbr in ['ALPH','GAS','TSU']:       cl.append('#2b5962')\n",
    "        elif abbr in ['MCLA','RIC','NOR']:       cl.append('#ff8700')\n",
    "        elif abbr in ['RED ','VER','PER']:       cl.append('#0600f0')\n",
    "        elif abbr in ['FERR','LEC','SAI']:       cl.append('#cb0000')\n",
    "        elif abbr in ['MERC','HAM','BOT']:       cl.append('#00d2bd')\n",
    "        elif abbr in ['ALPI','ALO','OCO']:       cl.append('#0090ff')\n",
    "    return cl"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ba3a722",
   "metadata": {},
   "source": [
    "## 2021 Season - Race Calendar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "baa04209",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GP Name</th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>Circuit Name</th>\n",
       "      <th>Race Date</th>\n",
       "      <th>Number of Laps</th>\n",
       "      <th>Turns</th>\n",
       "      <th>DRS Zones</th>\n",
       "      <th>Race Distance(km)</th>\n",
       "      <th>Lap Record</th>\n",
       "      <th>Record Owner</th>\n",
       "      <th>Record Year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Round</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Bahrain</td>\n",
       "      <td>Bahrain</td>\n",
       "      <td>Sakhir</td>\n",
       "      <td>Bahrain International Circuit</td>\n",
       "      <td>28 Mar 2021</td>\n",
       "      <td>57</td>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "      <td>308.238</td>\n",
       "      <td>1:31.447</td>\n",
       "      <td>Pedro de la Rosa</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Emilia Romagna</td>\n",
       "      <td>Italy</td>\n",
       "      <td>Imola</td>\n",
       "      <td>Autodromo Enzo e Dino Ferrari</td>\n",
       "      <td>18 Apr 2021</td>\n",
       "      <td>63</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>309.049</td>\n",
       "      <td>1:15.484</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Portugal</td>\n",
       "      <td>Portugal</td>\n",
       "      <td>Portimao</td>\n",
       "      <td>Autodromo Internacional do Algarve</td>\n",
       "      <td>02 May 2021</td>\n",
       "      <td>66</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>306.826</td>\n",
       "      <td>1:18.750</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Spain</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Catalunya</td>\n",
       "      <td>Circuit de Barcelona-Catalunya</td>\n",
       "      <td>09 May 2021</td>\n",
       "      <td>66</td>\n",
       "      <td>16</td>\n",
       "      <td>2</td>\n",
       "      <td>308.424</td>\n",
       "      <td>1:18.149</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Monaco</td>\n",
       "      <td>Monaco</td>\n",
       "      <td>Monte Carlo</td>\n",
       "      <td>Circuit de Monaco</td>\n",
       "      <td>23 May 2021</td>\n",
       "      <td>78</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>260.286</td>\n",
       "      <td>1:12.909</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>Baku</td>\n",
       "      <td>Baku City Circuit</td>\n",
       "      <td>06 Jun 2021</td>\n",
       "      <td>51</td>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>306.049</td>\n",
       "      <td>1:43.009</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>France</td>\n",
       "      <td>France</td>\n",
       "      <td>Le Castellet</td>\n",
       "      <td>Circuit Paul Ricard</td>\n",
       "      <td>20 Jun 2021</td>\n",
       "      <td>53</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>309.690</td>\n",
       "      <td>1:32.740</td>\n",
       "      <td>Sebastian Vettel</td>\n",
       "      <td>2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Styria</td>\n",
       "      <td>Austria</td>\n",
       "      <td>Spielberg</td>\n",
       "      <td>Red Bull Ring</td>\n",
       "      <td>04 Jul 2021</td>\n",
       "      <td>71</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>306.452</td>\n",
       "      <td>1:05.619</td>\n",
       "      <td>Carlos Sainz</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Austria</td>\n",
       "      <td>Austria</td>\n",
       "      <td>Spielberg</td>\n",
       "      <td>Red Bull Ring</td>\n",
       "      <td>18 Jul 2021</td>\n",
       "      <td>71</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>306.452</td>\n",
       "      <td>1:05.619</td>\n",
       "      <td>Carlos Sainz</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Great Britain</td>\n",
       "      <td>Great Britain</td>\n",
       "      <td>Siverstone</td>\n",
       "      <td>Silverstone Circuit</td>\n",
       "      <td>18 Jul 2021</td>\n",
       "      <td>52</td>\n",
       "      <td>18</td>\n",
       "      <td>2</td>\n",
       "      <td>306.198</td>\n",
       "      <td>1:27.097</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Hungary</td>\n",
       "      <td>Hungary</td>\n",
       "      <td>Budapest</td>\n",
       "      <td>Hungaroring</td>\n",
       "      <td>01 Aug 2021</td>\n",
       "      <td>70</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>306.630</td>\n",
       "      <td>1:16:627</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>Spa-Francorchamps</td>\n",
       "      <td>Circuit de Spa-Francorchamps</td>\n",
       "      <td>29 Aug 2021</td>\n",
       "      <td>44</td>\n",
       "      <td>19</td>\n",
       "      <td>2</td>\n",
       "      <td>308.052</td>\n",
       "      <td>1:48.286</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>2018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Dutch</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>Zandvoort</td>\n",
       "      <td>Circuit Zandvoort</td>\n",
       "      <td>05 Sep 2021</td>\n",
       "      <td>72</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>306.587</td>\n",
       "      <td>1:11.097</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Italy</td>\n",
       "      <td>Italy</td>\n",
       "      <td>Monza</td>\n",
       "      <td>Autodromo Nazionale Monza</td>\n",
       "      <td>12 Sep 2021</td>\n",
       "      <td>53</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>306.720</td>\n",
       "      <td>1:21.046</td>\n",
       "      <td>Rubens Barrichello</td>\n",
       "      <td>2004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Russia</td>\n",
       "      <td>Russia</td>\n",
       "      <td>Sochi</td>\n",
       "      <td>Sochi Autodrom</td>\n",
       "      <td>26 Sep 2021</td>\n",
       "      <td>53</td>\n",
       "      <td>18</td>\n",
       "      <td>2</td>\n",
       "      <td>309.745</td>\n",
       "      <td>1:35.761</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Turkey</td>\n",
       "      <td>Turkey</td>\n",
       "      <td>Istanbul</td>\n",
       "      <td>Intercity Istanbul Park</td>\n",
       "      <td>10 Oct 2021</td>\n",
       "      <td>58</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>309.396</td>\n",
       "      <td>1:24.770</td>\n",
       "      <td>Juan Pablo Montoya</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>United States</td>\n",
       "      <td>United States</td>\n",
       "      <td>Austin</td>\n",
       "      <td>Circuit of the Americas</td>\n",
       "      <td>24 Oct 2021</td>\n",
       "      <td>56</td>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>308.405</td>\n",
       "      <td>1:36.169</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Mexico</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>Mexico City</td>\n",
       "      <td>Autodromo Hermanos Rodriguez</td>\n",
       "      <td>07 Nov 2021</td>\n",
       "      <td>71</td>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "      <td>305.354</td>\n",
       "      <td>1:17.774</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Sao Paulo</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>Sao Paulo</td>\n",
       "      <td>Autodromo José Carlos Pace</td>\n",
       "      <td>14 Nov 2021</td>\n",
       "      <td>71</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>305.879</td>\n",
       "      <td>1:10.540</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>2018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Qatar</td>\n",
       "      <td>Qatar</td>\n",
       "      <td>Losail</td>\n",
       "      <td>Losail International Circuit</td>\n",
       "      <td>21 Nov 2021</td>\n",
       "      <td>57</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>306.660</td>\n",
       "      <td>1:23.196</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Saudi Arabia</td>\n",
       "      <td>Saudi Arabia</td>\n",
       "      <td>Jeddah</td>\n",
       "      <td>Jeddah Corniche Circuit</td>\n",
       "      <td>05 Dec 2021</td>\n",
       "      <td>50</td>\n",
       "      <td>27</td>\n",
       "      <td>3</td>\n",
       "      <td>308.450</td>\n",
       "      <td>1:30.734</td>\n",
       "      <td>Lewis Hmailton</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>Yas Island</td>\n",
       "      <td>Yas Marina Circuit</td>\n",
       "      <td>12 Dec 2021</td>\n",
       "      <td>58</td>\n",
       "      <td>16</td>\n",
       "      <td>2</td>\n",
       "      <td>306.183</td>\n",
       "      <td>1:26.103</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              GP Name        Country               City  \\\n",
       "Round                                                     \n",
       "1             Bahrain        Bahrain             Sakhir   \n",
       "2      Emilia Romagna          Italy              Imola   \n",
       "3            Portugal       Portugal           Portimao   \n",
       "4               Spain          Spain          Catalunya   \n",
       "5              Monaco         Monaco        Monte Carlo   \n",
       "6          Azerbaijan     Azerbaijan               Baku   \n",
       "7              France         France       Le Castellet   \n",
       "8              Styria        Austria          Spielberg   \n",
       "9             Austria        Austria          Spielberg   \n",
       "10      Great Britain  Great Britain         Siverstone   \n",
       "11            Hungary        Hungary           Budapest   \n",
       "12            Belgium        Belgium  Spa-Francorchamps   \n",
       "13              Dutch    Netherlands          Zandvoort   \n",
       "14              Italy          Italy              Monza   \n",
       "15             Russia         Russia              Sochi   \n",
       "16             Turkey         Turkey           Istanbul   \n",
       "17      United States  United States             Austin   \n",
       "18             Mexico         Mexico        Mexico City   \n",
       "19          Sao Paulo         Brazil          Sao Paulo   \n",
       "20              Qatar          Qatar             Losail   \n",
       "21       Saudi Arabia   Saudi Arabia             Jeddah   \n",
       "22          Abu Dhabi      Abu Dhabi         Yas Island   \n",
       "\n",
       "                             Circuit Name    Race Date  Number of Laps  Turns  \\\n",
       "Round                                                                           \n",
       "1           Bahrain International Circuit  28 Mar 2021              57     15   \n",
       "2           Autodromo Enzo e Dino Ferrari  18 Apr 2021              63     19   \n",
       "3      Autodromo Internacional do Algarve  02 May 2021              66     15   \n",
       "4          Circuit de Barcelona-Catalunya  09 May 2021              66     16   \n",
       "5                       Circuit de Monaco  23 May 2021              78     19   \n",
       "6                       Baku City Circuit  06 Jun 2021              51     20   \n",
       "7                     Circuit Paul Ricard  20 Jun 2021              53     15   \n",
       "8                           Red Bull Ring  04 Jul 2021              71     10   \n",
       "9                           Red Bull Ring  18 Jul 2021              71     10   \n",
       "10                    Silverstone Circuit  18 Jul 2021              52     18   \n",
       "11                            Hungaroring  01 Aug 2021              70     14   \n",
       "12           Circuit de Spa-Francorchamps  29 Aug 2021              44     19   \n",
       "13                      Circuit Zandvoort  05 Sep 2021              72     14   \n",
       "14              Autodromo Nazionale Monza  12 Sep 2021              53     11   \n",
       "15                         Sochi Autodrom  26 Sep 2021              53     18   \n",
       "16                Intercity Istanbul Park  10 Oct 2021              58     14   \n",
       "17                Circuit of the Americas  24 Oct 2021              56     20   \n",
       "18           Autodromo Hermanos Rodriguez  07 Nov 2021              71     17   \n",
       "19             Autodromo José Carlos Pace  14 Nov 2021              71     15   \n",
       "20           Losail International Circuit  21 Nov 2021              57     16   \n",
       "21                Jeddah Corniche Circuit  05 Dec 2021              50     27   \n",
       "22                     Yas Marina Circuit  12 Dec 2021              58     16   \n",
       "\n",
       "       DRS Zones  Race Distance(km) Lap Record        Record Owner  \\\n",
       "Round                                                                \n",
       "1              3            308.238   1:31.447    Pedro de la Rosa   \n",
       "2              1            309.049   1:15.484      Lewis Hamilton   \n",
       "3              1            306.826   1:18.750      Lewis Hamilton   \n",
       "4              2            308.424   1:18.149      Max Verstappen   \n",
       "5              1            260.286   1:12.909      Lewis Hamilton   \n",
       "6              2            306.049   1:43.009     Charles Leclerc   \n",
       "7              2            309.690   1:32.740    Sebastian Vettel   \n",
       "8              3            306.452   1:05.619        Carlos Sainz   \n",
       "9              3            306.452   1:05.619        Carlos Sainz   \n",
       "10             2            306.198   1:27.097      Max Verstappen   \n",
       "11             1            306.630   1:16:627      Lewis Hamilton   \n",
       "12             2            308.052   1:48.286     Valtteri Bottas   \n",
       "13             2            306.587   1:11.097      Lewis Hamilton   \n",
       "14             2            306.720   1:21.046  Rubens Barrichello   \n",
       "15             2            309.745   1:35.761      Lewis Hamilton   \n",
       "16             2            309.396   1:24.770  Juan Pablo Montoya   \n",
       "17             2            308.405   1:36.169     Charles Leclerc   \n",
       "18             3            305.354   1:17.774     Valtteri Bottas   \n",
       "19             2            305.879   1:10.540     Valtteri Bottas   \n",
       "20             1            306.660   1:23.196      Max Verstappen   \n",
       "21             3            308.450   1:30.734      Lewis Hmailton   \n",
       "22             2            306.183   1:26.103      Max Verstappen   \n",
       "\n",
       "       Record Year  \n",
       "Round               \n",
       "1             2005  \n",
       "2             2020  \n",
       "3             2020  \n",
       "4             2021  \n",
       "5             2021  \n",
       "6             2019  \n",
       "7             2019  \n",
       "8             2020  \n",
       "9             2020  \n",
       "10            2020  \n",
       "11            2020  \n",
       "12            2018  \n",
       "13            2021  \n",
       "14            2004  \n",
       "15            2019  \n",
       "16            2005  \n",
       "17            2019  \n",
       "18            2021  \n",
       "19            2018  \n",
       "20            2021  \n",
       "21            2021  \n",
       "22            2021  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calendar[['GP Name', 'Country', 'City', 'Circuit Name', 'Race Date', 'Number of Laps', 'Turns', 'DRS Zones', \n",
    "          'Race Distance(km)', 'Lap Record', 'Record Owner', 'Record Year']]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7de25477",
   "metadata": {},
   "source": [
    "The table gives us lots of information about the tracks, including race dates, number of laps, turns, total race distance, and current holder of lap time record.\n",
    "\n",
    "In total, **22 races** have been organized in **20 different countries**. As you know, **Italy** became the home of two races this season. One was in Imola (named _Emilia Romagna GP_) and the other was in Monza, the Temple of Speed. Furthermore, **Austria** held the grand prix twice under the names _Styria_ and _Austria GP_, in Red Bull Ring.\n",
    "\n",
    "Due to the **continuous effects of Covid-19 pandemic** worldwide, some races have been ruled out several weeks or months before their official dates. Yes, you don't see some well-known tracks in the table above. To the best of knowledge, these were **Canada**, **Australia**, **Japan** and **Singapore**. These have been replaced with other tracks that also existed in 2020, such as **Imola**, **Portugal** and **Turkey**. Additionally, there were new tracks hosting an F1 event for the first time: **Qatar** and **Saudi Arabia**."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ede8e16",
   "metadata": {},
   "source": [
    "## 2021 Season - Teams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d1dffaf4",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Team</th>\n",
       "      <th>Full Team Name</th>\n",
       "      <th>Base</th>\n",
       "      <th>Team Chief</th>\n",
       "      <th>Technical Chief</th>\n",
       "      <th>Chassis</th>\n",
       "      <th>Power Unit</th>\n",
       "      <th>First Team Entry</th>\n",
       "      <th>World Championships</th>\n",
       "      <th>Highest Race Finish</th>\n",
       "      <th>Pole Positions</th>\n",
       "      <th>Fastest Laps</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mercedes</td>\n",
       "      <td>Mercedes-AMG Petronas Formula One Team</td>\n",
       "      <td>Brackley, United Kingdom</td>\n",
       "      <td>Toto Wolff</td>\n",
       "      <td>Mike Elliott</td>\n",
       "      <td>W12</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>1970</td>\n",
       "      <td>8</td>\n",
       "      <td>1(x115)</td>\n",
       "      <td>127</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Red Bull</td>\n",
       "      <td>Red Bull Racing</td>\n",
       "      <td>Milton Keynes, United Kingdom</td>\n",
       "      <td>Christian Horner</td>\n",
       "      <td>Pierre Waché</td>\n",
       "      <td>RB16B</td>\n",
       "      <td>Honda</td>\n",
       "      <td>1997</td>\n",
       "      <td>4</td>\n",
       "      <td>1(x75)</td>\n",
       "      <td>73</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ferrari</td>\n",
       "      <td>Scuderia Ferrari</td>\n",
       "      <td>Maranello, Italy</td>\n",
       "      <td>Mattia Binotto</td>\n",
       "      <td>Enrico Cardile / Enrico Gualteri</td>\n",
       "      <td>SF21</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>1950</td>\n",
       "      <td>16</td>\n",
       "      <td>1(x239)</td>\n",
       "      <td>223</td>\n",
       "      <td>253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>McLaren</td>\n",
       "      <td>McLaren F1 Team</td>\n",
       "      <td>Woking, United Kingdom</td>\n",
       "      <td>Andreas Seidl</td>\n",
       "      <td>James Key</td>\n",
       "      <td>MCL35M</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>1966</td>\n",
       "      <td>8</td>\n",
       "      <td>1(x183)</td>\n",
       "      <td>156</td>\n",
       "      <td>160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Alpine</td>\n",
       "      <td>Alpine F1 Team</td>\n",
       "      <td>Enstone, United Kingdom</td>\n",
       "      <td>Davide Brivio</td>\n",
       "      <td>Pat Fry / Remi Taffin</td>\n",
       "      <td>A521</td>\n",
       "      <td>Renault</td>\n",
       "      <td>1986</td>\n",
       "      <td>2</td>\n",
       "      <td>1(x21)</td>\n",
       "      <td>20</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>AlphaTauri</td>\n",
       "      <td>Scuderia AlphaTauri</td>\n",
       "      <td>Faenza, Italy</td>\n",
       "      <td>Franz Tost</td>\n",
       "      <td>Jody Egginton</td>\n",
       "      <td>AT02</td>\n",
       "      <td>Honda</td>\n",
       "      <td>1985</td>\n",
       "      <td>0</td>\n",
       "      <td>1(x2)</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Aston Martin</td>\n",
       "      <td>Aston Martin Cognizant Formula One Team</td>\n",
       "      <td>Silverstone, United Kingdom</td>\n",
       "      <td>Otmar Szafnauer</td>\n",
       "      <td>Andrew Green</td>\n",
       "      <td>AMR21</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>1(x1)</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Williams</td>\n",
       "      <td>Williams Racing</td>\n",
       "      <td>Grove, United Kingdom</td>\n",
       "      <td>Jost Capito</td>\n",
       "      <td>François-Xavier Demaison</td>\n",
       "      <td>FW43B</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>1978</td>\n",
       "      <td>9</td>\n",
       "      <td>1(x114)</td>\n",
       "      <td>129</td>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Alfa Romeo</td>\n",
       "      <td>Alfa Romeo F1 Team ORLEN</td>\n",
       "      <td>Hinwil, Switzerland</td>\n",
       "      <td>Frédéric Vasseur</td>\n",
       "      <td>Jan Monchaux</td>\n",
       "      <td>C41</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>1993</td>\n",
       "      <td>0</td>\n",
       "      <td>1(x1)</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Haas</td>\n",
       "      <td>Uralkali Haas F1 Team</td>\n",
       "      <td>Kannapolis, United States</td>\n",
       "      <td>Guenther Steiner</td>\n",
       "      <td>Simone Resta</td>\n",
       "      <td>VF-21</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>2016</td>\n",
       "      <td>0</td>\n",
       "      <td>4(x1)</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Team                           Full Team Name  \\\n",
       "1       Mercedes   Mercedes-AMG Petronas Formula One Team   \n",
       "2       Red Bull                          Red Bull Racing   \n",
       "3        Ferrari                         Scuderia Ferrari   \n",
       "4        McLaren                          McLaren F1 Team   \n",
       "5         Alpine                           Alpine F1 Team   \n",
       "6     AlphaTauri                      Scuderia AlphaTauri   \n",
       "7   Aston Martin  Aston Martin Cognizant Formula One Team   \n",
       "8       Williams                          Williams Racing   \n",
       "9     Alfa Romeo                 Alfa Romeo F1 Team ORLEN   \n",
       "10          Haas                    Uralkali Haas F1 Team   \n",
       "\n",
       "                             Base        Team Chief  \\\n",
       "1        Brackley, United Kingdom        Toto Wolff   \n",
       "2   Milton Keynes, United Kingdom  Christian Horner   \n",
       "3                Maranello, Italy    Mattia Binotto   \n",
       "4          Woking, United Kingdom     Andreas Seidl   \n",
       "5         Enstone, United Kingdom     Davide Brivio   \n",
       "6                   Faenza, Italy        Franz Tost   \n",
       "7     Silverstone, United Kingdom   Otmar Szafnauer   \n",
       "8           Grove, United Kingdom       Jost Capito   \n",
       "9             Hinwil, Switzerland  Frédéric Vasseur   \n",
       "10      Kannapolis, United States  Guenther Steiner   \n",
       "\n",
       "                     Technical Chief Chassis Power Unit  First Team Entry  \\\n",
       "1                       Mike Elliott     W12   Mercedes              1970   \n",
       "2                       Pierre Waché   RB16B      Honda              1997   \n",
       "3   Enrico Cardile / Enrico Gualteri    SF21    Ferrari              1950   \n",
       "4                          James Key  MCL35M   Mercedes              1966   \n",
       "5              Pat Fry / Remi Taffin    A521    Renault              1986   \n",
       "6                      Jody Egginton    AT02      Honda              1985   \n",
       "7                       Andrew Green   AMR21   Mercedes              2018   \n",
       "8           François-Xavier Demaison   FW43B   Mercedes              1978   \n",
       "9                       Jan Monchaux     C41    Ferrari              1993   \n",
       "10                      Simone Resta   VF-21    Ferrari              2016   \n",
       "\n",
       "    World Championships Highest Race Finish  Pole Positions  Fastest Laps  \n",
       "1                     8             1(x115)             127            85  \n",
       "2                     4              1(x75)              73            76  \n",
       "3                    16             1(x239)             223           253  \n",
       "4                     8             1(x183)             156           160  \n",
       "5                     2              1(x21)              20            15  \n",
       "6                     0               1(x2)               1             2  \n",
       "7                     0               1(x1)               1             0  \n",
       "8                     9             1(x114)             129           133  \n",
       "9                     0               1(x1)               1             5  \n",
       "10                    0               4(x1)               0             2  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "teams"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a49a15a7",
   "metadata": {},
   "source": [
    "In this season, there were total of **10 teams** competed in Formula 1 and this number hasn't been changed since 2017.\n",
    "\n",
    "Here, the table reveals information such as the location of their base, name of their team and technical chief, chassis of their cars, manufacturer of the power unit, as well as the accomplishments they have done up until 2021.\n",
    "\n",
    "There are some noticeable changes, though:\n",
    "* **Alpine** has been re-branded from **Renault** which was known with their yellow-based livery. The French team has adopted to blue-weighted color, plus some white and red to represent the French flag under their logo and chassis. They still used the same Renault power unit.\n",
    "* The other team with the rebrand was **Aston Martin**, formerly known as **Racing Point** (and even earlier, **Force India**) with the pink livery. It was quite exciting to see the British luxury car manufacturer back in Formula 1 and represented by the little darker and shiny green color (reflecting the British racing green). Their engine supplier, Mercedes, remained unchanged.\n",
    "* **Mercedes-AMG Petronas**, which is known with the silver livery, continued to use their black-weighted one on W12, similar to 2020.\n",
    "* **Williams** had substantial changes to their livery on their FW43B, to better commemorate the past achievements and colors they used in 90s.\n",
    "* **Haas** found a new naming sponsor Uralkali (from Russia), thus minor changes have been made to their livery to reflect the Russian flag, especially on the front wing and the side. Doesn't it look strange as the team appeared with the colors that could cause a confusion if this was American or Russian?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d456ea7d",
   "metadata": {},
   "source": [
    "## 2021 Season - Drivers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7839edc9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number</th>\n",
       "      <th>Driver</th>\n",
       "      <th>Country</th>\n",
       "      <th>Date of Birth</th>\n",
       "      <th>Place of Birth</th>\n",
       "      <th>Team</th>\n",
       "      <th>World Championships</th>\n",
       "      <th>Grands Prix Entered</th>\n",
       "      <th>Podiums</th>\n",
       "      <th>Points</th>\n",
       "      <th>Highest Race Finish</th>\n",
       "      <th>Highest Grid Position</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Abbreviation</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>HAM</th>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>07/01/1985</td>\n",
       "      <td>Stevenage, England</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>7</td>\n",
       "      <td>288</td>\n",
       "      <td>182</td>\n",
       "      <td>4165.5</td>\n",
       "      <td>1(x103)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BOT</th>\n",
       "      <td>77</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>Finland</td>\n",
       "      <td>28/08/1989</td>\n",
       "      <td>Nastola, Finland</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>0</td>\n",
       "      <td>178</td>\n",
       "      <td>67</td>\n",
       "      <td>1738.0</td>\n",
       "      <td>1(x10)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VER</th>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>30/09/1997</td>\n",
       "      <td>Hasselt, Belgium</td>\n",
       "      <td>Red Bull Racing</td>\n",
       "      <td>1</td>\n",
       "      <td>141</td>\n",
       "      <td>60</td>\n",
       "      <td>1557.5</td>\n",
       "      <td>1(x20)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PER</th>\n",
       "      <td>11</td>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>26/01/1990</td>\n",
       "      <td>Guadalajara, Mexico</td>\n",
       "      <td>Red Bull Racing</td>\n",
       "      <td>0</td>\n",
       "      <td>214</td>\n",
       "      <td>15</td>\n",
       "      <td>896.0</td>\n",
       "      <td>1(x2)</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LEC</th>\n",
       "      <td>16</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>Monaco</td>\n",
       "      <td>16/10/1997</td>\n",
       "      <td>Monte Carlo, Monaco</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>0</td>\n",
       "      <td>81</td>\n",
       "      <td>13</td>\n",
       "      <td>560.0</td>\n",
       "      <td>1(x2)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SAI</th>\n",
       "      <td>55</td>\n",
       "      <td>Carlos Sainz</td>\n",
       "      <td>Spain</td>\n",
       "      <td>01/09/1994</td>\n",
       "      <td>Madrid, Spain</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>0</td>\n",
       "      <td>141</td>\n",
       "      <td>6</td>\n",
       "      <td>536.5</td>\n",
       "      <td>2(x2)</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NOR</th>\n",
       "      <td>4</td>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>13/11/1999</td>\n",
       "      <td>Bristol, England</td>\n",
       "      <td>McLaren</td>\n",
       "      <td>0</td>\n",
       "      <td>60</td>\n",
       "      <td>5</td>\n",
       "      <td>306.0</td>\n",
       "      <td>2(x1)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RIC</th>\n",
       "      <td>3</td>\n",
       "      <td>Daniel Ricciardo</td>\n",
       "      <td>Australia</td>\n",
       "      <td>01/07/1989</td>\n",
       "      <td>Perth, Australia</td>\n",
       "      <td>McLaren</td>\n",
       "      <td>0</td>\n",
       "      <td>210</td>\n",
       "      <td>32</td>\n",
       "      <td>1274.0</td>\n",
       "      <td>1(x8)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OCO</th>\n",
       "      <td>31</td>\n",
       "      <td>Esteban Ocon</td>\n",
       "      <td>France</td>\n",
       "      <td>17/09/1996</td>\n",
       "      <td>Evreux, Normandy</td>\n",
       "      <td>Alpine</td>\n",
       "      <td>0</td>\n",
       "      <td>89</td>\n",
       "      <td>2</td>\n",
       "      <td>272.0</td>\n",
       "      <td>1(x1)</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALO</th>\n",
       "      <td>14</td>\n",
       "      <td>Fernando Alonso</td>\n",
       "      <td>Spain</td>\n",
       "      <td>29/07/1981</td>\n",
       "      <td>Oviedo, Spain</td>\n",
       "      <td>Alpine</td>\n",
       "      <td>2</td>\n",
       "      <td>336</td>\n",
       "      <td>98</td>\n",
       "      <td>1980.0</td>\n",
       "      <td>1(x32)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GAS</th>\n",
       "      <td>10</td>\n",
       "      <td>Pierre Gasly</td>\n",
       "      <td>France</td>\n",
       "      <td>07/02/1996</td>\n",
       "      <td>Rouen, France</td>\n",
       "      <td>AlphaTauri</td>\n",
       "      <td>0</td>\n",
       "      <td>86</td>\n",
       "      <td>3</td>\n",
       "      <td>309.0</td>\n",
       "      <td>1(x1)</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSU</th>\n",
       "      <td>22</td>\n",
       "      <td>Yuki Tsunoda</td>\n",
       "      <td>Japan</td>\n",
       "      <td>11/05/2000</td>\n",
       "      <td>Sagamihara, Japan</td>\n",
       "      <td>AlphaTauri</td>\n",
       "      <td>0</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>4(x1)</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STR</th>\n",
       "      <td>18</td>\n",
       "      <td>Lance Stroll</td>\n",
       "      <td>Canada</td>\n",
       "      <td>29/10/1998</td>\n",
       "      <td>Montreal, Canada</td>\n",
       "      <td>Aston Martin</td>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>3</td>\n",
       "      <td>176.0</td>\n",
       "      <td>3(x3)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VET</th>\n",
       "      <td>5</td>\n",
       "      <td>Sebastian Vettel</td>\n",
       "      <td>Germany</td>\n",
       "      <td>03/07/1987</td>\n",
       "      <td>Heppenheim, Germany</td>\n",
       "      <td>Aston Martin</td>\n",
       "      <td>4</td>\n",
       "      <td>280</td>\n",
       "      <td>122</td>\n",
       "      <td>3061.0</td>\n",
       "      <td>1(x53)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RUS</th>\n",
       "      <td>63</td>\n",
       "      <td>George Russell</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>15/02/1998</td>\n",
       "      <td>King's Lynn, England</td>\n",
       "      <td>Williams</td>\n",
       "      <td>0</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>19.0</td>\n",
       "      <td>2(x1)</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAT</th>\n",
       "      <td>6</td>\n",
       "      <td>Nicholas Latifi</td>\n",
       "      <td>Canada</td>\n",
       "      <td>29/06/1995</td>\n",
       "      <td>Montreal, Canada</td>\n",
       "      <td>Williams</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7(x1)</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RAI</th>\n",
       "      <td>7</td>\n",
       "      <td>Kimi Raikkönen</td>\n",
       "      <td>Finland</td>\n",
       "      <td>17/10/1979</td>\n",
       "      <td>Espoo, Finland</td>\n",
       "      <td>Alfa Romeo</td>\n",
       "      <td>1</td>\n",
       "      <td>352</td>\n",
       "      <td>103</td>\n",
       "      <td>1873.0</td>\n",
       "      <td>1(x21)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GIO</th>\n",
       "      <td>99</td>\n",
       "      <td>Antonio Giovinazzi</td>\n",
       "      <td>Italy</td>\n",
       "      <td>14/12/1993</td>\n",
       "      <td>Martina France, Italy</td>\n",
       "      <td>Alfa Romeo</td>\n",
       "      <td>0</td>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>5(x1)</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSC</th>\n",
       "      <td>47</td>\n",
       "      <td>Mick Schumacher</td>\n",
       "      <td>Germany</td>\n",
       "      <td>22/03/1999</td>\n",
       "      <td>Vufflens-le-Chateau, Switzerland</td>\n",
       "      <td>Haas</td>\n",
       "      <td>0</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12(x1)</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAZ</th>\n",
       "      <td>9</td>\n",
       "      <td>Nikita Mazepin</td>\n",
       "      <td>RAF</td>\n",
       "      <td>02/03/1999</td>\n",
       "      <td>Moscow, Russia</td>\n",
       "      <td>Haas</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14(x1)</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KUB</th>\n",
       "      <td>88</td>\n",
       "      <td>Robert Kubica</td>\n",
       "      <td>Poland</td>\n",
       "      <td>07/12/1984</td>\n",
       "      <td>Krakow, Poland</td>\n",
       "      <td>Alfa Romeo</td>\n",
       "      <td>0</td>\n",
       "      <td>99</td>\n",
       "      <td>12</td>\n",
       "      <td>274.0</td>\n",
       "      <td>1(x1)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Number              Driver         Country Date of Birth  \\\n",
       "Abbreviation                                                             \n",
       "HAM               44      Lewis Hamilton  United Kingdom    07/01/1985   \n",
       "BOT               77     Valtteri Bottas         Finland    28/08/1989   \n",
       "VER               33      Max Verstappen     Netherlands    30/09/1997   \n",
       "PER               11        Sergio Perez          Mexico    26/01/1990   \n",
       "LEC               16     Charles Leclerc          Monaco    16/10/1997   \n",
       "SAI               55        Carlos Sainz           Spain    01/09/1994   \n",
       "NOR                4        Lando Norris  United Kingdom    13/11/1999   \n",
       "RIC                3    Daniel Ricciardo       Australia    01/07/1989   \n",
       "OCO               31        Esteban Ocon          France    17/09/1996   \n",
       "ALO               14     Fernando Alonso           Spain    29/07/1981   \n",
       "GAS               10        Pierre Gasly          France    07/02/1996   \n",
       "TSU               22        Yuki Tsunoda           Japan    11/05/2000   \n",
       "STR               18        Lance Stroll          Canada    29/10/1998   \n",
       "VET                5    Sebastian Vettel         Germany    03/07/1987   \n",
       "RUS               63      George Russell  United Kingdom    15/02/1998   \n",
       "LAT                6     Nicholas Latifi          Canada    29/06/1995   \n",
       "RAI                7      Kimi Raikkönen         Finland    17/10/1979   \n",
       "GIO               99  Antonio Giovinazzi           Italy    14/12/1993   \n",
       "MSC               47     Mick Schumacher         Germany    22/03/1999   \n",
       "MAZ                9      Nikita Mazepin             RAF    02/03/1999   \n",
       "KUB               88       Robert Kubica          Poland    07/12/1984   \n",
       "\n",
       "                                Place of Birth             Team  \\\n",
       "Abbreviation                                                      \n",
       "HAM                         Stevenage, England         Mercedes   \n",
       "BOT                           Nastola, Finland         Mercedes   \n",
       "VER                           Hasselt, Belgium  Red Bull Racing   \n",
       "PER                        Guadalajara, Mexico  Red Bull Racing   \n",
       "LEC                        Monte Carlo, Monaco          Ferrari   \n",
       "SAI                              Madrid, Spain          Ferrari   \n",
       "NOR                           Bristol, England          McLaren   \n",
       "RIC                           Perth, Australia          McLaren   \n",
       "OCO                           Evreux, Normandy           Alpine   \n",
       "ALO                              Oviedo, Spain           Alpine   \n",
       "GAS                              Rouen, France       AlphaTauri   \n",
       "TSU                          Sagamihara, Japan       AlphaTauri   \n",
       "STR                           Montreal, Canada     Aston Martin   \n",
       "VET                        Heppenheim, Germany     Aston Martin   \n",
       "RUS                       King's Lynn, England         Williams   \n",
       "LAT                           Montreal, Canada         Williams   \n",
       "RAI                             Espoo, Finland       Alfa Romeo   \n",
       "GIO                      Martina France, Italy       Alfa Romeo   \n",
       "MSC           Vufflens-le-Chateau, Switzerland             Haas   \n",
       "MAZ                             Moscow, Russia             Haas   \n",
       "KUB                             Krakow, Poland       Alfa Romeo   \n",
       "\n",
       "              World Championships  Grands Prix Entered  Podiums  Points  \\\n",
       "Abbreviation                                                              \n",
       "HAM                             7                  288      182  4165.5   \n",
       "BOT                             0                  178       67  1738.0   \n",
       "VER                             1                  141       60  1557.5   \n",
       "PER                             0                  214       15   896.0   \n",
       "LEC                             0                   81       13   560.0   \n",
       "SAI                             0                  141        6   536.5   \n",
       "NOR                             0                   60        5   306.0   \n",
       "RIC                             0                  210       32  1274.0   \n",
       "OCO                             0                   89        2   272.0   \n",
       "ALO                             2                  336       98  1980.0   \n",
       "GAS                             0                   86        3   309.0   \n",
       "TSU                             0                   22        0    32.0   \n",
       "STR                             0                  100        3   176.0   \n",
       "VET                             4                  280      122  3061.0   \n",
       "RUS                             0                   60        1    19.0   \n",
       "LAT                             0                   39        0     7.0   \n",
       "RAI                             1                  352      103  1873.0   \n",
       "GIO                             0                   62        0    21.0   \n",
       "MSC                             0                   22        0     0.0   \n",
       "MAZ                             0                   21        0     0.0   \n",
       "KUB                             0                   99       12   274.0   \n",
       "\n",
       "             Highest Race Finish  Highest Grid Position  \n",
       "Abbreviation                                             \n",
       "HAM                      1(x103)                      1  \n",
       "BOT                       1(x10)                      1  \n",
       "VER                       1(x20)                      1  \n",
       "PER                        1(x2)                      2  \n",
       "LEC                        1(x2)                      1  \n",
       "SAI                        2(x2)                      2  \n",
       "NOR                        2(x1)                      1  \n",
       "RIC                        1(x8)                      1  \n",
       "OCO                        1(x1)                      3  \n",
       "ALO                       1(x32)                      1  \n",
       "GAS                        1(x1)                      2  \n",
       "TSU                        4(x1)                      7  \n",
       "STR                        3(x3)                      1  \n",
       "VET                       1(x53)                      1  \n",
       "RUS                        2(x1)                      2  \n",
       "LAT                        7(x1)                     10  \n",
       "RAI                       1(x21)                      1  \n",
       "GIO                        5(x1)                      7  \n",
       "MSC                       12(x1)                     14  \n",
       "MAZ                       14(x1)                     15  \n",
       "KUB                        1(x1)                      1  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "drivers[['Number', 'Driver', 'Country', 'Date of Birth', 'Place of Birth', 'Team', 'World Championships', 'Grands Prix Entered',\n",
    "         'Podiums', 'Points', 'Highest Race Finish', 'Highest Grid Position']]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97dd1675",
   "metadata": {},
   "source": [
    "As there were 10 teams available, likewise, there were **20 drivers** (+1 reserve driver) competed in F1 2021 Season. You can see their info; for instance, nationality, place of birth, achievements in their careers up to and including this season.\n",
    "\n",
    "What were the grid line-up changes then, compared to 2020?\n",
    "* First of all, **Sergio Perez**, who raced for Racing Point (Aston Martin), was about to retire from Formula 1. However, Red Bull Racing saw his potential and transferred him as the teammate of Max Verstappen. That would make the Mexican happier that he grabbed a seat from a top team. As a consequence, Alexander Albon has been let go.\n",
    "* In Ferrari, Charles Leclerc met a new teammate **Carlos Sainz**, who was transferred from McLaren. The four-time world champion **Sebastian Vettel**, who had been there since 2015, had announced to part from the Italian team and joined Aston Martin as a new chapter for the rest of his career, together with Lance Stroll.\n",
    "* With the empty seat available for McLaren, they took **Daniel Ricciardo** from Renault (Alpine), to accompany with Lando Norris.\n",
    "* About Renault, now-called Alpine, the two-time world champion **Fernando Alonso** came back to Formula 1 and joined the French team where he obtained the titles from in the past with that team. He raced with Esteban Ocon in the whole season.\n",
    "* Pierre Gasly stayed in AlphaTauri and was accompanied by a Japanese rookie, **Yuki Tsunoda**.\n",
    "* In Haas, their former drivers Romain Grosjean and Kevin Magnussen left the team. Instead, they hired two new rookies: **Mick Schumacher**, champion of Formula 2 2020 Season and son of the legend Michael Schumacher, and **Nikita Mazepin**.\n",
    "* **Robert Kubica** was the only reserve driver who appeared in the grid, raced for Alfa Romeo in two grand prix events (Netherlands and Italy-Monza), replacing Kimi Raikkönen due to being tested positive for Covid-19."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f224e8c8",
   "metadata": {},
   "source": [
    "## Several Notable Races of 2021 Season\n",
    "\n",
    "This season has lasted for 22 races, but among all, there are several ones that stood out more compared to the others, with regards to exciting moments, weird incidents. Let's view the results of top 10 and put some discussions for these races:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1552872",
   "metadata": {},
   "source": [
    "### Grand Prix de Monaco 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2d48108f",
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>No</th>\n",
       "      <th>Driver</th>\n",
       "      <th>Team</th>\n",
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       "      <th>Laps</th>\n",
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       "    <tr>\n",
       "      <th>Position</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th>1</th>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
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       "      <td>18</td>\n",
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       "      <th>3</th>\n",
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       "      <td>Lando Norris</td>\n",
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       "      <td>+19.427</td>\n",
       "      <td>15</td>\n",
       "      <td>No</td>\n",
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       "      <td>Sergio Perez</td>\n",
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       "      <td>+20.490</td>\n",
       "      <td>12</td>\n",
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       "      <td>Pierre Gasly</td>\n",
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       "      <td>6</td>\n",
       "      <td>78</td>\n",
       "      <td>+53.896</td>\n",
       "      <td>8</td>\n",
       "      <td>No</td>\n",
       "      <td>1:15.412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>7</td>\n",
       "      <td>78</td>\n",
       "      <td>+68.231</td>\n",
       "      <td>7</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:12.909</td>\n",
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       "      <th>8</th>\n",
       "      <td>18</td>\n",
       "      <td>Lance Stroll</td>\n",
       "      <td>Aston Martin Mercedes</td>\n",
       "      <td>13</td>\n",
       "      <td>77</td>\n",
       "      <td>+1 lap</td>\n",
       "      <td>4</td>\n",
       "      <td>No</td>\n",
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       "      <th>9</th>\n",
       "      <td>31</td>\n",
       "      <td>Esteban Ocon</td>\n",
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       "      <td>11</td>\n",
       "      <td>77</td>\n",
       "      <td>+1 lap</td>\n",
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       "      <td>10</td>\n",
       "      <td>77</td>\n",
       "      <td>+1 lap</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>1:15.331</td>\n",
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      "text/plain": [
       "          No              Driver                       Team  Starting Grid  \\\n",
       "Position                                                                     \n",
       "1         33      Max Verstappen      Red Bull Racing Honda              2   \n",
       "2         55        Carlos Sainz                    Ferrari              4   \n",
       "3          4        Lando Norris           McLaren Mercedes              5   \n",
       "4         11        Sergio Perez      Red Bull Racing Honda              9   \n",
       "5          5    Sebastian Vettel      Aston Martin Mercedes              8   \n",
       "6         10        Pierre Gasly           AlphaTauri Honda              6   \n",
       "7         44      Lewis Hamilton                   Mercedes              7   \n",
       "8         18        Lance Stroll      Aston Martin Mercedes             13   \n",
       "9         31        Esteban Ocon             Alpine Renault             11   \n",
       "10        99  Antonio Giovinazzi  Alfa Romeo Racing Ferrari             10   \n",
       "\n",
       "          Laps Time/Retired  Points +1 Pt Fastest Lap  \n",
       "Position                                               \n",
       "1           78  1:38:56.820      25    No    1:14.649  \n",
       "2           78       +8.968      18    No    1:14.621  \n",
       "3           78      +19.427      15    No    1:14.670  \n",
       "4           78      +20.490      12    No    1:14.552  \n",
       "5           78      +52.591      10    No    1:15.316  \n",
       "6           78      +53.896       8    No    1:15.412  \n",
       "7           78      +68.231       7   Yes    1:12.909  \n",
       "8           77       +1 lap       4    No    1:14.674  \n",
       "9           77       +1 lap       2    No    1:15.316  \n",
       "10          77       +1 lap       1    No    1:15.331  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MonacoResults = raceResults[raceResults['Track'] == 'Monaco'].set_index('Position').drop('Track', axis=1).head(10)\n",
    "MonacoResults['Points'] = MonacoResults['Points'].astype(int)\n",
    "MonacoResults"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59cba0e3",
   "metadata": {},
   "source": [
    "It's the fifth grand prix of the season. **Monte Carlo circuit** in Monaco is always known as one of the most prestigious Formula 1 races in the history, and winning there brings **huge reputation** for the driver! Because the width of the circuit is too narrow overall, any mistake could put the drivers out of the race easily; it's like _riding a bicycle in a room!_\n",
    "\n",
    "Well, there were **two things** that came to our mind when remembering this grand prix: Firstly, it was **the native hero, Charles Leclerc**, who took the pole position, but **crashed into the barriers**, less than thirty seconds remaining before the end of the qualifying session and causing red flag. The damage on his car appeared that it could affect the engine and gearbox part badly as Ferrari did their best to repair everything. The next day, however, things got worse for the Monegasque driver, because he began losing power before lining up in the starting grid, and these previous issues seemed to continue. As a consequence, Leclerc was forced **to not participate in the race session**. What a big disappointment as he never successfully finished the home race in his career, up until this season!\n",
    "\n",
    "Second, it was the Mercedes driver, **Valtteri Bottas**, who came in for pit-stop on lap around 30 for tyre change, but things became so strange where **one of the tyres could not come out** despite all efforts by pit stop mechanics! This was a very unlucky moment for the Finnish as he had nothing to do with that, but getting off of his car with frustration!\n",
    "\n",
    "By looking at the results, Max Verstappen won this race, **his first at this location** in his career. Then, Carlos Sainz came second to mitigate the negative effects for Ferrari team in the whole weekend; and Lando Norris completed the podium. As a sidenote, McLaren raced here with one-off **Gulf Air livery**, containing light blue and orange colors."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd737460",
   "metadata": {},
   "source": [
    "### Azerbaijan Grand Prix 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9e7bb677",
   "metadata": {},
   "outputs": [
    {
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       "      <td>Lando Norris</td>\n",
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       "      <th>6</th>\n",
       "      <td>14</td>\n",
       "      <td>Fernando Alonso</td>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>8</td>\n",
       "      <td>51</td>\n",
       "      <td>+6.382</td>\n",
       "      <td>8</td>\n",
       "      <td>No</td>\n",
       "      <td>1:45.624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>22</td>\n",
       "      <td>Yuki Tsunoda</td>\n",
       "      <td>AlphaTauri Honda</td>\n",
       "      <td>7</td>\n",
       "      <td>51</td>\n",
       "      <td>+6.624</td>\n",
       "      <td>6</td>\n",
       "      <td>No</td>\n",
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       "      <th>8</th>\n",
       "      <td>55</td>\n",
       "      <td>Carlos Sainz</td>\n",
       "      <td>Ferrari</td>\n",
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       "      <td>51</td>\n",
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       "      <td>4</td>\n",
       "      <td>No</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>3</td>\n",
       "      <td>Daniel Ricciardo</td>\n",
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       "      <td>13</td>\n",
       "      <td>51</td>\n",
       "      <td>+8.874</td>\n",
       "      <td>2</td>\n",
       "      <td>No</td>\n",
       "      <td>1:45.713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>7</td>\n",
       "      <td>Kimi Raikkönen</td>\n",
       "      <td>Alfa Romeo Racing Ferrari</td>\n",
       "      <td>14</td>\n",
       "      <td>51</td>\n",
       "      <td>+9.576</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>1:45.601</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          No            Driver                       Team  Starting Grid  \\\n",
       "Position                                                                   \n",
       "1         11      Sergio Perez      Red Bull Racing Honda              6   \n",
       "2          5  Sebastian Vettel      Aston Martin Mercedes             11   \n",
       "3         10      Pierre Gasly           AlphaTauri Honda              4   \n",
       "4         16   Charles Leclerc                    Ferrari              1   \n",
       "5          4      Lando Norris           McLaren Mercedes              9   \n",
       "6         14   Fernando Alonso             Alpine Renault              8   \n",
       "7         22      Yuki Tsunoda           AlphaTauri Honda              7   \n",
       "8         55      Carlos Sainz                    Ferrari              5   \n",
       "9          3  Daniel Ricciardo           McLaren Mercedes             13   \n",
       "10         7    Kimi Raikkönen  Alfa Romeo Racing Ferrari             14   \n",
       "\n",
       "          Laps Time/Retired  Points +1 Pt Fastest Lap  \n",
       "Position                                               \n",
       "1           51  2:13:36.410      25    No    1:44.687  \n",
       "2           51       +1.385      18    No    1:44.890  \n",
       "3           51       +2.762      15    No    1:45.220  \n",
       "4           51       +3.828      12    No    1:45.382  \n",
       "5           51       +4.754      10    No    1:45.326  \n",
       "6           51       +6.382       8    No    1:45.624  \n",
       "7           51       +6.624       6    No    1:44.939  \n",
       "8           51       +7.709       4    No    1:45.700  \n",
       "9           51       +8.874       2    No    1:45.713  \n",
       "10          51       +9.576       1    No    1:45.601  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AzerbaijanResults = raceResults[raceResults['Track'] == 'Azerbaijan'].set_index('Position').drop('Track', axis=1).head(10)\n",
    "AzerbaijanResults['Points'] = AzerbaijanResults['Points'].astype(int)\n",
    "AzerbaijanResults"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53cd0f36",
   "metadata": {},
   "source": [
    "Here's the next race, **Baku Street Circuit** in Azerbaijan. **Charles Leclerc**'s curse seemed to continue as he again grabbed the pole position, but crashed into the wall before the end of the qualifying! This time, however, he was able to participate in the race and finished **4th**, as shown in the results table above.\n",
    "\n",
    "In reality, the whole circumstances of the race had been changed althogether with a couple of laps remaining, when **Max Verstappen** was out of the race near the start-finish line **due to the blown tyre**, and raised the red flag . After the incident, the standing restart was performed and it looked like a very short sprint could only last for **two laps**. The most interesting moment was that Mercedes driver **Lewis Hamilton** had a massive lock-up before turn 1, which put him to the back of the grid and finished **15th**! _(Could this be because he forgot to disable the magic button that affected the temperature of his car's brakes?)_ On the other side, the star of this race was **Sergio Perez**, winning the Azerbaijan GP; this was his second victory of his career! Next, **Sebastian Vettel** came second, the first podium he had with Aston Martin. Then, **Pierre Gasly** reached the last step of the podium."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "253bdd0b",
   "metadata": {},
   "source": [
    "### Rolex Magyar Nagydij 2021 (Hungary)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4b51e72c",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>No</th>\n",
       "      <th>Driver</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>31</td>\n",
       "      <td>Esteban Ocon</td>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>2:04:43.199</td>\n",
       "      <td>25</td>\n",
       "      <td>No</td>\n",
       "      <td>1:21.421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DQ</th>\n",
       "      <td>5</td>\n",
       "      <td>Sebastian Vettel</td>\n",
       "      <td>Aston Martin Mercedes</td>\n",
       "      <td>10</td>\n",
       "      <td>70</td>\n",
       "      <td>+1.859</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:21.459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>1</td>\n",
       "      <td>70</td>\n",
       "      <td>+2.736</td>\n",
       "      <td>18</td>\n",
       "      <td>No</td>\n",
       "      <td>1:18.715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>55</td>\n",
       "      <td>Carlos Sainz</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>15</td>\n",
       "      <td>70</td>\n",
       "      <td>+15.018</td>\n",
       "      <td>15</td>\n",
       "      <td>No</td>\n",
       "      <td>1:21.423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>14</td>\n",
       "      <td>Fernando Alonso</td>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>9</td>\n",
       "      <td>70</td>\n",
       "      <td>+15.651</td>\n",
       "      <td>12</td>\n",
       "      <td>No</td>\n",
       "      <td>1:20.359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10</td>\n",
       "      <td>Pierre Gasly</td>\n",
       "      <td>AlphaTauri Honda</td>\n",
       "      <td>5</td>\n",
       "      <td>70</td>\n",
       "      <td>+63.614</td>\n",
       "      <td>11</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:18.394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>22</td>\n",
       "      <td>Yuki Tsunoda</td>\n",
       "      <td>AlphaTauri Honda</td>\n",
       "      <td>16</td>\n",
       "      <td>70</td>\n",
       "      <td>+75.803</td>\n",
       "      <td>8</td>\n",
       "      <td>No</td>\n",
       "      <td>1:22.450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>6</td>\n",
       "      <td>Nicholas Latifi</td>\n",
       "      <td>Williams Mercedes</td>\n",
       "      <td>18</td>\n",
       "      <td>70</td>\n",
       "      <td>+77.910</td>\n",
       "      <td>6</td>\n",
       "      <td>No</td>\n",
       "      <td>1:22.831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>63</td>\n",
       "      <td>George Russell</td>\n",
       "      <td>Williams Mercedes</td>\n",
       "      <td>17</td>\n",
       "      <td>70</td>\n",
       "      <td>+79.094</td>\n",
       "      <td>4</td>\n",
       "      <td>No</td>\n",
       "      <td>1:22.112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>3</td>\n",
       "      <td>70</td>\n",
       "      <td>+80.244</td>\n",
       "      <td>2</td>\n",
       "      <td>No</td>\n",
       "      <td>1:20.945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>7</td>\n",
       "      <td>Kimi Raikkönen</td>\n",
       "      <td>Alfa Romeo Racing Ferrari</td>\n",
       "      <td>13</td>\n",
       "      <td>69</td>\n",
       "      <td>+1 lap</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>1:21.518</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          No            Driver                       Team  Starting Grid  \\\n",
       "Position                                                                   \n",
       "1         31      Esteban Ocon             Alpine Renault              8   \n",
       "DQ         5  Sebastian Vettel      Aston Martin Mercedes             10   \n",
       "2         44    Lewis Hamilton                   Mercedes              1   \n",
       "3         55      Carlos Sainz                    Ferrari             15   \n",
       "4         14   Fernando Alonso             Alpine Renault              9   \n",
       "5         10      Pierre Gasly           AlphaTauri Honda              5   \n",
       "6         22      Yuki Tsunoda           AlphaTauri Honda             16   \n",
       "7          6   Nicholas Latifi          Williams Mercedes             18   \n",
       "8         63    George Russell          Williams Mercedes             17   \n",
       "9         33    Max Verstappen      Red Bull Racing Honda              3   \n",
       "10         7    Kimi Raikkönen  Alfa Romeo Racing Ferrari             13   \n",
       "\n",
       "          Laps Time/Retired  Points +1 Pt Fastest Lap  \n",
       "Position                                               \n",
       "1           70  2:04:43.199      25    No    1:21.421  \n",
       "DQ          70       +1.859       0    No    1:21.459  \n",
       "2           70       +2.736      18    No    1:18.715  \n",
       "3           70      +15.018      15    No    1:21.423  \n",
       "4           70      +15.651      12    No    1:20.359  \n",
       "5           70      +63.614      11   Yes    1:18.394  \n",
       "6           70      +75.803       8    No    1:22.450  \n",
       "7           70      +77.910       6    No    1:22.831  \n",
       "8           70      +79.094       4    No    1:22.112  \n",
       "9           70      +80.244       2    No    1:20.945  \n",
       "10          69       +1 lap       1    No    1:21.518  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "HungaryResults = raceResults[raceResults['Track'] == 'Hungary'].set_index('Position').drop('Track', axis=1).head(11)\n",
    "HungaryResults['Points'] = HungaryResults['Points'].astype(int)\n",
    "HungaryResults"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9dec5b48",
   "metadata": {},
   "source": [
    "Now the Hungarian grand prix, before the summer break: It is clear to say that the race was **started with rainy conditions** and while all cars coming into turn 1, lots of them, especially the mid-pack, **crashed into each other** while the rest tried to escape from those accidents! It was full of carnage that looked like **the beginning of a open lobby race** in F1 videogame! This resulted in several DNFs togeher with the red flag and consequently, **Stroll**, **Leclerc**, **Perez**, **Bottas** could not continue the race, later **Norris** and **Mazepin**.\n",
    "\n",
    "Before the restart of the race, the track surface was **getting drier**, thus all the drivers (except one) were called to the pits for slick tyres, instead of getting on the starting grid. Yes, the driver without the pit at that moment was **Lewis Hamilton who started racing alone** after the lights out! One cannot argue that this was **one of the weirdest thing** we have experienced in 2021 Season and in Formula 1 history! Of course, he necessarily changed the tyres one lap later, putting him to the last place among all remaining drivers in the circuit.\n",
    "\n",
    "Despite all these incidents happened, we saw **Esteban Ocon** leading the race afterwards and doing his best to hold **Sebastian Vettel** back all the time, while Hamilton was climbing up positions lap after lap, even the team urged him to win the race as he had the potential for that. However, Ocon's teammate **Fernando Alonso** defended the Briton for almost 10 laps, thus prevented him from new overtakes for a long time. In the end, it was unforgettable for Ocon that he was **the grand prix winner in Hungary**! Alonso, of course, congratulated him after the race; and yeah, it was a great teamwork effort for Alpine!\n",
    "\n",
    "Sebastian Vettel could've come in second place, another podium with Aston Martin. However, he was **disqualified** after the race bacause the team **could not extract the required amount of fuel sample** from the car to be presented to FIA. Moreover, we witnessed **Williams** scoring points at last, after more than two years; it was fully emotional for **George Russell** during the interview as he obtained championship points under this team."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1cf103f",
   "metadata": {},
   "source": [
    "### Rolex Belgian Grand Prix 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3b276962",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>1</td>\n",
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       "      <td>12.5</td>\n",
       "      <td>No</td>\n",
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       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>+1.995</td>\n",
       "      <td>9.0</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>3</th>\n",
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       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>+2.601</td>\n",
       "      <td>7.5</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>Daniel Ricciardo</td>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>+4.496</td>\n",
       "      <td>6.0</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>Sebastian Vettel</td>\n",
       "      <td>Aston Martin Mercedes</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>+7.479</td>\n",
       "      <td>5.0</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>6</th>\n",
       "      <td>10</td>\n",
       "      <td>Pierre Gasly</td>\n",
       "      <td>AlphaTauri Honda</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>+10.177</td>\n",
       "      <td>4.0</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>31</td>\n",
       "      <td>Esteban Ocon</td>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>+11.579</td>\n",
       "      <td>3.0</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>16</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>+12.608</td>\n",
       "      <td>2.0</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>9</th>\n",
       "      <td>6</td>\n",
       "      <td>Nicholas Latifi</td>\n",
       "      <td>Williams Mercedes</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>+15.484</td>\n",
       "      <td>1.0</td>\n",
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       "      <th>10</th>\n",
       "      <td>55</td>\n",
       "      <td>Carlos Sainz</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>+16.166</td>\n",
       "      <td>0.5</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
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      "text/plain": [
       "          No            Driver                   Team  Starting Grid  Laps  \\\n",
       "Position                                                                     \n",
       "1         33    Max Verstappen  Red Bull Racing Honda              1     1   \n",
       "2         63    George Russell      Williams Mercedes              2     1   \n",
       "3         44    Lewis Hamilton               Mercedes              3     1   \n",
       "4          3  Daniel Ricciardo       McLaren Mercedes              4     1   \n",
       "5          5  Sebastian Vettel  Aston Martin Mercedes              5     1   \n",
       "6         10      Pierre Gasly       AlphaTauri Honda              6     1   \n",
       "7         31      Esteban Ocon         Alpine Renault              8     1   \n",
       "8         16   Charles Leclerc                Ferrari              9     1   \n",
       "9          6   Nicholas Latifi      Williams Mercedes             10     1   \n",
       "10        55      Carlos Sainz                Ferrari             11     1   \n",
       "\n",
       "         Time/Retired  Points +1 Pt Fastest Lap  \n",
       "Position                                         \n",
       "1         0:03:27.071    12.5    No         NaN  \n",
       "2              +1.995     9.0    No         NaN  \n",
       "3              +2.601     7.5    No         NaN  \n",
       "4              +4.496     6.0    No         NaN  \n",
       "5              +7.479     5.0    No         NaN  \n",
       "6             +10.177     4.0    No         NaN  \n",
       "7             +11.579     3.0    No         NaN  \n",
       "8             +12.608     2.0    No         NaN  \n",
       "9             +15.484     1.0    No         NaN  \n",
       "10            +16.166     0.5    No         NaN  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raceResults[raceResults['Track'] == 'Belgium'].set_index('Position').drop('Track', axis=1).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a04d649",
   "metadata": {},
   "source": [
    "Belgium Grand Prix this season was quite unusual, because there was always **torrential rain** on Saturday and Sunday, and that made the conditions very bad to drive these cars on the whole track surface for safety reasons! At least, we saw the qualifying session doable, and you can be astonished that how **George Russell** claimed the **2nd place**, i.e. the front row sharing with Max Verstappen and even outqualifying Hamilton!\n",
    "\n",
    "In the next day, everybody can accept that **the race was never actually happened**! All people watching on TV and those at grandstands or open areas in Spa-Franchorchamps got bored as we were not able to see the cars going around the track within the allowed 3 hours race time while there was heavy rain all the time! The only solution was to **get all the cars out for 2 laps** (the results above said 1 lap, but it doesn't matter), escorted by the Safety Car, in the moment when the effect of the rain was diminished and there was less aquaplanning; hence **half of the points** could be distributed for the top 10, according to the results of qualifying session. In the end, **Verstappen** was announced as the winner of this grand prix, while **Russell** and **Hamilton** deserved to step on the podium, as 2nd and 3rd, respectively.\n",
    "\n",
    "Here, let me share the race note, directly taken from Formula 1 official web site:\n",
    "\n",
    "_Half points awarded, as less than 75 percent of the original race distance was completed. Results were calculated in accordance with Article 51.14 of the FIA Formula One Sporting Regulations, namely at the end of lap 1 being the penultimate lap during which the signal to suspend the race was given. However, for the determination of points, Article 6.5 was applicable, the leader having crossed the Control Line 3 times, therefore complying with the requirement for the leader to have completed more than 2 laps in order of half points to be awarded._"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "816e9cb4",
   "metadata": {},
   "source": [
    "### Heineken Gran Premio D'Italia 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f7087712",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>No</th>\n",
       "      <th>Driver</th>\n",
       "      <th>Team</th>\n",
       "      <th>Starting Grid</th>\n",
       "      <th>Laps</th>\n",
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       "      <th>+1 Pt</th>\n",
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       "    <tr>\n",
       "      <th>Position</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>Daniel Ricciardo</td>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>2</td>\n",
       "      <td>53</td>\n",
       "      <td>1:21:54.365</td>\n",
       "      <td>26</td>\n",
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       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>3</td>\n",
       "      <td>53</td>\n",
       "      <td>+1.747</td>\n",
       "      <td>18</td>\n",
       "      <td>No</td>\n",
       "      <td>1:24.971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>77</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>19</td>\n",
       "      <td>53</td>\n",
       "      <td>+4.921</td>\n",
       "      <td>15</td>\n",
       "      <td>No</td>\n",
       "      <td>1:24.872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>16</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>5</td>\n",
       "      <td>53</td>\n",
       "      <td>+7.309</td>\n",
       "      <td>12</td>\n",
       "      <td>No</td>\n",
       "      <td>1:25.319</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>11</td>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>8</td>\n",
       "      <td>53</td>\n",
       "      <td>+8.723</td>\n",
       "      <td>10</td>\n",
       "      <td>No</td>\n",
       "      <td>1:25.156</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>55</td>\n",
       "      <td>Carlos Sainz</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>6</td>\n",
       "      <td>53</td>\n",
       "      <td>+10.535</td>\n",
       "      <td>8</td>\n",
       "      <td>No</td>\n",
       "      <td>1:25.559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>18</td>\n",
       "      <td>Lance Stroll</td>\n",
       "      <td>Aston Martin Mercedes</td>\n",
       "      <td>9</td>\n",
       "      <td>53</td>\n",
       "      <td>+15.804</td>\n",
       "      <td>6</td>\n",
       "      <td>No</td>\n",
       "      <td>1:25.853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>14</td>\n",
       "      <td>Fernando Alonso</td>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>10</td>\n",
       "      <td>53</td>\n",
       "      <td>+17.201</td>\n",
       "      <td>4</td>\n",
       "      <td>No</td>\n",
       "      <td>1:25.472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>63</td>\n",
       "      <td>George Russell</td>\n",
       "      <td>Williams Mercedes</td>\n",
       "      <td>14</td>\n",
       "      <td>53</td>\n",
       "      <td>+19.742</td>\n",
       "      <td>2</td>\n",
       "      <td>No</td>\n",
       "      <td>1:25.835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>31</td>\n",
       "      <td>Esteban Ocon</td>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>12</td>\n",
       "      <td>53</td>\n",
       "      <td>+20.868</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>1:25.566</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          No            Driver                   Team  Starting Grid  Laps  \\\n",
       "Position                                                                     \n",
       "1          3  Daniel Ricciardo       McLaren Mercedes              2    53   \n",
       "2          4      Lando Norris       McLaren Mercedes              3    53   \n",
       "3         77   Valtteri Bottas               Mercedes             19    53   \n",
       "4         16   Charles Leclerc                Ferrari              5    53   \n",
       "5         11      Sergio Perez  Red Bull Racing Honda              8    53   \n",
       "6         55      Carlos Sainz                Ferrari              6    53   \n",
       "7         18      Lance Stroll  Aston Martin Mercedes              9    53   \n",
       "8         14   Fernando Alonso         Alpine Renault             10    53   \n",
       "9         63    George Russell      Williams Mercedes             14    53   \n",
       "10        31      Esteban Ocon         Alpine Renault             12    53   \n",
       "\n",
       "         Time/Retired  Points +1 Pt Fastest Lap  \n",
       "Position                                         \n",
       "1         1:21:54.365      26   Yes    1:24.812  \n",
       "2              +1.747      18    No    1:24.971  \n",
       "3              +4.921      15    No    1:24.872  \n",
       "4              +7.309      12    No    1:25.319  \n",
       "5              +8.723      10    No    1:25.156  \n",
       "6             +10.535       8    No    1:25.559  \n",
       "7             +15.804       6    No    1:25.853  \n",
       "8             +17.201       4    No    1:25.472  \n",
       "9             +19.742       2    No    1:25.835  \n",
       "10            +20.868       1    No    1:25.566  "
      ]
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     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ItalyResults = raceResults[raceResults['Track'] == 'Italy'].set_index('Position').drop('Track', axis=1).head(10)\n",
    "ItalyResults['Points'] = ItalyResults['Points'].astype(int)\n",
    "ItalyResults"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fde66b50",
   "metadata": {},
   "source": [
    "Now, the Italian Grand Prix in Monza, one of the iconic circuits also known as _the Temple of Speed_.\n",
    "\n",
    "Surely, the most unforgettable moment there was **the collision between Verstappen and Hamilton** on lap 26. The Dutchman attempted to overtake the British driver coming into turn 1, but after the tyre contact together with the sausage kerb, Verstappen's Red Bull lifted up into the air and then its back side landed on Hamilton's Mercedes, pushing it into the sand pool. Additionally, the scary moment there, without a doubt, was the rear right tyre of Verstappen's car **touching Hamilton's helmet**, but he was left unharmed, thanks to the **protection provided by halo**, preventing him from getting serious injury. All things considered, both drivers became DNF and walked away from the track unpleased, overall another red flag due to this incident...\n",
    "\n",
    "On the other hand, **McLaren** absolutely lived a wonderful weekend in Monza! Without the existence of two biggest rivals there, and with their strong pace, **Daniel Ricciardo** won the race and his teammate **Lando Norris** finished second! If you ask what these meant for this team, it was **their first win after 9 years** and nonetheless, **first 1-2 double finish since 2010**! What a great achievement for the name of British luxury sports car manufacturer, that they took all the opportunities to claim the win they missed for almost a decade!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67ded5dd",
   "metadata": {},
   "source": [
    "### Rolex Turkish Grand Prix 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "95a71cbd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Position</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <td>Valtteri Bottas</td>\n",
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       "      <td>1</td>\n",
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       "      <td>26</td>\n",
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       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>2</td>\n",
       "      <td>58</td>\n",
       "      <td>+14.584</td>\n",
       "      <td>18</td>\n",
       "      <td>No</td>\n",
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       "      <th>3</th>\n",
       "      <td>11</td>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>6</td>\n",
       "      <td>58</td>\n",
       "      <td>+33.471</td>\n",
       "      <td>15</td>\n",
       "      <td>No</td>\n",
       "      <td>1:32.459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>16</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>3</td>\n",
       "      <td>58</td>\n",
       "      <td>+37.814</td>\n",
       "      <td>12</td>\n",
       "      <td>No</td>\n",
       "      <td>1:32.737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>11</td>\n",
       "      <td>58</td>\n",
       "      <td>+41.812</td>\n",
       "      <td>10</td>\n",
       "      <td>No</td>\n",
       "      <td>1:32.763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10</td>\n",
       "      <td>Pierre Gasly</td>\n",
       "      <td>AlphaTauri Honda</td>\n",
       "      <td>4</td>\n",
       "      <td>58</td>\n",
       "      <td>+44.292</td>\n",
       "      <td>8</td>\n",
       "      <td>No</td>\n",
       "      <td>1:32.814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>4</td>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>7</td>\n",
       "      <td>58</td>\n",
       "      <td>+47.213</td>\n",
       "      <td>6</td>\n",
       "      <td>No</td>\n",
       "      <td>1:32.446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>55</td>\n",
       "      <td>Carlos Sainz</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>19</td>\n",
       "      <td>58</td>\n",
       "      <td>+51.526</td>\n",
       "      <td>4</td>\n",
       "      <td>No</td>\n",
       "      <td>1:31.921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>18</td>\n",
       "      <td>Lance Stroll</td>\n",
       "      <td>Aston Martin Mercedes</td>\n",
       "      <td>8</td>\n",
       "      <td>58</td>\n",
       "      <td>+82.018</td>\n",
       "      <td>2</td>\n",
       "      <td>No</td>\n",
       "      <td>1:32.608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>31</td>\n",
       "      <td>Esteban Ocon</td>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>12</td>\n",
       "      <td>57</td>\n",
       "      <td>+1 lap</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>1:34.584</td>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          No           Driver                   Team  Starting Grid  Laps  \\\n",
       "Position                                                                    \n",
       "1         77  Valtteri Bottas               Mercedes              1    58   \n",
       "2         33   Max Verstappen  Red Bull Racing Honda              2    58   \n",
       "3         11     Sergio Perez  Red Bull Racing Honda              6    58   \n",
       "4         16  Charles Leclerc                Ferrari              3    58   \n",
       "5         44   Lewis Hamilton               Mercedes             11    58   \n",
       "6         10     Pierre Gasly       AlphaTauri Honda              4    58   \n",
       "7          4     Lando Norris       McLaren Mercedes              7    58   \n",
       "8         55     Carlos Sainz                Ferrari             19    58   \n",
       "9         18     Lance Stroll  Aston Martin Mercedes              8    58   \n",
       "10        31     Esteban Ocon         Alpine Renault             12    57   \n",
       "\n",
       "         Time/Retired  Points +1 Pt Fastest Lap  \n",
       "Position                                         \n",
       "1         1:31:04.103      26   Yes    1:30.432  \n",
       "2             +14.584      18    No    1:32.759  \n",
       "3             +33.471      15    No    1:32.459  \n",
       "4             +37.814      12    No    1:32.737  \n",
       "5             +41.812      10    No    1:32.763  \n",
       "6             +44.292       8    No    1:32.814  \n",
       "7             +47.213       6    No    1:32.446  \n",
       "8             +51.526       4    No    1:31.921  \n",
       "9             +82.018       2    No    1:32.608  \n",
       "10             +1 lap       1    No    1:34.584  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TurkeyResults = raceResults[raceResults['Track'] == 'Turkey'].set_index('Position').drop('Track', axis=1).head(10)\n",
    "TurkeyResults['Points'] = TurkeyResults['Points'].astype(int)\n",
    "TurkeyResults"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ea537f7",
   "metadata": {},
   "source": [
    "It was great to see the **Turkish GP** once more in this season's calendar, after 2020; where the race in Istanbul Park Circuit was marked as one the most exciting races, mainly due to the effect of rainy conditions that could challenge the drivers all the time, resulted in **Lance Stroll**'s astounding pole position and **Lewis Hamilton**'s obtainment of 7th world championship title!\n",
    "\n",
    "This year, the days of that weekend coincided with **mixed weather conditions**, but the effect of rain when occurred was less severe, compared to 2020. Here, **Valtteri Bottas** had a perfect race on Sunday by starting in pole position (actually, his teammate Hamilton, but received grid penalties for new power unit components), leading every lap, setting the fastest lap and certainly, crowned for the win! Both Red Bull drivers' pace were not enough the catch the Mercedes driver up, thus Verstappen and Perez finished in the podium alongside him. Furthermore, it was special for Red Bull as they presented a **white livery** on their cars to **commemorate the past accomplishments by their engine supplier, Honda**.\n",
    "\n",
    "There should also be one more thing to mention that **Esteban Ocon** completed the race with **the same intermediate tyre** all the time (although he was 1 lap behind the leader and finished 10th to claim the last point, plus **no mandatory pit-stop to change the tyre compound** when the track surface was wet)! We believe that Alpine team and Ocon himself had their hearts in their mouths as the rubber (mostly the front left tyre) was getting thinner every lap, but luckily, it wasn't exploded before the race finish."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f5994cf",
   "metadata": {},
   "source": [
    "### Heineken Gran Premio de Sao Paulo 2021 (Brazil)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "672b8cc3",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>No</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>Position</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>10</td>\n",
       "      <td>71</td>\n",
       "      <td>1:32:22.851</td>\n",
       "      <td>25</td>\n",
       "      <td>No</td>\n",
       "      <td>1:11.982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>2</td>\n",
       "      <td>71</td>\n",
       "      <td>+10.496</td>\n",
       "      <td>18</td>\n",
       "      <td>No</td>\n",
       "      <td>1:12.486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>77</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>1</td>\n",
       "      <td>71</td>\n",
       "      <td>+13.576</td>\n",
       "      <td>15</td>\n",
       "      <td>No</td>\n",
       "      <td>1:12.526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11</td>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>4</td>\n",
       "      <td>71</td>\n",
       "      <td>+39.940</td>\n",
       "      <td>13</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:11.010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>16</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>6</td>\n",
       "      <td>71</td>\n",
       "      <td>+49.517</td>\n",
       "      <td>10</td>\n",
       "      <td>No</td>\n",
       "      <td>1:12.822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>55</td>\n",
       "      <td>Carlos Sainz</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>3</td>\n",
       "      <td>71</td>\n",
       "      <td>+51.820</td>\n",
       "      <td>8</td>\n",
       "      <td>No</td>\n",
       "      <td>1:12.710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10</td>\n",
       "      <td>Pierre Gasly</td>\n",
       "      <td>AlphaTauri Honda</td>\n",
       "      <td>7</td>\n",
       "      <td>70</td>\n",
       "      <td>+1 lap</td>\n",
       "      <td>6</td>\n",
       "      <td>No</td>\n",
       "      <td>1:13.227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>31</td>\n",
       "      <td>Esteban Ocon</td>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>+1 lap</td>\n",
       "      <td>4</td>\n",
       "      <td>No</td>\n",
       "      <td>1:14.430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>14</td>\n",
       "      <td>Fernando Alonso</td>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>12</td>\n",
       "      <td>70</td>\n",
       "      <td>+1 lap</td>\n",
       "      <td>2</td>\n",
       "      <td>No</td>\n",
       "      <td>1:13.922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>4</td>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>5</td>\n",
       "      <td>70</td>\n",
       "      <td>+1 lap</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>1:13.761</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          No           Driver                   Team  Starting Grid  Laps  \\\n",
       "Position                                                                    \n",
       "1         44   Lewis Hamilton               Mercedes             10    71   \n",
       "2         33   Max Verstappen  Red Bull Racing Honda              2    71   \n",
       "3         77  Valtteri Bottas               Mercedes              1    71   \n",
       "4         11     Sergio Perez  Red Bull Racing Honda              4    71   \n",
       "5         16  Charles Leclerc                Ferrari              6    71   \n",
       "6         55     Carlos Sainz                Ferrari              3    71   \n",
       "7         10     Pierre Gasly       AlphaTauri Honda              7    70   \n",
       "8         31     Esteban Ocon         Alpine Renault              8    70   \n",
       "9         14  Fernando Alonso         Alpine Renault             12    70   \n",
       "10         4     Lando Norris       McLaren Mercedes              5    70   \n",
       "\n",
       "         Time/Retired  Points +1 Pt Fastest Lap  \n",
       "Position                                         \n",
       "1         1:32:22.851      25    No    1:11.982  \n",
       "2             +10.496      18    No    1:12.486  \n",
       "3             +13.576      15    No    1:12.526  \n",
       "4             +39.940      13   Yes    1:11.010  \n",
       "5             +49.517      10    No    1:12.822  \n",
       "6             +51.820       8    No    1:12.710  \n",
       "7              +1 lap       6    No    1:13.227  \n",
       "8              +1 lap       4    No    1:14.430  \n",
       "9              +1 lap       2    No    1:13.922  \n",
       "10             +1 lap       1    No    1:13.761  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BrazilResults = raceResults[raceResults['Track'] == 'Brazil'].set_index('Position').drop('Track', axis=1).head(10)\n",
    "BrazilResults['Points'] = BrazilResults['Points'].astype(int)\n",
    "BrazilResults"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38f4281c",
   "metadata": {},
   "source": [
    "The Brazilian GP in Interlagos usually contained thrilling moments in the past, and this season, we have experienced familiar things such that the main focus point was **Lewis Hamilton** in the whole weekend.\n",
    "\n",
    "Everything started with the Briton's car being marked as **illegal** after the qualifying because of **the rear-wing rule infringement**, resulted in starting at the back of the grid in Sprint qualifying (see details below). However, Hamilton showed his strength, climbed up positions lap after lap and succeeded to place in **5th** after the end of that session, but another grid penalty was applied due to additional usage of power unit elements, hence readied himself to start the main race in **10th**.\n",
    "\n",
    "His perseverance continued even on Sunday; during the race we saw him overtaking rivals in the first couple of laps to reach Red Bulls, especially Max Verstappen, and his mind was telling him to take the race victory at all costs! Through the rest of the race, we have sighted **several fights between these two drivers** while also being as fair as possible with respect to track limits. Of course, their teammates, Bottas and Perez, accompanied them behind or side-to-side to support and show their superorities against each other.\n",
    "\n",
    "As a consequence, **Hamilton took the chequered flag first**, while his closest rival Verstappen crossed the finish line as second! Then, their teammates came after them, but Perez from Red Bull **strategically stole the fastest lap point** from Mercedes and Hamilton... All in all, we will remember this weekend for the British driver's struggle with grid penalties, but not giving up the fight until the last moment and his triumphant."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30124d0d",
   "metadata": {},
   "source": [
    "### Etihad Airways Abu Dhabi Grand Prix 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "d9573da3",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>No</th>\n",
       "      <th>Driver</th>\n",
       "      <th>Team</th>\n",
       "      <th>Starting Grid</th>\n",
       "      <th>Laps</th>\n",
       "      <th>Time/Retired</th>\n",
       "      <th>Points</th>\n",
       "      <th>+1 Pt</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>Position</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>1</td>\n",
       "      <td>58</td>\n",
       "      <td>1:30:17.345</td>\n",
       "      <td>26</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:26.103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>2</td>\n",
       "      <td>58</td>\n",
       "      <td>+2.256</td>\n",
       "      <td>18</td>\n",
       "      <td>No</td>\n",
       "      <td>1:26.615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>55</td>\n",
       "      <td>Carlos Sainz</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>5</td>\n",
       "      <td>58</td>\n",
       "      <td>+5.173</td>\n",
       "      <td>15</td>\n",
       "      <td>No</td>\n",
       "      <td>1:27.618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>22</td>\n",
       "      <td>Yuki Tsunoda</td>\n",
       "      <td>AlphaTauri Honda</td>\n",
       "      <td>8</td>\n",
       "      <td>58</td>\n",
       "      <td>+5.692</td>\n",
       "      <td>12</td>\n",
       "      <td>No</td>\n",
       "      <td>1:27.496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10</td>\n",
       "      <td>Pierre Gasly</td>\n",
       "      <td>AlphaTauri Honda</td>\n",
       "      <td>12</td>\n",
       "      <td>58</td>\n",
       "      <td>+6.531</td>\n",
       "      <td>10</td>\n",
       "      <td>No</td>\n",
       "      <td>1:27.342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>77</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>6</td>\n",
       "      <td>58</td>\n",
       "      <td>+7.463</td>\n",
       "      <td>8</td>\n",
       "      <td>No</td>\n",
       "      <td>1:26.862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>4</td>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>3</td>\n",
       "      <td>58</td>\n",
       "      <td>+59.200</td>\n",
       "      <td>6</td>\n",
       "      <td>No</td>\n",
       "      <td>1:26.762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>14</td>\n",
       "      <td>Fernando Alonso</td>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>11</td>\n",
       "      <td>58</td>\n",
       "      <td>+61.708</td>\n",
       "      <td>4</td>\n",
       "      <td>No</td>\n",
       "      <td>1:27.607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>31</td>\n",
       "      <td>Esteban Ocon</td>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>9</td>\n",
       "      <td>58</td>\n",
       "      <td>+64.026</td>\n",
       "      <td>2</td>\n",
       "      <td>No</td>\n",
       "      <td>1:28.249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>16</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>7</td>\n",
       "      <td>58</td>\n",
       "      <td>+66.057</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>1:28.433</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          No           Driver                   Team  Starting Grid  Laps  \\\n",
       "Position                                                                    \n",
       "1         33   Max Verstappen  Red Bull Racing Honda              1    58   \n",
       "2         44   Lewis Hamilton               Mercedes              2    58   \n",
       "3         55     Carlos Sainz                Ferrari              5    58   \n",
       "4         22     Yuki Tsunoda       AlphaTauri Honda              8    58   \n",
       "5         10     Pierre Gasly       AlphaTauri Honda             12    58   \n",
       "6         77  Valtteri Bottas               Mercedes              6    58   \n",
       "7          4     Lando Norris       McLaren Mercedes              3    58   \n",
       "8         14  Fernando Alonso         Alpine Renault             11    58   \n",
       "9         31     Esteban Ocon         Alpine Renault              9    58   \n",
       "10        16  Charles Leclerc                Ferrari              7    58   \n",
       "\n",
       "         Time/Retired  Points +1 Pt Fastest Lap  \n",
       "Position                                         \n",
       "1         1:30:17.345      26   Yes    1:26.103  \n",
       "2              +2.256      18    No    1:26.615  \n",
       "3              +5.173      15    No    1:27.618  \n",
       "4              +5.692      12    No    1:27.496  \n",
       "5              +6.531      10    No    1:27.342  \n",
       "6              +7.463       8    No    1:26.862  \n",
       "7             +59.200       6    No    1:26.762  \n",
       "8             +61.708       4    No    1:27.607  \n",
       "9             +64.026       2    No    1:28.249  \n",
       "10            +66.057       1    No    1:28.433  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AbuDhabiResults = raceResults[raceResults['Track'] == 'Abu Dhabi'].set_index('Position').drop('Track', axis=1).head(10)\n",
    "AbuDhabiResults['Points'] = AbuDhabiResults['Points'].astype(int)\n",
    "AbuDhabiResults"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "315aeb8c",
   "metadata": {},
   "source": [
    "Here comes the last race of the season! It is unbeliveable to see that both Hamilton and Verstappen came to Abu Dhabi, **having their points equalized (369.5)** after Saudi Arabia GP! That was something we rarely testified in Formula 1 where the championship title will be decided **in the final race** among all eligible drivers! So, for this season, leaving the previous results aside, it was up to only **two drivers** for the championship; and mathematically, any driver who finished ahead of his rival would definitely take the title! Also note that, Yas Marina circuit was redesigned this season by removing a few turns for easiness and get the average speed a little faster overall.\n",
    "\n",
    "Speaking of the race, we saw the two closest rivals started at the front row, where Verstappen was on pole position and Hamilton was second. It is undeniable to say that **both drivers had their fights continuously against each other**, even in the last race, and particularly Perez sometimes helped his teammate to slow Hamilton down a bit! _(Did you remember when Verstappen and/or his race engineer told that Perez was absolute animal?)_ Well, the excitement, the tension, the stress, the heart-beating... Whatever you say, every mood was at the peak for all staff from Mercedes and Red Bull, including the people who supported Hamilton and Verstappen, as well as for the others.\n",
    "\n",
    "Well, the actual incidents and dramatic moments of the race began when the Williams driver **Nicholas Latifi** had an accident with several laps remaining and Safety Car was deployed. While the car and debris were being cleaned, during that period Verstappen was **called to the pit for fresh soft tyres**, while Hamilton stayed out on track with **40-lap old hard tyres**. After that, there were **several lapped cars** between these two rivals while the Safety Car was roaming, but at one moment, FIA race director Michael Masi stated that **the lapped cars could overtake to unlap themselves!** Yes, that was a crucial decision that could significantly affect the rest of the race, as Mercedes' team principal Toto Wolff criticized Masi for that, saying _\"No, no, Michael, no! That was so not right!\"_ However, with this decision, the race director insisted that it was convenient for motor racing!\n",
    "\n",
    "Can you really believe it? After the Safety Car period and these incidents, there was **only one lap left** to go and determine the championship title for either Hamilton or Verstappen, and no car remained between them! **It was totally do or die!**\n",
    "\n",
    "In the turn 5 of Yas Marina Circuit on the last lap, Verstappen **successfully passed Hamilton**, thanks to his new soft tyres! Later, the Briton could not succeed to take the position back from the Dutchman even in the long straights afterwards! If you were watching the moment, be it on the TV, on the Internet or in the grandstand, did you believe that everything was in favor of Verstappen's side after it happened? To tell the truth, the answer was absolutely **'yes'** when he crossed the finish line.\n",
    "\n",
    "Whoa! After coming through all of these, **Max Verstappen became the world champion of Formula 1 2021 Season**, winning the Abu Dhabi GP and finishing ahead of Hamilton! We all heard the screams from himself, his race engineer, Christian Horner, all team staff as they all became crazy, plus the happiness of his supporters (especially the Orange Army) from all around the world! It was certain that 24-year old Verstappen made history in Formula 1!\n",
    "\n",
    "_What about Lewis Hamilton and Mercedes team?_ Despite winning the constructors' championship title, they remained completely silent after all these incidents happened and thought the chance for drivers championship title was slipped away by the FIA, especially Michael Masi. At least for the necessity of sportsmanship, **we saw Hamilton congratulating Verstappen** after the race and at the podium, but his face certainly **looked unamused** at all! Even Mercedes going appeal for the incidents in the race happened to the FIA did not help them change the result by any means, so it was clear that Max Verstappen added the championship title to his career!\n",
    "\n",
    "After the conclusion of the season, we could not see Hamilton anywhere for a long time, even nothing new from his social media accounts. We all became curious for what he was doing in the silent times... In February 2022, at last he posted a photo in Twitter, saying that _\"I've been gone, but I'm back.\"_"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04bdcbe7",
   "metadata": {},
   "source": [
    "## 2021 Season - Driver Standings\n",
    "\n",
    "By learning many things from the discussions of notables races in 2021, let's see how the driver standings has been shaped after 22 races:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "087074ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Driver</th>\n",
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       "      <th>Points</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Max Verstappen</td>\n",
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       "      <td>395.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>387.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>226.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Carlos Sainz</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>164.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>160.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>159.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Daniel Ricciardo</td>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>115.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Pierre Gasly</td>\n",
       "      <td>AlphaTauri Honda</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Fernando Alonso</td>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>81.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Esteban Ocon</td>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>74.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Sebastian Vettel</td>\n",
       "      <td>Aston Martin Mercedes</td>\n",
       "      <td>43.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Lance Stroll</td>\n",
       "      <td>Aston Martin Mercedes</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Yuki Tsunoda</td>\n",
       "      <td>AlphaTauri Honda</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>George Russell</td>\n",
       "      <td>Williams Mercedes</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Kimi Raikkönen</td>\n",
       "      <td>Alfa Romeo Racing Ferrari</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Nicholas Latifi</td>\n",
       "      <td>Williams Mercedes</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Antonio Giovinazzi</td>\n",
       "      <td>Alfa Romeo Racing Ferrari</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Nikita Mazepin</td>\n",
       "      <td>Haas Ferrari</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Robert Kubica</td>\n",
       "      <td>Alfa Romeo Racing Ferrari</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Mick Schumacher</td>\n",
       "      <td>Haas Ferrari</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Driver                       Team  Points\n",
       "1       Max Verstappen      Red Bull Racing Honda   395.5\n",
       "2       Lewis Hamilton                   Mercedes   387.5\n",
       "3      Valtteri Bottas                   Mercedes   226.0\n",
       "4         Sergio Perez      Red Bull Racing Honda   190.0\n",
       "5         Carlos Sainz                    Ferrari   164.5\n",
       "6         Lando Norris           McLaren Mercedes   160.0\n",
       "7      Charles Leclerc                    Ferrari   159.0\n",
       "8     Daniel Ricciardo           McLaren Mercedes   115.0\n",
       "9         Pierre Gasly           AlphaTauri Honda   110.0\n",
       "10     Fernando Alonso             Alpine Renault    81.0\n",
       "11        Esteban Ocon             Alpine Renault    74.0\n",
       "12    Sebastian Vettel      Aston Martin Mercedes    43.0\n",
       "13        Lance Stroll      Aston Martin Mercedes    34.0\n",
       "14        Yuki Tsunoda           AlphaTauri Honda    32.0\n",
       "15      George Russell          Williams Mercedes    16.0\n",
       "16      Kimi Raikkönen  Alfa Romeo Racing Ferrari    10.0\n",
       "17     Nicholas Latifi          Williams Mercedes     7.0\n",
       "18  Antonio Giovinazzi  Alfa Romeo Racing Ferrari     3.0\n",
       "19      Nikita Mazepin               Haas Ferrari     0.0\n",
       "20       Robert Kubica  Alfa Romeo Racing Ferrari     0.0\n",
       "21     Mick Schumacher               Haas Ferrari     0.0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "driverPts = raceResults.groupby(['Driver', 'Team'])['Points'].sum()\n",
    "sprintQualiDriverPts = sprintQualiResults.groupby(['Driver', 'Team'])['Points'].sum()\n",
    "driverPts = (driverPts+sprintQualiDriverPts).sort_values(ascending=False).reset_index()\n",
    "driverPts.index = [i for i in range(1,22)]\n",
    "driverPts"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23134e42",
   "metadata": {},
   "source": [
    "Certainly, **Max Verstappen** is the champion of 2021 Season and it ended up by 8 points ahead of **Lewis Hamilton** after a season-long competition between each other. It is quite natural that their teammates, **Bottas** and **Perez** placed 3rd and 4th, also helped in these battles with regards to strategic moves such as the attempts to slow down their opponents, and more importantly, their contributions to valuable points for standings of their teams.\n",
    "\n",
    "The places between **5th and 8th** places were occupied by Ferrari and McLaren drivers. Here, it is interesting to see that **Carlos Sainz** (in his first season of Ferrari) outperformed everyone in the group, including his teammate **Leclerc**! For McLaren, it is similar that **Lando Norris** got ahead of **Ricciardo** (also, his first season in the British team).\n",
    "\n",
    "**Gasly** seemed to do a good job in the whole season under AlphaTauri, by accumulating more than 100 points; but for the rookie **Tsunoda**, the gap was big against the Frenchman.\n",
    "\n",
    "Then, we see Alpine and Aston Martin drivers in the list; the veterans **Alonso** and **Vettel** finished the season ahead of their teammates **Ocon** and **Stroll**, respectively.\n",
    "\n",
    "Next, Williams and Alfa Romeo drivers existed between 15th and 18th places. Within that group, **George Russell** have beaten his rivals, including **Raikkönen** and finally saw him as point scorer in the long-dated team.\n",
    "\n",
    "About Haas, we never witnessed their drivers **Schumacher** and **Mazepin** scoring points in 2021, and they stayed in almost all races as backmarkers."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe11db16",
   "metadata": {},
   "source": [
    "## Points Progression of Top 10 Drivers\n",
    "\n",
    "If the table above is not enough, then a data visualization should greatly enlighten us for how the drivers progressed through the races of 2021 Season. Here, let's take the drivers who **finished in the top 10 of drivers standings**, and follow the **solid or dashed lines**:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "714e658f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tracks = raceResults['Track'].unique()\n",
    "plt.style.use('seaborn')\n",
    "plt.style.use('dark_background')\n",
    "plt.rcParams['axes.facecolor'] = '#15151d'\n",
    "plt.rcParams['figure.facecolor'] = '#15151d'\n",
    "plt.rcParams['grid.color'] = '#444444'\n",
    "top10 = driverPts['Driver'].values[:10]\n",
    "c = assign_color(\"drivers\", top10)\n",
    "plt.figure(figsize=(16,7))\n",
    "plt.axis([-0.4, 21.4, -10, 410])\n",
    "for i in range(len(top10)):\n",
    "    ls = '-'\n",
    "    pts = raceResults[raceResults['Driver'] == top10[i]]['Points'].values\n",
    "    if top10[i] == \"Max Verstappen\":     pts[9] += 3;  pts[13] += 2;  pts[18] += 2\n",
    "    elif top10[i] == \"Lewis Hamilton\":   pts[9] += 2;\n",
    "    elif top10[i] == \"Valtteri Bottas\":  pts[9] += 1;  pts[13] += 3;  pts[18] += 3;  ls = '--';\n",
    "    elif top10[i] == \"Daniel Ricciardo\":  pts[13] += 1;  ls = '--';\n",
    "    elif top10[i] == \"Carlos Sainz\":     pts[18] += 1;\n",
    "    elif top10[i] == \"Sergio Perez\" or top10[i] == \"Charles Leclerc\":  ls = '--'\n",
    "    plt.plot(np.cumsum(pts), linewidth=3, label=top10[i].split()[1], color=c[i], linestyle=ls)\n",
    "plt.title(\"Formula 1 - 2021 Season\\nTop 10 Drivers' Points Progression\", color='#bbbbbb', fontsize=22, fontweight='bold')\n",
    "plt.legend(fontsize=15)\n",
    "plt.xlabel('RACES', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.xticks(range(0,len(tracks)), tracks, fontsize=14, color='#ffff55', rotation=80)\n",
    "plt.ylabel('POINTS', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.yticks(fontsize=14, color='#ffff55')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92b6ab83",
   "metadata": {},
   "source": [
    "Yeah, we can definitely say that both **Verstappen** and **Hamilton** were in **another league**! Can you see how the gap was getting increased against the rest of the drivers after each race? Moreover, the graphic tells us sometimes Hamilton was the leading the championship, sometimes Verstappen (plus, no other drivers!); and in terms of height (points), we see the blue solid line being higher than the other.\n",
    "\n",
    "Hopefully, this gives a clear picture of how these drivers proceeded in the whole season as the standings continuously changed race after race.\n",
    "\n",
    "**To make it even more explanatory for the rivalry between Verstappen and Hamilton, there's another visualization below to show the points gap and which driver was in favor for the championship:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "fb68bb4f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "verPts = raceResults[raceResults['Driver'] == 'Max Verstappen']['Points'].values\n",
    "verPts[9] += 3;  verPts[13] += 2;  verPts[18] += 2\n",
    "hamPts = raceResults[raceResults['Driver'] == 'Lewis Hamilton']['Points'].values\n",
    "hamPts[9] += 2\n",
    "pointsGap = np.cumsum(verPts) - np.cumsum(hamPts)\n",
    "c = []\n",
    "for i in range(len(pointsGap)):\n",
    "    if pointsGap[i] >= 0:   c.append('#0600f0')\n",
    "    else:    c.append('#00d2b5')\n",
    "plt.figure(figsize=(16,7))\n",
    "plt.axis([-0.7, 21.7, min(pointsGap)-3, max(pointsGap)+4])\n",
    "plt.bar(tracks, pointsGap, color=c)\n",
    "for i in range(len(pointsGap)):\n",
    "    if pointsGap[i] >= 0:   vsh = 0.5\n",
    "    else:   vsh = -2\n",
    "    plt.text(i-0.2, pointsGap[i]+vsh, \"{:2}\".format(int(abs(pointsGap[i]))), fontsize=16)\n",
    "plt.axhline(0, color='#aaaaaa')\n",
    "plt.text(17.5, 32, \"VERSTAPPEN\", color=\"#0600f0\", fontsize=20, fontweight='bold')\n",
    "plt.text(18, -13, \"HAMILTON\", color=\"#00d2b5\", fontsize=20, fontweight='bold')\n",
    "plt.title(\"Formula 1 - 2021 Season\\nHead to Head - Verstappen vs Hamilton\", color='#bbbbbb', \n",
    "          fontsize=22, fontweight='bold')\n",
    "plt.xlabel('RACES', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.xticks(range(0,len(tracks)), tracks, fontsize=14, color='#ffff55', rotation=80)\n",
    "plt.ylabel('POINTS GAP', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.yticks(fontsize=16, color='#ffff55')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f50f32c1",
   "metadata": {},
   "source": [
    "**That's the exact one we'd like to see! This explains the whole story of the biggest two rivals in 2021 Season!**\n",
    "\n",
    "Here, in the first 4 races, Hamilton was leading. After Monaco, Verstappen has taken the championship lead (he experienced that for the first time in his career) and even extended the gap **by up to 32 points** after Austria GP!\n",
    "\n",
    "Later, the Briton again took the lead once more in Hungary, and continued in Belgium. Then, the needle changed into Verstappen's direction for Netherlands and Italy (Monza). Next, Hamilton grabbed that back in Russia with only 2-points gap.\n",
    "\n",
    "From Turkey to Qatar GP, the Dutchman was in favor for the title. After Saudi Arabia, it is unbelievable to see that the points of these two rivals have been equalized! So, the node of the championship would be solved in the last race, Abu Dhabi. As everyone knows, it was ended with Verstappen being the champion of 2021.\n",
    "\n",
    "_To be honest, we've never lived such a battle that could last till the end of a season for a long time in Formula 1 history. Surely, year 2021 will be remembered as one of the epic seasons..._"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2eb7856",
   "metadata": {},
   "source": [
    "## 2021 Season - Constructor Standings\n",
    "\n",
    "Now, let's discuss how the constructor standings has been resulted in 2021 Season:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "fa5f52ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Team</th>\n",
       "      <th>Points</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mercedes</td>\n",
       "      <td>613.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>585.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ferrari</td>\n",
       "      <td>323.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>275.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>155.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>AlphaTauri Honda</td>\n",
       "      <td>142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Aston Martin Mercedes</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Williams Mercedes</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Alfa Romeo Racing Ferrari</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Haas Ferrari</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Team  Points\n",
       "1                    Mercedes   613.5\n",
       "2       Red Bull Racing Honda   585.5\n",
       "3                     Ferrari   323.5\n",
       "4            McLaren Mercedes   275.0\n",
       "5              Alpine Renault   155.0\n",
       "6            AlphaTauri Honda   142.0\n",
       "7       Aston Martin Mercedes    77.0\n",
       "8           Williams Mercedes    23.0\n",
       "9   Alfa Romeo Racing Ferrari    13.0\n",
       "10               Haas Ferrari     0.0"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "teamPts = raceResults.groupby('Team')['Points'].sum()\n",
    "sprintQualiTeamPts = sprintQualiResults.groupby('Team')['Points'].sum()\n",
    "teamPts = (teamPts+sprintQualiTeamPts).sort_values(ascending=False).reset_index()\n",
    "teamPts.index = [i for i in range(1,11)]\n",
    "teamPts"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c67250d",
   "metadata": {},
   "source": [
    "As seen from the table above, **Mercedes** secured their constructors' championship title once again. And, that's the **8th consecutive season**! In other words, since 2014, that is, since the beginning of the **1.6 litre turbo hybrid engine era**, no other teams have ever obtained that title, thus an extraordinary achievement for the German team! However, the same thing can not be said for drivers' standings this year, due to the incidents happened in Abu Dhabi, they handed over the title to Max Verstappen of **Red Bull Racing**. Of course, it is not surprising that the Austrian team became the runner-up in this competitive season.\n",
    "\n",
    "For the **3rd place**, we've witnessed good battles between **Ferrari** and **McLaren**, but at the end, the iconic Italian team deserved to come behind the top two teams.\n",
    "\n",
    "A similar competitive has also been seen between **Alpine** and **AlphaTauri** for **5th place**. As a result, the Renault-powered French team got ahead of their rivals of mid-pack.\n",
    "\n",
    "About **Aston Martin** (with the re-brand from Racing Point), they seemed to guarantee the **7th place**, as there are large point gaps against the teams of one place above and below.\n",
    "\n",
    "After two and a half years, we've finally seen **Williams** scoring points in several races, hence they got rid of being the last team, even surpassing **Alfa Romeo**.\n",
    "\n",
    "**Haas** was the only team completing the season as pointless! The reason might be because they almost never invested development for their cars and planned to transfer everything for the next season. It was a kind of season in vain!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ad49501",
   "metadata": {},
   "source": [
    "## 2021 Season - Sprint Qualifying Results & Points\n",
    "\n",
    "Sprint Qualifying is the newest feature introduced in F1 2021 Season.\n",
    "\n",
    "In the race weekends where this format is available on Saturday, a total of **two** practice sessions are held (one each on Friday and Saturday) and drivers are placed at the grid for Sprint Qualifying according to **the results obtained on Friday qualifying session**. The race distance is set to **at least 100 kilometres** and there are **no mandatory pit-stops**. That is, it's just pure racing which lasts roughly **one third** of the time compared to regular race session! Lastly, the result of the Sprint Qualifying constitutes the starting grid of the race session on Sunday and the driver finished in the 1st place is awarded with **pole position**!\n",
    "\n",
    "The purpose of bringing this qualifying format is to let the drivers struggle **for gaining positions** against opponents and **mix the grid altogether** before the main race. When the sprint ends, no trophy is given to the drivers finishing in top 3, only medals for their success and **3**, **2** and **1** points, respectively.\n",
    "\n",
    "If Sprint Qualifying is found to be successful by the drivers and teams, as well as FIA, then it can be sustained for the next seasons and more race weekends might contain this session."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2250affa",
   "metadata": {},
   "source": [
    "**Below you can see the top 10 results of the Sprint Qualifying sessions that were held in only three different race weekends in 2021:**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33956c0d",
   "metadata": {},
   "source": [
    "### Great Britain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "0a86dbbc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Track</th>\n",
       "      <th>No</th>\n",
       "      <th>Driver</th>\n",
       "      <th>Team</th>\n",
       "      <th>Starting Grid</th>\n",
       "      <th>Laps</th>\n",
       "      <th>Time/Retired</th>\n",
       "      <th>Points</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Position</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Great Britain</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>2</td>\n",
       "      <td>17</td>\n",
       "      <td>25:38.426</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Great Britain</td>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>+1.430</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Great Britain</td>\n",
       "      <td>77</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>+7.502</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Great Britain</td>\n",
       "      <td>16</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "      <td>+11.278</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Great Britain</td>\n",
       "      <td>4</td>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>6</td>\n",
       "      <td>17</td>\n",
       "      <td>+24.111</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Great Britain</td>\n",
       "      <td>3</td>\n",
       "      <td>Daniel Ricciardo</td>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>+30.959</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Great Britain</td>\n",
       "      <td>14</td>\n",
       "      <td>Fernando Alonso</td>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>11</td>\n",
       "      <td>17</td>\n",
       "      <td>+43.527</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Great Britain</td>\n",
       "      <td>5</td>\n",
       "      <td>Sebastian Vettel</td>\n",
       "      <td>Aston Martin Mercedes</td>\n",
       "      <td>10</td>\n",
       "      <td>17</td>\n",
       "      <td>+44.439</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Great Britain</td>\n",
       "      <td>63</td>\n",
       "      <td>George Russell</td>\n",
       "      <td>Williams Mercedes</td>\n",
       "      <td>8</td>\n",
       "      <td>17</td>\n",
       "      <td>+46.652</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Great Britain</td>\n",
       "      <td>31</td>\n",
       "      <td>Esteban Ocon</td>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>13</td>\n",
       "      <td>17</td>\n",
       "      <td>+47.395</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Track  No            Driver                   Team  \\\n",
       "Position                                                               \n",
       "1         Great Britain  33    Max Verstappen  Red Bull Racing Honda   \n",
       "2         Great Britain  44    Lewis Hamilton               Mercedes   \n",
       "3         Great Britain  77   Valtteri Bottas               Mercedes   \n",
       "4         Great Britain  16   Charles Leclerc                Ferrari   \n",
       "5         Great Britain   4      Lando Norris       McLaren Mercedes   \n",
       "6         Great Britain   3  Daniel Ricciardo       McLaren Mercedes   \n",
       "7         Great Britain  14   Fernando Alonso         Alpine Renault   \n",
       "8         Great Britain   5  Sebastian Vettel  Aston Martin Mercedes   \n",
       "9         Great Britain  63    George Russell      Williams Mercedes   \n",
       "10        Great Britain  31      Esteban Ocon         Alpine Renault   \n",
       "\n",
       "          Starting Grid  Laps Time/Retired  Points  \n",
       "Position                                            \n",
       "1                     2    17    25:38.426       3  \n",
       "2                     1    17       +1.430       2  \n",
       "3                     3    17       +7.502       1  \n",
       "4                     4    17      +11.278       0  \n",
       "5                     6    17      +24.111       0  \n",
       "6                     7    17      +30.959       0  \n",
       "7                    11    17      +43.527       0  \n",
       "8                    10    17      +44.439       0  \n",
       "9                     8    17      +46.652       0  \n",
       "10                   13    17      +47.395       0  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sprintQualiResults[sprintQualiResults['Track'] == 'Great Britain'].set_index('Position').head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f37a4383",
   "metadata": {},
   "source": [
    "### Italy (Monza)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6d8569da",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Italy</td>\n",
       "      <td>77</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>27:54.078</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Italy</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "      <td>+2.325</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Italy</td>\n",
       "      <td>3</td>\n",
       "      <td>Daniel Ricciardo</td>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>5</td>\n",
       "      <td>18</td>\n",
       "      <td>+14.534</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Italy</td>\n",
       "      <td>4</td>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>4</td>\n",
       "      <td>18</td>\n",
       "      <td>+18.835</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Italy</td>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>2</td>\n",
       "      <td>18</td>\n",
       "      <td>+20.011</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Italy</td>\n",
       "      <td>16</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>8</td>\n",
       "      <td>18</td>\n",
       "      <td>+23.442</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Italy</td>\n",
       "      <td>55</td>\n",
       "      <td>Carlos Sainz</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>7</td>\n",
       "      <td>18</td>\n",
       "      <td>+27.952</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Italy</td>\n",
       "      <td>99</td>\n",
       "      <td>Antonio Giovinazzi</td>\n",
       "      <td>Alfa Romeo Racing Ferrari</td>\n",
       "      <td>10</td>\n",
       "      <td>18</td>\n",
       "      <td>+31.089</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Italy</td>\n",
       "      <td>11</td>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>9</td>\n",
       "      <td>18</td>\n",
       "      <td>+31.680</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Italy</td>\n",
       "      <td>18</td>\n",
       "      <td>Lance Stroll</td>\n",
       "      <td>Aston Martin Mercedes</td>\n",
       "      <td>12</td>\n",
       "      <td>18</td>\n",
       "      <td>+38.671</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Track  No              Driver                       Team  \\\n",
       "Position                                                             \n",
       "1         Italy  77     Valtteri Bottas                   Mercedes   \n",
       "2         Italy  33      Max Verstappen      Red Bull Racing Honda   \n",
       "3         Italy   3    Daniel Ricciardo           McLaren Mercedes   \n",
       "4         Italy   4        Lando Norris           McLaren Mercedes   \n",
       "5         Italy  44      Lewis Hamilton                   Mercedes   \n",
       "6         Italy  16     Charles Leclerc                    Ferrari   \n",
       "7         Italy  55        Carlos Sainz                    Ferrari   \n",
       "8         Italy  99  Antonio Giovinazzi  Alfa Romeo Racing Ferrari   \n",
       "9         Italy  11        Sergio Perez      Red Bull Racing Honda   \n",
       "10        Italy  18        Lance Stroll      Aston Martin Mercedes   \n",
       "\n",
       "          Starting Grid  Laps Time/Retired  Points  \n",
       "Position                                            \n",
       "1                     1    18    27:54.078       3  \n",
       "2                     3    18       +2.325       2  \n",
       "3                     5    18      +14.534       1  \n",
       "4                     4    18      +18.835       0  \n",
       "5                     2    18      +20.011       0  \n",
       "6                     8    18      +23.442       0  \n",
       "7                     7    18      +27.952       0  \n",
       "8                    10    18      +31.089       0  \n",
       "9                     9    18      +31.680       0  \n",
       "10                   12    18      +38.671       0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sprintQualiResults[sprintQualiResults['Track'] == 'Italy'].set_index('Position').head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9072a0ed",
   "metadata": {},
   "source": [
    "### Brazil"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "74dcf277",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Brazil</td>\n",
       "      <td>77</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>2</td>\n",
       "      <td>24</td>\n",
       "      <td>29:09.559</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>+1.170</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>55</td>\n",
       "      <td>Carlos Sainz</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>5</td>\n",
       "      <td>24</td>\n",
       "      <td>+18.723</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>11</td>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>3</td>\n",
       "      <td>24</td>\n",
       "      <td>+19.787</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>20</td>\n",
       "      <td>24</td>\n",
       "      <td>+20.872</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>4</td>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>7</td>\n",
       "      <td>24</td>\n",
       "      <td>+22.858</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>16</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>6</td>\n",
       "      <td>24</td>\n",
       "      <td>+25.056</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>10</td>\n",
       "      <td>Pierre Gasly</td>\n",
       "      <td>AlphaTauri Honda</td>\n",
       "      <td>4</td>\n",
       "      <td>24</td>\n",
       "      <td>+34.158</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>31</td>\n",
       "      <td>Esteban Ocon</td>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>10</td>\n",
       "      <td>24</td>\n",
       "      <td>+34.632</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>5</td>\n",
       "      <td>Sebastian Vettel</td>\n",
       "      <td>Aston Martin Mercedes</td>\n",
       "      <td>11</td>\n",
       "      <td>24</td>\n",
       "      <td>+34.867</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Track  No            Driver                   Team  Starting Grid  \\\n",
       "Position                                                                       \n",
       "1         Brazil  77   Valtteri Bottas               Mercedes              2   \n",
       "2         Brazil  33    Max Verstappen  Red Bull Racing Honda              1   \n",
       "3         Brazil  55      Carlos Sainz                Ferrari              5   \n",
       "4         Brazil  11      Sergio Perez  Red Bull Racing Honda              3   \n",
       "5         Brazil  44    Lewis Hamilton               Mercedes             20   \n",
       "6         Brazil   4      Lando Norris       McLaren Mercedes              7   \n",
       "7         Brazil  16   Charles Leclerc                Ferrari              6   \n",
       "8         Brazil  10      Pierre Gasly       AlphaTauri Honda              4   \n",
       "9         Brazil  31      Esteban Ocon         Alpine Renault             10   \n",
       "10        Brazil   5  Sebastian Vettel  Aston Martin Mercedes             11   \n",
       "\n",
       "          Laps Time/Retired  Points  \n",
       "Position                             \n",
       "1           24    29:09.559       3  \n",
       "2           24       +1.170       2  \n",
       "3           24      +18.723       1  \n",
       "4           24      +19.787       0  \n",
       "5           24      +20.872       0  \n",
       "6           24      +22.858       0  \n",
       "7           24      +25.056       0  \n",
       "8           24      +34.158       0  \n",
       "9           24      +34.632       0  \n",
       "10          24      +34.867       0  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sprintQualiResults[sprintQualiResults['Track'] == 'Brazil'].set_index('Position').head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67176e2c",
   "metadata": {},
   "source": [
    "According to the results of Sprint Qualifying sessions above, **Valtteri Bottas** finished 1st twice, and **Max Verstappen**, once.\n",
    "\n",
    "Of course, we can definitely state that several drivers succedded to **gain some positions**, also the others lost a few. Thus, it seems this format is operating well enough for mixing the grid for the next day.\n",
    "\n",
    "Perhaps, the moment which attracted the most attention was from **Lewis Hamilton** in Brazil, where the Mercedes driver started the sprint from last **(P20)** and quickly climbed up the positions in the 24-lap race and consequently, he finished **5th**! Showing this performance was very important for Hamilton in order to keep the competition for championship title alive against Verstappen, but after the sprint, it was ended with **5-place grid penalty** for the main race by the use of additional power unit element."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02a94c51",
   "metadata": {},
   "source": [
    "### Total Points Earned in Sprint Qualifying"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a6be80c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sprintQualiDriver = sprintQualiResults.groupby(['Driver', 'Team'])['Points'].sum().sort_values(ascending=False)\n",
    "sprintQualiDriver = sprintQualiDriver[sprintQualiDriver > 0].reset_index()\n",
    "sprintQualiDriver.index = [i for i in range(1,6)]\n",
    "c = assign_color(\"drivers\", sprintQualiDriver['Driver'])\n",
    "surnames = [driver.split()[1] for driver in sprintQualiDriver['Driver']]\n",
    "plt.figure(figsize=(14,6))\n",
    "plt.axis([0,7.2,4.7,-0.7])\n",
    "plt.barh(surnames, sprintQualiDriver['Points'], color=c)\n",
    "for i in range(1,len(sprintQualiDriver)+1):\n",
    "    plt.text(sprintQualiDriver['Points'][i]-0.2, i-0.88, sprintQualiDriver['Points'][i], fontsize=24, color='k')\n",
    "plt.title(\"Formula 1 - 2021 Season\\nPoints Earned by Drivers in Sprint Qualifying\", \n",
    "          fontsize=22, fontweight='bold', color='#bbbbbb')\n",
    "plt.xlabel('POINTS', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.xticks(fontsize=14, color='#ffff55')\n",
    "plt.ylabel('DRIVERS', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.yticks(fontsize=15, color='#ffff55')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c5358b4",
   "metadata": {},
   "source": [
    "From the visualization above, **only 5 drivers** benefited from Sprint Qualifying sessions. **Bottas** and **Verstappen** earned equally **7 points** and Hamilton was able to obtain only 2 points (came from Great Britain GP). Ricciardo and Sainz were the other drivers with points, but limited to 1 single point to contribute to their standings."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59cd43c9",
   "metadata": {},
   "source": [
    "## Race Winners\n",
    "\n",
    "Here comes the winners of all races of the 2021 Season calendar!\n",
    "\n",
    "Please take your time to inspect the table below as well as the other beneficial information..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "d3e83914",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>No</th>\n",
       "      <th>Driver</th>\n",
       "      <th>Team</th>\n",
       "      <th>Starting Grid</th>\n",
       "      <th>Laps</th>\n",
       "      <th>Time/Retired</th>\n",
       "      <th>Points</th>\n",
       "      <th>+1 Pt</th>\n",
       "      <th>Fastest Lap</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Track</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Bahrain</th>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>2</td>\n",
       "      <td>56</td>\n",
       "      <td>1:32:03.897</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:34.015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Emilia Romagna</th>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>2</td>\n",
       "      <td>63</td>\n",
       "      <td>2:02:34.598</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:17.524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portugal</th>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>2</td>\n",
       "      <td>66</td>\n",
       "      <td>1:34:31.421</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:20.933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spain</th>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>1</td>\n",
       "      <td>66</td>\n",
       "      <td>1:33:07.680</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:20.665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Monaco</th>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>2</td>\n",
       "      <td>78</td>\n",
       "      <td>1:38:56.820</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:14.649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Azerbaijan</th>\n",
       "      <td>11</td>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>6</td>\n",
       "      <td>51</td>\n",
       "      <td>2:13:36.410</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:44.687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>1</td>\n",
       "      <td>53</td>\n",
       "      <td>1:27:25.770</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:36.404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Styria</th>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>1</td>\n",
       "      <td>71</td>\n",
       "      <td>1:22:18.925</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:08.017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Austria</th>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>1</td>\n",
       "      <td>71</td>\n",
       "      <td>1:23:54.543</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:06.200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Great Britain</th>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>2</td>\n",
       "      <td>52</td>\n",
       "      <td>1:58:23.284</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:29.699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hungary</th>\n",
       "      <td>31</td>\n",
       "      <td>Esteban Ocon</td>\n",
       "      <td>Alpine Renault</td>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>2:04:43.199</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:21.421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Belgium</th>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0:03:27.071</td>\n",
       "      <td>12.5</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Netherlands</th>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>1</td>\n",
       "      <td>72</td>\n",
       "      <td>1:30:05.395</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:13.275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>3</td>\n",
       "      <td>Daniel Ricciardo</td>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>2</td>\n",
       "      <td>53</td>\n",
       "      <td>1:21:54.365</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:24.812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Russia</th>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>4</td>\n",
       "      <td>53</td>\n",
       "      <td>1:30:41.001</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:37.575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>77</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>1</td>\n",
       "      <td>58</td>\n",
       "      <td>1:31:04.103</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:30.432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United States</th>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>1</td>\n",
       "      <td>56</td>\n",
       "      <td>1:34:36.552</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:39.096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>3</td>\n",
       "      <td>71</td>\n",
       "      <td>1:38:39.086</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:18.999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>10</td>\n",
       "      <td>71</td>\n",
       "      <td>1:32:22.851</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:11.982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Qatar</th>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>1</td>\n",
       "      <td>57</td>\n",
       "      <td>1:24:28.471</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:25.084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>2:06:15.118</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:30.734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Abu Dhabi</th>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>1</td>\n",
       "      <td>58</td>\n",
       "      <td>1:30:17.345</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:26.103</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                No            Driver                   Team  Starting Grid  \\\n",
       "Track                                                                        \n",
       "Bahrain         44    Lewis Hamilton               Mercedes              2   \n",
       "Emilia Romagna  33    Max Verstappen  Red Bull Racing Honda              2   \n",
       "Portugal        44    Lewis Hamilton               Mercedes              2   \n",
       "Spain           44    Lewis Hamilton               Mercedes              1   \n",
       "Monaco          33    Max Verstappen  Red Bull Racing Honda              2   \n",
       "Azerbaijan      11      Sergio Perez  Red Bull Racing Honda              6   \n",
       "France          33    Max Verstappen  Red Bull Racing Honda              1   \n",
       "Styria          33    Max Verstappen  Red Bull Racing Honda              1   \n",
       "Austria         33    Max Verstappen  Red Bull Racing Honda              1   \n",
       "Great Britain   44    Lewis Hamilton               Mercedes              2   \n",
       "Hungary         31      Esteban Ocon         Alpine Renault              8   \n",
       "Belgium         33    Max Verstappen  Red Bull Racing Honda              1   \n",
       "Netherlands     33    Max Verstappen  Red Bull Racing Honda              1   \n",
       "Italy            3  Daniel Ricciardo       McLaren Mercedes              2   \n",
       "Russia          44    Lewis Hamilton               Mercedes              4   \n",
       "Turkey          77   Valtteri Bottas               Mercedes              1   \n",
       "United States   33    Max Verstappen  Red Bull Racing Honda              1   \n",
       "Mexico          33    Max Verstappen  Red Bull Racing Honda              3   \n",
       "Brazil          44    Lewis Hamilton               Mercedes             10   \n",
       "Qatar           44    Lewis Hamilton               Mercedes              1   \n",
       "Saudi Arabia    44    Lewis Hamilton               Mercedes              1   \n",
       "Abu Dhabi       33    Max Verstappen  Red Bull Racing Honda              1   \n",
       "\n",
       "                Laps Time/Retired  Points +1 Pt Fastest Lap  \n",
       "Track                                                        \n",
       "Bahrain           56  1:32:03.897    25.0    No    1:34.015  \n",
       "Emilia Romagna    63  2:02:34.598    25.0    No    1:17.524  \n",
       "Portugal          66  1:34:31.421    25.0    No    1:20.933  \n",
       "Spain             66  1:33:07.680    25.0    No    1:20.665  \n",
       "Monaco            78  1:38:56.820    25.0    No    1:14.649  \n",
       "Azerbaijan        51  2:13:36.410    25.0    No    1:44.687  \n",
       "France            53  1:27:25.770    26.0   Yes    1:36.404  \n",
       "Styria            71  1:22:18.925    25.0    No    1:08.017  \n",
       "Austria           71  1:23:54.543    26.0   Yes    1:06.200  \n",
       "Great Britain     52  1:58:23.284    25.0    No    1:29.699  \n",
       "Hungary           70  2:04:43.199    25.0    No    1:21.421  \n",
       "Belgium            1  0:03:27.071    12.5    No         NaN  \n",
       "Netherlands       72  1:30:05.395    25.0    No    1:13.275  \n",
       "Italy             53  1:21:54.365    26.0   Yes    1:24.812  \n",
       "Russia            53  1:30:41.001    25.0    No    1:37.575  \n",
       "Turkey            58  1:31:04.103    26.0   Yes    1:30.432  \n",
       "United States     56  1:34:36.552    25.0    No    1:39.096  \n",
       "Mexico            71  1:38:39.086    25.0    No    1:18.999  \n",
       "Brazil            71  1:32:22.851    25.0    No    1:11.982  \n",
       "Qatar             57  1:24:28.471    25.0    No    1:25.084  \n",
       "Saudi Arabia      50  2:06:15.118    26.0   Yes    1:30.734  \n",
       "Abu Dhabi         58  1:30:17.345    26.0   Yes    1:26.103  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raceWinners = raceResults[raceResults['Position'] == '1'].set_index('Track').drop('Position', axis=1)\n",
    "raceWinners"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "184aba0f",
   "metadata": {},
   "source": [
    "Here, we can say that most of these races this season have been won by **starting at the front row**.\n",
    "\n",
    "On the other hand, there were other races where the driver began the races far from the front row and achieved to claim the race wins! The most remarkable ones were **Ocon** in Hungary GP, where the Frenchman started P8; and **Hamilton** in Brazil GP, where he started the race in 10th place.\n",
    "\n",
    "To better illustrate this, let's make **a bar chart to count the race wins by drivers** in 2021 Season:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "daed7d39",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "raceWinnersCnt = raceWinners['Driver'].value_counts()\n",
    "c = assign_color(\"drivers\", raceWinnersCnt.index)\n",
    "surnames = [driver.split()[1] for driver in raceWinnersCnt.index]\n",
    "plt.figure(figsize=(14,6))\n",
    "plt.axis([0,10.2,5.65,-0.65])\n",
    "plt.barh(surnames, raceWinnersCnt.values, color=c)\n",
    "for i in range(len(raceWinnersCnt)):\n",
    "    plt.text(raceWinnersCnt.values[i]-0.5, i+0.15, \"{:3}\".format(raceWinnersCnt.values[i]), fontsize=24, color='k')\n",
    "plt.title(\"Formula 1 - 2021 Season\\nDrivers' Race Win Counts\", fontsize=22, fontweight='bold', color='#bbbbbb')\n",
    "plt.xlabel('RACE WINS', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.xticks(fontsize=14, color='#ffff55')\n",
    "plt.ylabel('DRIVERS', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.yticks(fontsize=15, color='#ffff55')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af6b9ab7",
   "metadata": {},
   "source": [
    "So, in all these 22-race long season, there were total of **6 drivers** who saw the chequered flag in the 1st place! It is clear to state that the two closest rivals **Verstappen** and **Hamilton** occupied the first two places in the chart above, with the numbers **10** and **8**, respectively.\n",
    "\n",
    "The rest, **Ocon**, **Perez**, **Bottas** and **Ricciardo** also have won races **once** this season.\n",
    "\n",
    "Remember that **Hungarian GP** was Ocon's first grand prix win he had in his career. Likewise, Perez achieved to score his **second F1 win** in Azerbaijan after incidents in the last few laps.\n",
    "\n",
    "For Bottas, his win only came from Turkey, and **stayed significantly behind** Hamilton in terms of race win counts. Well, on the positive side, he did not finish the season without a win, though.\n",
    "\n",
    "Last but not least, Ricciardo enjoyed the victory in Italy (Monza) and this was **his first in McLaren team** if we consider his wins he had from Red Bull Racing."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1db264cf",
   "metadata": {},
   "source": [
    "## Pole Positions\n",
    "\n",
    "Qualifying session on Saturday (for some race weekends, with Sprint Qualifying) is **crucial** for drivers and teams to show what they've got to be the fastest and take **the pole position**, thus earning the advantage to start the race ahead of all rivals!\n",
    "\n",
    "The table below shows us the polesitters of all races this season, and, in the meantime, the focus point is **how these drivers finished their races** after starting from pole:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "30c42a9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Position</th>\n",
       "      <th>No</th>\n",
       "      <th>Driver</th>\n",
       "      <th>Team</th>\n",
       "      <th>Laps</th>\n",
       "      <th>Time/Retired</th>\n",
       "      <th>Points</th>\n",
       "      <th>+1 Pt</th>\n",
       "      <th>Fastest Lap</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Track</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Bahrain</th>\n",
       "      <td>2</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>56</td>\n",
       "      <td>+0.745</td>\n",
       "      <td>18.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:33.228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Emilia Romagna</th>\n",
       "      <td>2</td>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>63</td>\n",
       "      <td>+22.000</td>\n",
       "      <td>19.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:16.702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portugal</th>\n",
       "      <td>3</td>\n",
       "      <td>77</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>66</td>\n",
       "      <td>+33.530</td>\n",
       "      <td>16.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:19.865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spain</th>\n",
       "      <td>1</td>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>66</td>\n",
       "      <td>1:33:07.680</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:20.665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Monaco</th>\n",
       "      <td>NC</td>\n",
       "      <td>16</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>0</td>\n",
       "      <td>DNS</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Azerbaijan</th>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>51</td>\n",
       "      <td>+3.828</td>\n",
       "      <td>12.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:45.382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>53</td>\n",
       "      <td>1:27:25.770</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:36.404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Styria</th>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>71</td>\n",
       "      <td>1:22:18.925</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:08.017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Austria</th>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>71</td>\n",
       "      <td>1:23:54.543</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:06.200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Great Britain</th>\n",
       "      <td>NC</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>0</td>\n",
       "      <td>DNF</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hungary</th>\n",
       "      <td>2</td>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>70</td>\n",
       "      <td>+2.736</td>\n",
       "      <td>18.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:18.715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Belgium</th>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>1</td>\n",
       "      <td>0:03:27.071</td>\n",
       "      <td>12.5</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Netherlands</th>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>72</td>\n",
       "      <td>1:30:05.395</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:13.275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>NC</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>25</td>\n",
       "      <td>DNF</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:25.173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Russia</th>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>53</td>\n",
       "      <td>+87.224</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:37.423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>1</td>\n",
       "      <td>77</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>58</td>\n",
       "      <td>1:31:04.103</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:30.432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United States</th>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>56</td>\n",
       "      <td>1:34:36.552</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:39.096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>15</td>\n",
       "      <td>77</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>69</td>\n",
       "      <td>+2 laps</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:17.774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>3</td>\n",
       "      <td>77</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>71</td>\n",
       "      <td>+13.576</td>\n",
       "      <td>15.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:12.526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Qatar</th>\n",
       "      <td>1</td>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>57</td>\n",
       "      <td>1:24:28.471</td>\n",
       "      <td>25.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:25.084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>1</td>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>50</td>\n",
       "      <td>2:06:15.118</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:30.734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Abu Dhabi</th>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>58</td>\n",
       "      <td>1:30:17.345</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1:26.103</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Position  No           Driver                   Team  Laps  \\\n",
       "Track                                                                       \n",
       "Bahrain               2  33   Max Verstappen  Red Bull Racing Honda    56   \n",
       "Emilia Romagna        2  44   Lewis Hamilton               Mercedes    63   \n",
       "Portugal              3  77  Valtteri Bottas               Mercedes    66   \n",
       "Spain                 1  44   Lewis Hamilton               Mercedes    66   \n",
       "Monaco               NC  16  Charles Leclerc                Ferrari     0   \n",
       "Azerbaijan            4  16  Charles Leclerc                Ferrari    51   \n",
       "France                1  33   Max Verstappen  Red Bull Racing Honda    53   \n",
       "Styria                1  33   Max Verstappen  Red Bull Racing Honda    71   \n",
       "Austria               1  33   Max Verstappen  Red Bull Racing Honda    71   \n",
       "Great Britain        NC  33   Max Verstappen  Red Bull Racing Honda     0   \n",
       "Hungary               2  44   Lewis Hamilton               Mercedes    70   \n",
       "Belgium               1  33   Max Verstappen  Red Bull Racing Honda     1   \n",
       "Netherlands           1  33   Max Verstappen  Red Bull Racing Honda    72   \n",
       "Italy                NC  33   Max Verstappen  Red Bull Racing Honda    25   \n",
       "Russia                7   4     Lando Norris       McLaren Mercedes    53   \n",
       "Turkey                1  77  Valtteri Bottas               Mercedes    58   \n",
       "United States         1  33   Max Verstappen  Red Bull Racing Honda    56   \n",
       "Mexico               15  77  Valtteri Bottas               Mercedes    69   \n",
       "Brazil                3  77  Valtteri Bottas               Mercedes    71   \n",
       "Qatar                 1  44   Lewis Hamilton               Mercedes    57   \n",
       "Saudi Arabia          1  44   Lewis Hamilton               Mercedes    50   \n",
       "Abu Dhabi             1  33   Max Verstappen  Red Bull Racing Honda    58   \n",
       "\n",
       "               Time/Retired  Points +1 Pt Fastest Lap  \n",
       "Track                                                  \n",
       "Bahrain              +0.745    18.0    No    1:33.228  \n",
       "Emilia Romagna      +22.000    19.0   Yes    1:16.702  \n",
       "Portugal            +33.530    16.0   Yes    1:19.865  \n",
       "Spain           1:33:07.680    25.0    No    1:20.665  \n",
       "Monaco                  DNS     0.0    No         NaN  \n",
       "Azerbaijan           +3.828    12.0    No    1:45.382  \n",
       "France          1:27:25.770    26.0   Yes    1:36.404  \n",
       "Styria          1:22:18.925    25.0    No    1:08.017  \n",
       "Austria         1:23:54.543    26.0   Yes    1:06.200  \n",
       "Great Britain           DNF     0.0    No         NaN  \n",
       "Hungary              +2.736    18.0    No    1:18.715  \n",
       "Belgium         0:03:27.071    12.5    No         NaN  \n",
       "Netherlands     1:30:05.395    25.0    No    1:13.275  \n",
       "Italy                   DNF     0.0    No    1:25.173  \n",
       "Russia              +87.224     7.0   Yes    1:37.423  \n",
       "Turkey          1:31:04.103    26.0   Yes    1:30.432  \n",
       "United States   1:34:36.552    25.0    No    1:39.096  \n",
       "Mexico              +2 laps     0.0    No    1:17.774  \n",
       "Brazil              +13.576    15.0    No    1:12.526  \n",
       "Qatar           1:24:28.471    25.0    No    1:25.084  \n",
       "Saudi Arabia    2:06:15.118    26.0   Yes    1:30.734  \n",
       "Abu Dhabi       1:30:17.345    26.0   Yes    1:26.103  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "polePos = raceResults[raceResults['Starting Grid'] == 1].set_index('Track').drop('Starting Grid', axis=1)\n",
    "polePos"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7a3fabe",
   "metadata": {},
   "source": [
    "**From this table, we can take these outcomes:**\n",
    "* In **11** different tracks, the driver, who started from the pole position, won the race. Among those, **Max Verstappen** accomplished it a total of **7 times**. His close rival, **Lewis Hamilton** did this **3 times**. The remaining one came from **Bottas** (in Turkey).\n",
    "* In **3** different tracks, the polesitters failed to finish the races, especially the one where **Leclerc** could not participate in the grid, in his home race, **Monaco**! The other two came from **Verstappen**; in **Great Britain GP**, he clashed with **Hamilton** in the first lap and hit the barriers with very high G-force; and in **Italy** (as mentioned above), he again made contact the Briton, ending in DNF for both drivers.\n",
    "* The drivers starting at 1st position also set the fastest lap time, in **8** different tracks. Among **the five of them**, this was clinched with race wins, where we can see Verstappen's name in those **three** times.\n",
    "\n",
    "Together with that, the visualization below will help us count the total pole positions obtained by drivers in 2021:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "e8914a8d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "polePosCnt = polePos['Driver'].value_counts()\n",
    "c = assign_color(\"drivers\", polePosCnt.index)\n",
    "plt.figure(figsize=(14,6))\n",
    "plt.axis([0,10.2,4.65,-0.65])\n",
    "plt.barh([driver.split()[1] for driver in polePosCnt.index], polePosCnt.values, color=c)\n",
    "for i in range(len(polePosCnt)):\n",
    "    plt.text(polePosCnt.values[i]-0.42, i+0.15, \"{:2}\".format(polePosCnt.values[i]), fontsize=24, color='k')\n",
    "plt.title(\"Formula 1 - 2021 Season\\nDrivers' Pole Position Counts\", fontsize=22, fontweight='bold', color='#bbbbbb')\n",
    "plt.xlabel('POLE POSITIONS', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.xticks(fontsize=14, color='#ffff55')\n",
    "plt.ylabel('DRIVERS', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.yticks(fontsize=15, color='#ffff55')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e45914ea",
   "metadata": {},
   "source": [
    "Here, this season's champion Verstappen took the pole position **10 times**, which was **more than twice the amount** of Mercedes drivers!\n",
    "\n",
    "Leclerc (2) and Norris (1) were the other drivers who were not from Red Bull and Mercedes, to earn the right of starting 1st in the race sessions.\n",
    "\n",
    "Note that for this season, we could not see Leclerc to start in Monaco, as explained above! Additionally, in Russia, Norris achieved to start **on pole for the first time in his career**!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c694f4f6",
   "metadata": {},
   "source": [
    "## Podium Finishes\n",
    "\n",
    "Besides winning races, finishing in top 3 places and **stepping on the podium** after the race is a great glory for drivers and making their team proud! Its value is immensely high if the driver did not achieve that before or had only a few in his long-lasting career.\n",
    "\n",
    "Let's see the drivers who successfully were on the podium and count the number of trophies they earned, in 2021 Season:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5a420182",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "podiumFinish = raceResults[raceResults['Position'].isin(['1','2','3'])].set_index('Track').drop('Position', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "128b4be4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "podiumCnt = podiumFinish['Driver'].value_counts()\n",
    "c = assign_color(\"drivers\", podiumCnt.index)\n",
    "plt.figure(figsize=(14,7))\n",
    "plt.axis([0,18.2,12.65,-0.65])\n",
    "plt.barh([driver.split()[1] for driver in podiumCnt.index], podiumCnt.values, color=c)\n",
    "for i in range(len(podiumCnt)):\n",
    "    plt.text(podiumCnt.values[i]-0.6, i+0.25, \"{:2}\".format(podiumCnt.values[i]), fontsize=18, color='k')\n",
    "plt.title(\"Formula 1 - 2021 Season\\nDrivers' Podium Counts\", fontsize=22, fontweight='bold', color='#bbbbbb')\n",
    "plt.xlabel('PODIUMS', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.xticks(range(0,20,3), fontsize=14, color='#ffff55')\n",
    "plt.ylabel('DRIVERS', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.yticks(fontsize=15, color='#ffff55')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b29aea37",
   "metadata": {},
   "source": [
    "Well, it is certain that **Verstappen** and **Hamilton** dominated the count of podium finishes this season, with **18** and **17**, respectively! Their teammates **Bottas** and **Perez** came after them with numbers **11** and **5**.\n",
    "\n",
    "**Norris** and **Sainz** were the other drivers (4) who successfully scored **more than one podium finishes** in 2021.\n",
    "\n",
    "Moreover, **Gasly**, **Ricciardo**, **Ocon**, **Leclerc**, **Russell**, **Alonso** and **Vettel** were the remaining drivers joining the podium ceremony **once** this season.\n",
    "\n",
    "All in all, 2021 Season has seen **13 different drivers** stepping on the podium in all races!\n",
    "\n",
    "Also note that, it was **George Russell**'s first podium he achieved in his F1 career (which occurred in Belgium, mentioned above). Plus, it was great to see the two-times world champion **Fernando Alonso** back on the podium in **Qatar** (his 98th in total)!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6428683a",
   "metadata": {},
   "source": [
    "## Top 10 Finishes\n",
    "\n",
    "Now, let's take a much broader angle by counting **the top 10 finishes** by all drivers throughout the season (i.e. how many times each driver **scored points** in all races):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "a9e34999",
   "metadata": {},
   "outputs": [],
   "source": [
    "topTen = [str(i) for i in range(1,11)]\n",
    "topTenFinish = raceResults[raceResults['Position'].isin(topTen)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "6a6ad6cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x540 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "topTenFinishCnt = topTenFinish['Driver'].value_counts()\n",
    "c = assign_color(\"drivers\", topTenFinishCnt.index)\n",
    "plt.figure(figsize=(14,7.5))\n",
    "plt.axis([0,20.5,17.65,-0.65])\n",
    "plt.barh([driver.split()[1] for driver in topTenFinishCnt.index], topTenFinishCnt.values, color=c)\n",
    "for i in range(len(topTenFinishCnt)):\n",
    "    plt.text(topTenFinishCnt.values[i]-0.57, i+0.26, \"{:2}\".format(topTenFinishCnt.values[i]), fontsize=16, color='k')\n",
    "plt.title(\"Formula 1 - 2021 Season\\nDrivers' Top 10 Finish Counts\", fontsize=22, fontweight='bold', color='#bbbbbb')\n",
    "plt.xlabel('TOP 10 FINISHES', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.xticks(range(0,20,3), fontsize=14, color='#ffff55')\n",
    "plt.ylabel('DRIVERS', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.yticks(fontsize=13, color='#ffff55')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ff13d9c",
   "metadata": {},
   "source": [
    "Whoa, **Hamilton**, **Norris** and **Sainz** together were the most point scorers in different tracks this season, with a total of **20**! **Verstappen** followed the trio with **19**. His teammate **Perez** finished in the top 10 by **16** times. And, **Leclerc** got sandwiched between the Red Bull drivers with **18**.\n",
    "\n",
    "Looking at the bottom, **Williams** and **Alfa Romeo** drivers had the least top 10 finishes with mutually **4** and **2** times.\n",
    "\n",
    "What about **Haas** drivers? Well, with no doubt, we've never seen **Mick Schumacher** and **Nikita Mazepin** scoring points in the whole season; that's why, they are not shown in the chart above."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "08dbbbea",
   "metadata": {},
   "source": [
    "## +1 Point from Fastest Laps\n",
    "\n",
    "Since 2019 Season, any driver who set **the fastest lap time** in the race session is awarded with **1 additional point**. In many races, the importance of this point is high as the driver and his team attempts to steal it from their opponents by, for instance, **entering the pit and getting the soft tyres** if there is enough gap against the driver behind, then doing his best to be the fastest on the track! At the end, this might have a substantial effect on drivers' and constructors' standings.\n",
    "\n",
    "In the table below, you see the drivers who set the fastest laps in different tracks of 2021 Season and claimed the +1 point. However, some tracks are not listed because in order to get the point, the driver must also **finish in the top 10**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "4f2425c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Position</th>\n",
       "      <th>No</th>\n",
       "      <th>Driver</th>\n",
       "      <th>Team</th>\n",
       "      <th>Starting Grid</th>\n",
       "      <th>Laps</th>\n",
       "      <th>Time/Retired</th>\n",
       "      <th>Points</th>\n",
       "      <th>Fastest Lap</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Track</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Bahrain</th>\n",
       "      <td>3</td>\n",
       "      <td>77</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>3</td>\n",
       "      <td>56</td>\n",
       "      <td>+37.383</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1:32.090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Emilia Romagna</th>\n",
       "      <td>2</td>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>1</td>\n",
       "      <td>63</td>\n",
       "      <td>+22.000</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1:16.702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portugal</th>\n",
       "      <td>3</td>\n",
       "      <td>77</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>1</td>\n",
       "      <td>66</td>\n",
       "      <td>+33.530</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1:19.865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spain</th>\n",
       "      <td>2</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>2</td>\n",
       "      <td>66</td>\n",
       "      <td>+15.841</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1:18.149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Monaco</th>\n",
       "      <td>7</td>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>7</td>\n",
       "      <td>78</td>\n",
       "      <td>+68.231</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1:12.909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>1</td>\n",
       "      <td>53</td>\n",
       "      <td>1:27:25.770</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1:36.404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Styria</th>\n",
       "      <td>2</td>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>2</td>\n",
       "      <td>71</td>\n",
       "      <td>+35.743</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1:07.058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Austria</th>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>1</td>\n",
       "      <td>71</td>\n",
       "      <td>1:23:54.543</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1:06.200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hungary</th>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>Pierre Gasly</td>\n",
       "      <td>AlphaTauri Honda</td>\n",
       "      <td>5</td>\n",
       "      <td>70</td>\n",
       "      <td>+63.614</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1:18.394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Netherlands</th>\n",
       "      <td>2</td>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>2</td>\n",
       "      <td>72</td>\n",
       "      <td>+20.932</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1:11.097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Daniel Ricciardo</td>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>2</td>\n",
       "      <td>53</td>\n",
       "      <td>1:21:54.365</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1:24.812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Russia</th>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>McLaren Mercedes</td>\n",
       "      <td>1</td>\n",
       "      <td>53</td>\n",
       "      <td>+87.224</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1:37.423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>1</td>\n",
       "      <td>77</td>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>1</td>\n",
       "      <td>58</td>\n",
       "      <td>1:31:04.103</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1:30.432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United States</th>\n",
       "      <td>2</td>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>2</td>\n",
       "      <td>56</td>\n",
       "      <td>+1.333</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1:38.485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>4</td>\n",
       "      <td>71</td>\n",
       "      <td>+39.940</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1:11.010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Qatar</th>\n",
       "      <td>2</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>7</td>\n",
       "      <td>57</td>\n",
       "      <td>+25.743</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1:23.196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>1</td>\n",
       "      <td>44</td>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>Mercedes</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>2:06:15.118</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1:30.734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Abu Dhabi</th>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>1</td>\n",
       "      <td>58</td>\n",
       "      <td>1:30:17.345</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1:26.103</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Position  No            Driver                   Team  \\\n",
       "Track                                                                  \n",
       "Bahrain               3  77   Valtteri Bottas               Mercedes   \n",
       "Emilia Romagna        2  44    Lewis Hamilton               Mercedes   \n",
       "Portugal              3  77   Valtteri Bottas               Mercedes   \n",
       "Spain                 2  33    Max Verstappen  Red Bull Racing Honda   \n",
       "Monaco                7  44    Lewis Hamilton               Mercedes   \n",
       "France                1  33    Max Verstappen  Red Bull Racing Honda   \n",
       "Styria                2  44    Lewis Hamilton               Mercedes   \n",
       "Austria               1  33    Max Verstappen  Red Bull Racing Honda   \n",
       "Hungary               5  10      Pierre Gasly       AlphaTauri Honda   \n",
       "Netherlands           2  44    Lewis Hamilton               Mercedes   \n",
       "Italy                 1   3  Daniel Ricciardo       McLaren Mercedes   \n",
       "Russia                7   4      Lando Norris       McLaren Mercedes   \n",
       "Turkey                1  77   Valtteri Bottas               Mercedes   \n",
       "United States         2  44    Lewis Hamilton               Mercedes   \n",
       "Brazil                4  11      Sergio Perez  Red Bull Racing Honda   \n",
       "Qatar                 2  33    Max Verstappen  Red Bull Racing Honda   \n",
       "Saudi Arabia          1  44    Lewis Hamilton               Mercedes   \n",
       "Abu Dhabi             1  33    Max Verstappen  Red Bull Racing Honda   \n",
       "\n",
       "                Starting Grid  Laps Time/Retired  Points Fastest Lap  \n",
       "Track                                                                 \n",
       "Bahrain                     3    56      +37.383    16.0    1:32.090  \n",
       "Emilia Romagna              1    63      +22.000    19.0    1:16.702  \n",
       "Portugal                    1    66      +33.530    16.0    1:19.865  \n",
       "Spain                       2    66      +15.841    19.0    1:18.149  \n",
       "Monaco                      7    78      +68.231     7.0    1:12.909  \n",
       "France                      1    53  1:27:25.770    26.0    1:36.404  \n",
       "Styria                      2    71      +35.743    19.0    1:07.058  \n",
       "Austria                     1    71  1:23:54.543    26.0    1:06.200  \n",
       "Hungary                     5    70      +63.614    11.0    1:18.394  \n",
       "Netherlands                 2    72      +20.932    19.0    1:11.097  \n",
       "Italy                       2    53  1:21:54.365    26.0    1:24.812  \n",
       "Russia                      1    53      +87.224     7.0    1:37.423  \n",
       "Turkey                      1    58  1:31:04.103    26.0    1:30.432  \n",
       "United States               2    56       +1.333    19.0    1:38.485  \n",
       "Brazil                      4    71      +39.940    13.0    1:11.010  \n",
       "Qatar                       7    57      +25.743    19.0    1:23.196  \n",
       "Saudi Arabia                1    50  2:06:15.118    26.0    1:30.734  \n",
       "Abu Dhabi                   1    58  1:30:17.345    26.0    1:26.103  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "onePtByFastestLaps = raceResults[raceResults['+1 Pt'] == 'Yes'].set_index('Track').drop('+1 Pt', axis=1)\n",
    "onePtByFastestLaps"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0749021",
   "metadata": {},
   "source": [
    "From this table, we can say that total of **18 points** were distributed to drivers by setting the fastest laps in different tracks. Furthermore, the locations with no +1 point given are **Azerbaijan**, **Great Britain**, **Belgium** and **Mexico**.\n",
    "\n",
    "Another knowledge we can have is that there are **5 tracks** where the driver started the race in pole position and won with the fastest lap time (that's 26 points maximum). **Verstappen** achieved this **three times** (in Spain, France and Abu Dhabi), whereas **Hamilton** and **Bottas** did this **once** (in Saudi Arabia and Turkey, respectively).\n",
    "\n",
    "**Ricciardo** is the only driver who won with the +1 point without starting from pole, occurred in Italy (Monza)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "890f4dc1",
   "metadata": {},
   "source": [
    "The visualization chart below will clearly state **the different drivers** setting the fastest lap this season, along with their counts:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "b124ae94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "onePtFLCnt = onePtByFastestLaps['Driver'].value_counts()\n",
    "c = assign_color(\"drivers\", onePtFLCnt.index)\n",
    "plt.figure(figsize=(14,6))\n",
    "plt.axis([0,6.3,6.65,-0.65])\n",
    "plt.barh([driver.split()[1] for driver in onePtFLCnt.index], onePtFLCnt.values, color=c)\n",
    "for i in range(len(onePtFLCnt)):\n",
    "    plt.text(onePtFLCnt.values[i]-0.2, i+0.15, \"{:2}\".format(onePtFLCnt.values[i]), fontsize=20, color='k')\n",
    "plt.title(\"Formula 1 - 2021 Season\\n+1 Points Earned from Fastest Laps for Drivers\", \n",
    "          fontsize=22, fontweight=\"bold\", color=\"#bbbbbb\")\n",
    "plt.xlabel('# OF FASTEST LAPS', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.xticks(fontsize=14, color='#ffff55')\n",
    "plt.ylabel('DRIVERS', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.yticks(fontsize=15, color='#ffff55')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d5a48db8",
   "metadata": {},
   "source": [
    "Here, **Hamilton** has claimed **6** additional points by setting the fastest laps in race sessions, and his biggest rival **Verstappen** got this a total of **5** this season. We can see the Briton's teammate **Bottas** is coming after them with **3**.\n",
    "\n",
    "In addition, **Ricciardo**, **Norris**, **Gasly** and **Perez** received these +1 points once this season and added \"the fastest driver\" achievements to their careers."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38f8dc19",
   "metadata": {},
   "source": [
    "## DNF Analyses\n",
    "\n",
    "Every F1 driver wants to see **the chequered flag** and finish the races after a long time of driving. However, since this is motorsport racing, anything unexpected could happen while racing such as **driver mistakes** (e.g. contact with rivals, spinning out, hitting the wall) or **mechanical issues** (e.g. engine failure, gearbox issue, oil leakage), resulting in DNF! The distressing thing is that it could badly affect both drivers' and constructors' standings through the season."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5db0fb60",
   "metadata": {},
   "source": [
    "### Drivers\n",
    "\n",
    "Here, traditionally, it is inevitable to see many drivers to not complete some races due to aforementioned reasons in 2021 Season. Let's take a look at the visualization below to observe **the counts of DNFs by drivers**:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "ef279a52",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x540 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dnfResultsDriver = raceResults[raceResults['Time/Retired'] == 'DNF']['Driver'].value_counts()\n",
    "c = assign_color(\"drivers\", dnfResultsDriver.index)\n",
    "plt.figure(figsize=(14,7.5))\n",
    "plt.axis([0,6.15,18.65,-0.65])\n",
    "plt.barh([driver.split()[1] for driver in dnfResultsDriver.index], dnfResultsDriver.values, color=c)\n",
    "for i in range(len(dnfResultsDriver)):\n",
    "    plt.text(dnfResultsDriver.values[i]-0.15, i+0.25, \"{:2}\".format(dnfResultsDriver.values[i]), fontsize=16, color='k')\n",
    "plt.title(\"Formula 1 - 2021 Season\\nDNFs by Drivers\", fontsize=22, fontweight='bold', color='#bbbbbb')\n",
    "plt.xlabel('# OF DNFs', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.xticks(fontsize=14, color='#ffff55')\n",
    "plt.ylabel('DRIVERS', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.yticks(fontsize=13, color='#ffff55')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90bfe355",
   "metadata": {},
   "source": [
    "We can imply that **George Russell** had the most DNFs among all drivers in the whole season, which is **6**. Then, **Mazepin** and **Latifi** come after the British driver, with **5** DNFs.\n",
    "\n",
    "After that, **Vettel**, **Gasly** and **Bottas** could not successfully see the finish line in **4** different races.\n",
    "\n",
    "Our 2021 Season champion **Verstappen** did not take the chequered flag in **3** races, which is the same as his teammate **Perez**. If you wonder which races the Dutchman did not finish, these are **Azerbaijan**, **Great Britain** and **Italy (Monza)**.\n",
    "\n",
    "His closest rival **Hamilton** experienced only a **single** DNF in 2021; that was from, as you expected, the collision he had with Verstappen in **Italy(Monza)**.\n",
    "\n",
    "Lastly, you notice that there is only one driver who did not show up in the bar chart above. Yep, this is **Carlos Sainz** from Ferrari, thus he is the only one completing all the races this season. What a great consistency!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "931b2651",
   "metadata": {},
   "source": [
    "### Teams\n",
    "\n",
    "Of course, if we calculate all the DNF counts with regards to **teams**, then we'll have the result below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7fe91e8d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dnfResultsTeam = raceResults[raceResults['Time/Retired'] == 'DNF']['Team'].value_counts()\n",
    "c = assign_color(\"teams\", dnfResultsTeam.index)\n",
    "plt.figure(figsize=(14,7))\n",
    "plt.axis([0,11.2,9.65,-0.65])\n",
    "plt.barh(dnfResultsTeam.index, dnfResultsTeam.values, color=c)\n",
    "for i in range(len(dnfResultsTeam)):\n",
    "    plt.text(dnfResultsTeam.values[i]-0.35, i+0.18, \"{:2}\".format(dnfResultsTeam.values[i]), fontsize=18, color='k')\n",
    "plt.title(\"Formula 1 - 2021 Season\\nDNFs by Teams\", fontsize=22, fontweight='bold', color='#bbbbbb')\n",
    "plt.xlabel('# OF DNFs', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.xticks(fontsize=14, color='#ffff55')\n",
    "plt.ylabel('TEAMS', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.yticks(fontsize=13, color='#ffff55')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07ca63ec",
   "metadata": {},
   "source": [
    "The graphic indicates that **Williams** had **11** DNFs in total, which is the highest among all the other teams!\n",
    "\n",
    "**Haas** took the second place with 8 DNFs, then **AlphaTauri** and **Aston Martin** shared the third place for not having their cars seen the finish line with a total of **7** DNFs.\n",
    "\n",
    "It may not be surprising that **Scuderia Ferrari** was the team with the least DNFs in the whole season, stayed at just **1 DNF**! As observed from the DNFs by drivers chart, **Charles Leclerc** got this DNF which occurred in **Hungarian Grand Prix**."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23aaf622",
   "metadata": {},
   "source": [
    "**There are other situations which are worthwhile to tell and should not be overlooked!...**\n",
    "\n",
    "The worst of all is probably **not even starting the race** before the start time officially comes! Here, the table below shows that **three drivers** experienced that in **three different tracks**.\n",
    "\n",
    "In this season, **Leclerc** did not start the race in **Monaco** (his home race actually, which was even more disappointing!) because of the gearbox issue found beforehand. That might have happened due to the crash he caused near the end of Q3 of qualifying session in that weekend and the damage was not fixed completely before the race.\n",
    "\n",
    "Next, **Tsunoda** seemed to have major mechanical issues on his car before the race start on Sunday in **Italy (Monza)**. \n",
    "\n",
    "And, in Abu Dhabi, **Mazepin** was forced to withdraw from the grid due to being tested positive for Covid-19, ending the season earlier!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "107ca6a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Track</th>\n",
       "      <th>Position</th>\n",
       "      <th>No</th>\n",
       "      <th>Driver</th>\n",
       "      <th>Team</th>\n",
       "      <th>Starting Grid</th>\n",
       "      <th>Laps</th>\n",
       "      <th>Time/Retired</th>\n",
       "      <th>Points</th>\n",
       "      <th>+1 Pt</th>\n",
       "      <th>Fastest Lap</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>Monaco</td>\n",
       "      <td>NC</td>\n",
       "      <td>16</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>DNS</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>279</th>\n",
       "      <td>Italy</td>\n",
       "      <td>NC</td>\n",
       "      <td>22</td>\n",
       "      <td>Yuki Tsunoda</td>\n",
       "      <td>AlphaTauri Honda</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>DNS</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>NC</td>\n",
       "      <td>9</td>\n",
       "      <td>Nikita Mazepin</td>\n",
       "      <td>Haas Ferrari</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>DNS</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Track Position  No           Driver              Team  Starting Grid  \\\n",
       "99      Monaco       NC  16  Charles Leclerc           Ferrari              1   \n",
       "279      Italy       NC  22     Yuki Tsunoda  AlphaTauri Honda             15   \n",
       "439  Abu Dhabi       NC   9   Nikita Mazepin      Haas Ferrari             20   \n",
       "\n",
       "     Laps Time/Retired  Points +1 Pt Fastest Lap  \n",
       "99      0          DNS     0.0    No         NaN  \n",
       "279     0          DNS     0.0    No         NaN  \n",
       "439     0          DNS     0.0    No         NaN  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raceResults[raceResults['Time/Retired'] == 'DNS']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c88dfd6",
   "metadata": {},
   "source": [
    "**Here comes another one:** Any driver who did not finish a race can be still be classified in the results of the related race, provided that the driver has completed **more than 90%** of the race distance.\n",
    "\n",
    "In the table below, we have **9 different driver and track combinations** for the situation here. If we take them individually, that's 7 different tracks and 6 different drivers..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "7659aedd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Track</th>\n",
       "      <th>Position</th>\n",
       "      <th>No</th>\n",
       "      <th>Driver</th>\n",
       "      <th>Team</th>\n",
       "      <th>Starting Grid</th>\n",
       "      <th>Laps</th>\n",
       "      <th>Time/Retired</th>\n",
       "      <th>Points</th>\n",
       "      <th>+1 Pt</th>\n",
       "      <th>Fastest Lap</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Bahrain</td>\n",
       "      <td>17</td>\n",
       "      <td>10</td>\n",
       "      <td>Pierre Gasly</td>\n",
       "      <td>AlphaTauri Honda</td>\n",
       "      <td>5</td>\n",
       "      <td>52</td>\n",
       "      <td>DNF</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:34.090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Bahrain</td>\n",
       "      <td>18</td>\n",
       "      <td>6</td>\n",
       "      <td>Nicholas Latifi</td>\n",
       "      <td>Williams Mercedes</td>\n",
       "      <td>17</td>\n",
       "      <td>51</td>\n",
       "      <td>DNF</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:36.602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Emilia Romagna</td>\n",
       "      <td>15</td>\n",
       "      <td>5</td>\n",
       "      <td>Sebastian Vettel</td>\n",
       "      <td>Aston Martin Mercedes</td>\n",
       "      <td>13</td>\n",
       "      <td>61</td>\n",
       "      <td>DNF</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:19.074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>17</td>\n",
       "      <td>63</td>\n",
       "      <td>George Russell</td>\n",
       "      <td>Williams Mercedes</td>\n",
       "      <td>15</td>\n",
       "      <td>48</td>\n",
       "      <td>DNF</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:45.959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>18</td>\n",
       "      <td>33</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>3</td>\n",
       "      <td>45</td>\n",
       "      <td>DNF</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:44.481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>Austria</td>\n",
       "      <td>17</td>\n",
       "      <td>5</td>\n",
       "      <td>Sebastian Vettel</td>\n",
       "      <td>Aston Martin Mercedes</td>\n",
       "      <td>11</td>\n",
       "      <td>69</td>\n",
       "      <td>DNF</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:08.420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>Netherlands</td>\n",
       "      <td>17</td>\n",
       "      <td>63</td>\n",
       "      <td>George Russell</td>\n",
       "      <td>Williams Mercedes</td>\n",
       "      <td>11</td>\n",
       "      <td>69</td>\n",
       "      <td>DNF</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:15.628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>298</th>\n",
       "      <td>Russia</td>\n",
       "      <td>19</td>\n",
       "      <td>6</td>\n",
       "      <td>Nicholas Latifi</td>\n",
       "      <td>Williams Mercedes</td>\n",
       "      <td>18</td>\n",
       "      <td>47</td>\n",
       "      <td>DNF</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:40.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>15</td>\n",
       "      <td>11</td>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>Red Bull Racing Honda</td>\n",
       "      <td>4</td>\n",
       "      <td>55</td>\n",
       "      <td>DNF</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>1:26.419</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Track Position  No            Driver                   Team  \\\n",
       "16          Bahrain       17  10      Pierre Gasly       AlphaTauri Honda   \n",
       "17          Bahrain       18   6   Nicholas Latifi      Williams Mercedes   \n",
       "34   Emilia Romagna       15   5  Sebastian Vettel  Aston Martin Mercedes   \n",
       "116      Azerbaijan       17  63    George Russell      Williams Mercedes   \n",
       "117      Azerbaijan       18  33    Max Verstappen  Red Bull Racing Honda   \n",
       "176         Austria       17   5  Sebastian Vettel  Aston Martin Mercedes   \n",
       "256     Netherlands       17  63    George Russell      Williams Mercedes   \n",
       "298          Russia       19   6   Nicholas Latifi      Williams Mercedes   \n",
       "434       Abu Dhabi       15  11      Sergio Perez  Red Bull Racing Honda   \n",
       "\n",
       "     Starting Grid  Laps Time/Retired  Points +1 Pt Fastest Lap  \n",
       "16               5    52          DNF     0.0    No    1:34.090  \n",
       "17              17    51          DNF     0.0    No    1:36.602  \n",
       "34              13    61          DNF     0.0    No    1:19.074  \n",
       "116             15    48          DNF     0.0    No    1:45.959  \n",
       "117              3    45          DNF     0.0    No    1:44.481  \n",
       "176             11    69          DNF     0.0    No    1:08.420  \n",
       "256             11    69          DNF     0.0    No    1:15.628  \n",
       "298             18    47          DNF     0.0    No    1:40.000  \n",
       "434              4    55          DNF     0.0    No    1:26.419  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raceResults.loc[(raceResults['Time/Retired'] == 'DNF') & (raceResults['Position'] != 'NC')]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66e71a8b",
   "metadata": {},
   "source": [
    "## Total Laps and Distances Driven in Race Sessions\n",
    "\n",
    "After many analyses we've inspected here, there are a few more things to see where you could find them interesting and informative.\n",
    "\n",
    "Let's begin this part by calculating the **total laps driven for all drivers** raced throughout the season according to the data in race results... _(Note that, only full laps are considered)_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "22d25482",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Dus+mTVt4//1PbI47uRulyWTitttusl7rpZfGsG+f8brUq3fqsXNFRUVs2bKV5ctXYjKZqF8/lJYtI05M/OJGs2ZNiI6OIjZ2XaX8nYmIVCb1ExARucyUbbGJioqkTZso67ajo6N1gWyA2Nh1FZ7jYjQ8lB1D6OXlabPGW4cOMed0rtDQ0nX2CgoKyc3NA4xJQzp2LD3Xxew+t23bDm666Y5yjy++qLibYomwsIbcfvvN1u0tW7bx3nsfVxj0AWzeXLpUQNkJYLp06Wh9XnYNQIB7773TGgAVFxfzwQdVH/QVFBSydet26/Ztt91UbukNf38/68yWUDo+tOx6hq1atbQGumC8x7/55n+MHfsi//nPTYDxw0HZ91PZoKvs61LS0uzm5sqrr77A11//j08+eY86dQKxWCzs27efmTPnsHt3vPUYX19foHL+zkREKpNa/ERELjNJScksX76Szp2NL7ijRj3M2rUbyMjIoFWrltaxSdnZOfz++5/VWM7D5Obm4ezshL29PY8//hD//ruI4OAgrrqq9zmdKyWldKr84OAgXnzxGfbu3UdUVCR16wZZ82rC5C633DLSZmxeWlo61103tNx+f/wxnby8PJYvX8mIEcNwc3Olffu2PP74gxw7lm0NAouLi5k3r3SynRYtImwmOElJSaV58/Byy1bs2rW70gOWP/6YTmRkC8xmMyEhwXzwwZusX7+JzMyj+Pr6EB0dZW39zczMZNmyFdYyxsauIyYmGicnJ157bTSrVsVSVFREp04dcHJyIiysIevWGYu4Z2Uds074AvDii8+wdu0GGjQItbnPkmtlZ+eQk5Nj3f/VV19gzZp1HD+eS/36ITYTBO3caSz6XlP+zkTk8qHAT0TkMvTVV9/j4eFh/ZIdExNtk5+dnWMzxX11KCwsZM6cedZxcI0bh9G4cRiAtYWlZPtM9uzZy5Yt26xf0MPDmxIe3hQw7rVkDFzZCTkuRaGh9coFYD16dK1w31mz5pCXl0dW1jG++up7HnzwHuzs7IiJaWuz319//U18/F7r9slBdZ06gRWORfznn38rPfDbsSOOb7/9if/8x+iG6erqatMCVyIr6xjvvvuxzVqGX331PcHBdQkODsLFxZmePbvZHLNp0xbrzK4Wi4WZM2dbx3YGBgbQr18fwHjfFRYW4ezshLu7G66uLuTkHOfzz79m9OinqVs3CA8Pd664onu5ck2bNsNmIpea8HcmIpcPBX4iIpeh48dzef31d+nWrTPdunWmQYP6uLq6kJ5+hPXrNzJ9+iybWTmry8SJU8jKyqJXr574+fmRnp7OsmUrmTZtBk8//dg5nev99z/huuuG0q5dG7y8PElPP8KOHXFMnjyVV155Hj8/Xxo2bEBAgL911sdLzfkuFr9y5WrS09MZNmzwieUR7Dhw4BBz5sxj0aKlNvtGRDSrjKKet3nzFrB9+0769r2S5s3D8ff3x8HBnuzsHJKTk9mwYTOzZ8+zruFX4ujRozz//CsMGHA1HTq0IzAwgOLiYg4fTmbhwqXMn7/QZmzq77//eeK9dQV16gSQlXWM/fsTmTbtL/r0uZLu3bucCNbasmjRUjIyMnnhhVfp3fsKOnaMwd/fHzc3V7Kzs9mzZy/z5i1g7doNNmWqKX9nInJ5MAUEhGqKKBERERERkVpMk7uIiIiIiIjUcgr8REREREREajkFfiIiIiIiIrWcAj8REREREZFaToGfiIiIiIhILafAT0REREREpJbTOn4ictH06NGV++67E4CtW7czZszb1VyiqjFhwjcVpufn55OdnUNCQiKLFy9j2bKVWCznvqJO2ddxw4ZNvPXWBxdU3upU9rW6//5Hycw8Wm3XL0t1dW4u1n0OHz7Euuj6yYqLi8nPL+Do0aPEx+9j5szZxMXtrpJyXEydO3egc+eOhIU1wMPDg+LiItLTM9ixI465c+fZLBh/qfL39+Ojj94BID+/gNtvv7eaSyRyeVLgJyJykTg6OuLo6IiPjzdRUZF07dqZDz/8lLy8/OoumpxEdVXzmM1mnJ2dcHYOIDAwgPbt2/LJJ1+wYsXq6i7aebGzs+Oxxx6kbdvWJ+U4EBwcRHBwED16dOGnnyYye/Y/1VJGEalZFPiJiFShf/75l5yc45jNZlxdXWjUqCENGzYAoE2bVtxxx2189tlX53TOhIRE/vxzJgCHDiVVepkvV6qr81cd97l/fyLr12+0bpvNJjw8PGjXrg3u7u6YzWb++99bWLt2A/n5NS9gHzz4GmvQV1xczObNWzl48BBOTk5ERUXi5+eLnZ0dt956A3Fxu9izZ2/1Fvg0jh8/bn1/FBUVVXNpRC5fCvxERKrQn3/OJDU1zSatV6+e3HXXfwDo3r0Lc+bMZ/fuPWd9zvj4fcTH76vUcorq6kJUx33Gx+/l118nl0uvVy+Yt956FbPZjIeHB02bNmbLlm0XtWyVoWfPbtbnH374P1avXmvddnBw4NVXX6BBg1DMZjNXXNH9kg78srNzKqwrEbm4FPiJyCXPZDJx1VW96datE3Xr1sXZ2Ynjx3M5ePAg8+cvYuHCJTb7l4zbSktL55FHnmLQoGu44opu+Pj4kJyczD//LGDu3Pnlxmy1aBFB//59ady4Ee7ubhQWFpGamsratRuYPn0m2dk5lXI/8+cvpG3b1rRt2waAPn2usAYTzZuHM3r00wAsXLiEtWs3cPPN1+Pt7U1qahovvzyWtm3blBtP1a9fX2677UYA1q7dwLvvfmhzTQ8PDz799D3s7e3Jz8/n//7vMXJyjgPg6+vD0KEDiY5ujaenB1lZx9i6dTvTps3gwIGDNue59947rF9IX3vtLXJyjjNixFDCw5thNpuJi9vF5MlT2bXr7IOjEmazmUGD+tO79xV4e3uTnJzCwoWLmTVrLsXFxQA89NC9dO7cEYBp02YwceIUm3P07duL//73FgBiY9fy/vufnHM5yqotdfXGG+/Rvn1bunbtjMViYfHipXz//QTs7Ozo378vHTu2p27dIJycHMnJOc7+/QksWLCYpUtXnNXrdKoxfie/Rt999xPDhg2mc+cOeHl5kZKSwvz5C/n773/OawxlRQ4cOEhWVhZeXl4AeHp62uQ3bdqYQYP606RJY9zd3SgutpCens769ZuYMmUa2dnZ5c7ZsWN7evfuScOG9XFwcCAt7Qhbt26r8McCgKioSAYO7EejRg2xs7Pj8OEUVq5czYwZs8+69dHb29v6PCvrmE1eQUEBv//+J337XglgfX+UFRwcxLBhg4iMbIGrqysZGZls2LCJqVP/Ij39iM2+JpOJK67oTo8eXQkJCcbZ2Znc3DwOHjzI0qUrmDv33wv6vDybMX5du3aiZ89uhIbWw8XFlfT0dDZs2MT06bPKlfd8P4c8PT0ZOnQAUVGt8Pf3xWw2c/RoFrt27eavv/4+r88tkZpEgZ+IXPJuv/1m+vbtZZPm5uZK06ZNaNq0CQEB/kyePLXccSaTiccff9D6pR0gJKQet99+M40bh9l02+vatRP3338XZnPpZMf29vaEhNQjJKQerVq14LXX3iY3N7dS7mnlylhruSIimlW4T+PGYXTt2gl7e+OjOj8/n2PHyn8pBViyZBk33ngdDg4OREW1xMPD3ebLYufO7a3nWb16rfWLYmhoCM89Nwovr9Ivx76+PnTr1pkOHdoxbtynrF+/qcJrtmrVkgEDrsbBwcGaFhUVSUREOC+9NJZ9+85t0on777+LyMgW1u2QkGBuvnkkzZo15YMPjABuwYIl1sCvc+cO5QK/Dh3aWZ8vXrz8nK5/KrWhrm666XoaNAi1bh8+nALAk08+QlRUpM2+Hh7utGzZnJYtm+Pv78+0aX+d8rU5Fy4uLrz00nM0bFjfmlavXjC33nojXl5eldYi1KBBKB4eHtbt5OQU6/Pw8KY8++woHB0dbI4JCqpDv351iIpqyXPPvWITnN1zz3+54oruNvuXjLHr1Kk9r776FomJB6x5gwdfww03XGezf/36IdSvH0L79m0ZO/bdCoPLkx08eMj6Wj3xxMPMm7eAVatiiY/fh8ViYfXqNaxevabCYyMjW/D44w/h7OxkTQsI8KdPnyvp1Kk9b7zxPvHxe615d955G7169bQ5R9nP2Pr1Q/nqq++teZX5eeng4MAjj/xfubGMQUF1CAqqQ/fuXfjgg09P2Wp7tp9Dnp6ejB37In5+vjbH+/r60KFDDG3atObttz9g69btZyyzSE2l5RxE5JLWoEF9a9CXm5vHggWL+fvvuTZfWvr161Phsb6+PrRt24bExAPMnWvbRa979y7WAAKML8YlX2LWr9/IzJmzWbhwifVLd1hYQ66+unel3VfZ1pk6dQKxs7Mrt09ISD0KC4uYP38hsbFrWbbs1K0vx45ls3btBsD4AtaxY4xNfteunazPS1pI7ezsePTR/7MGEklJh5kzZ771C5ajoyP/939323yJLmvo0IHk5eUxb94Cmwk0HB0duOqqc3+tIiNbsH9/InPmzLeZjbF9+7bWL96bN28lJSUVgMDAABo1amjdz9PTk+bNw0+8HsdYu3b9OZehIrWhrho0CCUx8SCzZ//D/v0JrFixmqioltagLyvrGAsXLmHmzNls3rzVetx11w0p90X5fHXo0I769UNYu3YDs2f/YzOD69VX97YGu2crLKwhN9xwnfVxyy038MAD9zB69DPWv+X4+L02f/f/+c/N1qBv8+atzJw5m5UrV1NYWAhAcHBdWrduZd2/V6+eNkHf+vUbmT37Hw4ePASAu7s7DzxwjzW/RYsIrr/+2jL7b2Lu3PmkpaUD0LBhA2tr75n89dcs63M3N1cGD76GMWNeZPz4j3j88Qe54oruuLq6lDvO3d2Nhx661xr07d27jzlz5lm7grq7u/PQQ/da38d16wZZg77c3DyWLl3BjBmziY1da21p79WrJ02bNrZeozI/L2+5ZaTNWMY1a9bxzz//WgN2V1dXHnvsQQIDAyo8/mw/h/r372t9Lx86lMTcufP5+++51qDd0dGBO+649azKLFJTqcVPRC5p9vb2zJ07nwYN6jNz5mxWrTJ+4XZwsOfzzz/CxcUZV1dXPDw8yMrKKnf8li3bePPN9ykqKsJkMvHQQ/fRqVN7AK66qhfLl6/EwcEBHx9vwPiS9Pbb46zHL1iwmEGDriEx8QD79iVU2n0dP277S7irq2uF5f/hhwksWLD4rM65cOFiaxDRpUsn/vlnAWAESE2bNgGM7q8lwUJMTFvq1g0CYP/+BEaPHkNBQQEAt99+C1dd1Qt3d3d69uzKX3/9Xe562dk5PPfcK9aubjk5OdYvkCEhwWdV5rI2b97KW299YJ38oWx3rt69r2DBgsUnuiku49prBwPQqVMH6xfaDh3aWr+MrlixutImkagNdZWTc5xXXnndpvtdTEwb6/M//viTv/8unRny+uuvxd/fj8TEAxUGuufrp59+tV5n2bKVvPLK8wA4OTkRGOjPwYNnPzFMSSvaqezfn8i4cf+zbjs5ObJ+/UbS04+QnZ1t0+J/9923c+WVPQCoU6c0wBg4sJ/1+bff/sTcufOt5X3nnTH4+/vh5uZKcHAQBw8mMXBgP+t7cNKk35k69S/r8zfffBU/P1+6dOnIL7/8RkZG5mnvb9mylfj5+XH99cNs6sDNzY2YmLbExLTl1ltv5JdffuOff/615l9xRXfrDwAbNmzi7bfHYbFYMJlMPPHEQ7Rt24agoDrExESzcmWsTUA1f/5CfvrpV+v21Vf3oVmzJiQmHrC2glbm56W/vx+9e19h3X7//U+sP9g4OTny1FOP0bx5OK6uLlx77WA+//zrcuc428+hsvf54YefsX+/UT57e3seeOBujh3LJjHxIE5Ojpq9V2otBX4icknbvXuPzS/29vb2hIU1IDKyBSaTyZp+ctetEn/8Md0aAFgsFv74409r4Ne4cRh2dnYUFBRw4MBB6tULpmHDBrzxxiusX7+Bbdt2snPnrnJjsCrDyeNl7OzKd8AoLi5m5cqzn4p+w4bNpKWl4+fnS7NmTfDz8yUtLd2mBWnRoqXWa0dGNremL168zBpIgNHSdNVVvU7s16LCYGLVqjU245vWrdtg/cLl4uJ81uUu8ddfs2yCtenTZ1oDv4YN62NnZ0dRURGLFi1l6NCBmM1mOnVqz4QJkwDo0KG05Wzx4mXnfP1TqQ11tXnzlnJjVOPjS7vi3njjCFq2bM7mzdvYsWMnv/32R6WNuSuRn1/A3LmlAUpc3G6ys7Nxc3MDwNn53N8zFdm6dTt//z2XtWs3WFusAPLy8pk06XebfQMDA2jePNw6eytg7TLo6+tDUFCdE8fmMX/+wjLnyuP1198lK+uYtdumyWQiIiLcus+8eQusz7Ozc1izZh1XXdUbOzs7mjePYPnylWe8l+nTZ7J6dSy9e19Ju3ZtrOUp4eLibG2lKgn+ynaX/vffRdZ6tFgsLFq01NptOTKyBStXxrJ/fwJFRUXY2dnRr18f6tcPYePGzezYEcc///xbbqmIyvy8bN++9MeajRs327TS5+Xl8+uvk60/DrRr1waTyVTufXm2n0N79+6jc+cOADz//JOsXbuerVu3s2NHHB9++NlZl1mkJlPgJyKXPA8PD/r0uYI2bVoRFtawwi5hZYPAsk6eWv7QocMUFxdjNpuxt7fH3d2NzMyjjB//LU8++Qju7u40aBBKgwahDBliTD2+fftO/vnnX1aujK20e3Jxse2iVdGYn+zsnHKtTadjsVhYsmQZQ4YYQVGXLh2ZPn0WXbqUdmldtGip9XnZLnw33zySm28eWeF5S1qaTpaenm6zXbasZcf+nK2kpGSb7bJ1ZWdnh4eHOxkZmSQnp7Bt244TY9D8aNq0MUlJydZunocOJVXqwt21oa5SUspPQLJ79x7+/HMmgwdfg4ODA+3aRdOuXTRgdJVdvXotf/31d6Utz5CZmVmuFfb48Vxr4Heu75mFC5cwfvy3+Pr6MGzYIOuX/WbNmrBs2UqboK+sTp3a07lzRyIimlbYNbakHD4+Pta0I0cyypU9KemwzbaHh7vNmLovvvjolGUPDq64niqSlJTMzz9P5OefJ+Lv70fLls1p06YV7dpFWz8Lhw8fwr//LqKoqAhf39L3yqOPPnCaMtS13tuPP/7CbbfdhNlsJjKyhTV4zM3NZd26Dfz112yb7vWV9XlZp06g9XlFC9Hv25dg/Qxwc3PD3d29XGv72X4O/f33P0RFRdKyZXM8PNzp2bOb9Yelw4eTWbp0BbNmzam0SbxELkUK/ETkkhYUVIeXXnrWOrZp585dbNmyjZ07d3H33bfj6+tz2uPLDvgHrGN5SpT8ehwXt5vHHnuWHj26EBPTlqZNG2Nvb4+dnZ11oou//vrb2rp0ocp+8UtNTaOgoLDcPsePl5+p70wWLFjCkCEDAeML7vr1G6lXz+jutH37Tg4fLg2uyn4pys7OsWlFKuvk16xEfr7t/hfaQmRvb9ul8ORAoOwX+YULl9CypdEK1rlzR5suiUuWVM6kLiVqQ12dqny//jqZFStW0aNHV9q0ibK2KLm7u3PllT3o2rUTr7zyps2X/vNVUZkv9D1jsVhIS0vnq6++x9PTg5iYttjb23PXXf8hMzOTNWvW2+z/6KMPWCcASktLZ/78hezcuYsmTRrRp8+VNvuW/S3pbILSk/c5XVfOM50vMDCAsLAGeHl5ceRIhnUSl9TUNBYuXMLChUto1Kghr7zyPHZ2dnh5eRIUVIcDBw7anDsr69gpuzyXTZ8zZz4bN26hZ8+uREe3sXahdXZ2pnPnjnTs2N6mG2ZlfV4WFp65O7bta1X+/XK2n0MFBQWMHfsObdu2pnPnDrRqFYmnpxH416kTyLXXDqZLl4688MKrFc6SKlIbKPATkUvaiBHDrEHfDz/8wt9/z7Xmnc3Yo/r1Q2xm9QsKCrR+kTh55sXjx4+zaNEyZs2ai6OjI40bhxEdHcXAgf0BY7zPtGl/Vcovwq1atbQ+P9VsdWfzpehkhw8ns23bDpo3DycsrKHNl9mTl704ciTD+nzKlGk2r21FXaqqWkhIPZsxXnXqBJyyrlatWsPtt9+Mq6srHTvGEBpaDzCCw8oO/GpDXZ0qIDTKkcIvv/zGDz/8go+PN+HhTbnqqt5ERDTD0dGRYcMGXvCyGBfDV199T3h4aSveXXfdzvbtz1tbaFu3bmUN+nbv3sPLL79hDX5KAu6yyi4h4Ovrg6Ojo81sn507dyAoqA6JiQfZuTOOrKxjFBQUWH9sevLJ520+K87lb6pFiwjuuee/gBHsxcauLXfsnj17yc0tbTEt6e5+5MgR648VX375LbGx686qDEeOHGHq1BlMnPg7Hh7uNGvWhJ49uxMTE43ZbOa664badMWsjM/Lsq11ZWd7LVF2Jtpjx46VW9bifOzeHW+dXKlevWAiIpoxZMgA/P39CAqqQ48e3Wz+vkRqE83qKSKXtNDQ0skbynbxiYxsYTOt/al+QR8yZCBOTo7W7Wuuudr6PC5uN8XFxURENOPtt1/ju+8+56WXnsHBwVg/bdu2HUyc+LvNr79namE8GxERzWy69JWdmMHW+QVeZYOGkokTcnNzy3W92rZth/X5lVd2t3mdRo4czvjxH/Hii8+Um+a9qgwc2B8Hh9LfIwcNusb6fNeuPTYtfvn5+dYZ/Hx8vK2tfzt2xFln/awMtaWuKvquf+ONI/jkk/f4+utPrV/WjxzJYMWK1TZj8SprVs+qdvRoFj/+WDoxiZeXJyNHls6wWfLjABjdAUuCPmdnZ5ulBEq6jaenH7F257S3t7eZpdLBwYERI4YxYsQwHnvsARo3bkRRUZFNF+Orr+5js//777/BuHFv8cQTD1m7WZ7Kxo2bre93f38/Ro4cXm6fXr16WoO+/PwCDh0yyrp9+07rPn36XGnz2fjAA/fw2Wcf8Nxzo4iJaQtAv359+fDDt/n66//xn//cBBgthWvWrGf69JnWY0veB5X5eVk2kIyKiqRNmyjrtqOjo819lw1gz5XJZOLZZ5/gyy8/5rPPxlmXZTlw4CDz5i1gw4bSZVBqyvtd5HyoxU9EqkWDBqE899yoU+bv2BHHlCnTSElJsc7MdscdtxER0Qx3dzfrWKQSJ3fpLNG4cRhvvPEKmzdvJTQ0hPDwpta8OXPmAcaU797eXtZ1qN5881U2bdoCmGjZMsI6ZfrRo1nnNOsgGGt6lXwRcnBwoG7dIFq1amHTLXH37vhzOueZrFy5mttuuwlXVxfrl75Vq9aUW1Nr5crVjBw5HB8fb0JDQ3j77TGsX78RT08P2rdvh9lsJiKiWYVrJFaFJk0a8cYbr7Jx4yYaNmxgs2Ze2UCkxIIFi8sFOhcyqcvlVld79+5n0CAj4Bs+fAhNmzbh4MGDeHp62vx97dix68Jv9CJZsmQ53bp1ti5T0atXT+bNW8i+ffttfhCIjGzBU089RkpKCu3aRdsEKGUnipo5czZ33HEbUDoBzsGDSURGtrB2i01OTmH9+o2AMY6sRYsIAK67bigREc1ITDxAixYRNuPZTh4feLL09CM27+/Bg68hOjqKnTt3UVxcTMOG9a2zv4Lxt1Dynvn330UMGNAPZ2cnoqIiefPNV9iyZRtBQXWsS1W4u7vzzTc/AkbrZ0CAP2DMCFqnTiDx8ftwdXWxWQN15844oHI/L5OSklm+fKV1aZ1Rox5m7doNZGRk0KpVS+trlp2dw++//3nac52OxWIhOTnF2nr/1FOPsWbNWjIzjxIUFESbNqVLeJTcp0htpMBPRKqFm5ubzexzJyv5EjNjxmxat26F2WzGxcXZZurv7Owc3NxcAaMLZ9n11kqsW7eB6OjW5WbDmz9/IatXrwWM2ePef/8TnnrqMZydnahbN6jcJBmFhYWMH//NOS8RcPK4obI2bNjE119/f8r885WXl8/Klaut09ND+a6DJft99NFnPP30Yzg7OxMQ4G9dM7HEH39MvygLGqemphEfv4/27duWm/hi8eJlFc6YuWvXHhITD1p/GMjPz7+gCXgut7pavnwlzZo15uqr+2A2m2nTppXNF2CAhIREpkyZdo53Vb2++up73n77NZydnTGbzdx++8288sobrF27wTobJWBzr2U/S+rUKf2s+OefBTRt2oTu3bsARqtU2QXvjx/P5dNPx1tb52Jj1zJr1lz69+8LYDNRSsl1Pvzws1NOPFPW999PwM/P1xqshYaG2PSAKLFp0xZ+/rm0pTM9/QhffPE1Dzxwj82i6iWKi4v55psfrcFnXNxufv55onXCoObNw60TJZU9Z0lramV/Xn711fd4eHgQGdkCs9lMTIztj3rZ2Tl88MEnNjN3no+ffppI/fohNG3aBGdnJ7p27Vxun6VLV1j/XxCpjRT4icglbevW7bz55vsMHz6EkJB6FBUVcehQEvPnL8TOzs46DiYmpm25iRwAvvzye7p160SfPlfi4+PN4cPJzJkzv1yXve3bd/LUUy9wzTVX0aJFc/z9fXFwcODIkQy2b9/JjBl/k5Bw4ILupaCggGPHsomP38fixUsrdZbQky1YsNgaTJTMglmRHTvieOqp0QwZMoBWrVri7e3N8eM5JCQcsE6JfzFYLBbGjfuUgQP7ceWVPfD19SU5OYV58xZYW2YrsmvXbmvgt2bNuvOaZKUil0tdff/9BNat28hVV/UmJCQYHx9vCguLSEpKYvXqtcyaNafGrWmWmprG5MlTueWWGwAID29K166dWLp0BWPHvsPIkcOJjGyBm5sbqampbN68lb/++pv3338TR0cHWrVqabOW22effcXGjZvp1asnDRqE4ujoyJEjGWzevI0//5xhMwkPwI8//sLWrdvo0+dKwsIa4uzsTHp6Olu3bufPP2fajDk+nYKCAt566wM6dmxP166dCAtrgKenB8XFxWRlHWPPnr2sXLma5ctXlTt25cpYDh5MYtCg/jRvHo6npwdZWcfYu3cf06fPYscO21atGTNms3PnLvr3v4qGDevj6+tDcbGFlJQU1q3byIwZf9uMr6vMz8vjx3N5/fV36datM926daZBg/q4urqQnn6E9es3Mn36LJvxlucrLy+P1157mx49utK9excCAwPw8HDn+PFc9u3bz+LFyyp1GRiRS5EpICD04o7eFxGpYhMmfGN9fv/9j5KZebQaSyNVxcvLk3fffd3aUvP22+OsXe5ERETEllr8RESkxnBxcWb48CEUFxfTsWN7a9CXnJxiM0GDiIiI2FLgJyIiNUZubh5XXdXbunA1GOuR/fDDhIu+/ISIiEhNosBPRERqDIvFwq5de2jYsAGFhQUkJBzgzz9nqrVPRETkDDTGT0REREREpJbTAu4iIiIiIiK1nAK/GqJZs4bVXQSpAqrX2kn1WjupXmsn1WvtpHqtnVSvF0aBXw3h4uJU3UWQKqB6rZ1Ur7WT6rV2Ur3WTqrX2kn1emEU+ImIiIiIiNRyCvxERERERERqOQV+IiIiIiIitZyWc6ghZqYkVHcRRERERESkilwTEFql51eLn4iIiIiISC2nwE9ERERERAR4HRhzUtok4DqgO3A9MPWk/P3AI8CVwADgC6DwFOc/APQEpldOcc+JAj8REREREbmsWYDPgT9OSp8MfALcAfwC3AS8Bcw8kX8UuBvIP3H8GOAf4I0KrlEMvAzkVG7Rz5oCv5M0auTM9983Y+fOGPbsac+//7bippsCznhcx44exMZGX4QSioiIiIhIZUkE7gemAEEn5f0OjACuAUKAoSeel7TY/QXkAW8C4UA08ALwJ3DwpHN9D5gAu8q+gbOkwK8MkwkmToxgw4ZsoqLW0Ljxap57bi8vvdSAgQN9T3vsypVZxMSsu0glFRERERGRyrAJqIfRohd8Ut4TwLUnpZkwWvoAEoBGgFeZ/PAT/5aNDHYAPwMvVkJ5z5cCvzL8/Oxp0MCZKVNSyc21YLHA8uVZvPrqPhwcTDg7m3jrrYasXNmG+Pj2rFjRmv79fQDo0sWTbdvaATByZAC//hrBp582ZvfuGFatasOIEf4APPJIMPHx7a2PhIQOHDrUEWdnU7Xdt4iIiIjI5ao/MBrwryCvHUZQWCIJmAN0PrEdACRjdOMsUdLSl37i33zgJYxWxZDKKfJ5UeBXRmpqIUuWZPLbb8156qkQunb1xNXVzM8/p/DHH2n83/8F07SpC336bKJx49X88ksKr7/esMJz9erlzcKFmTRrFsuXXybxxhsNcXIy8eGHBwkLW01Y2Gqiotayd28ur7+eQG6uVtUQEREREblUHQEeBfyA20+k9TmR/jGQC6QB72J05yyZ4OVTjABx+MUraoXsq/n6l5wbb9zOf/5Th4EDfXnoIaOxd8aMdJ59di/ffJPEt98eJju7iHr1nDh2rIi6dR0rPE9CQh6TJqUCMGlSCmPHNsTf34EDB/IBMJth/PimbN6cw8cfn9wDWERERERELhWJGDN35mLM2ul+Ir0+xkQubwATABfgXmAX4AasAWacyDuT1q3Dz7zTWdiwYUeF6Qr8TpKXZ2H8+CTGj0/CyclEx44evPhiA8aNa8To0ft4660w2rZ1Z+/eXPbty8NsrriLZlpagfV5YaHRmld239dea4Cvrz3//W/FFSMiIiIiItVvB/Aw4Al8TfkJYHqceKRijPXLA97H6Nb5F3AMYzmIEkUYk8HMBT4qk36qgK2yqKtnGUOG+LF6dRvrdl6ehUWLjvLBB4lERrrx7rth7Np1nBYtYrn66s18803SeV3nttsCGTzYj9tv36kuniIiIiIil6i9wANAXeBLygd96zHG7hVhjBF0ABZitPxFAQ8Bv2FM7FLysMNoFXyhqgt/EgV+ZSxalImbmx1jxjTA399oDA0Lc+I//6nDnDlHcHe3Ize3mKIiCA525JlnQgGwtz/7iVm6dfPkpZfqc/vtOzl0KL9K7kNERERERC7cS4Aj8ArGmL3UE4+ME/kNMVoEP8ZYnP1f4B3gvxjdQX2B0JMeAD5A4EUof1nq6lnGkSOFDBq0hWefDWXhwta4uZlJTS1k8uQU3nvvAK1bu/Huu424884g0tIK+P77w7Ru7UazZi5nfY3HHquHg4OZn34Kx8nJjOlEzHjDDdtZuTKriu5MRERERETOxT5g64nn152UF4Kx2Ls3RrfOcRiLvQcA92As9H6pMQUEhKqvYQ0wMyWhuosgIiIiIiJV5JqA0DPvdAHU1VNERERERKSWU4tfDdG6dXiVz/QjF5/qtXZSvdZOqtfaSfVaO6leayfV64VRi5+IiIiIiEgtp8BPRERERESkllPgJyIiIiIiUstpjF8NkTLvu+ougoiIiIiInEZA79uruwinpBY/ERERERGRWk4LuIuIiIiISO3x6vtQVAyvjCpN+2Wq8UhKgeBAuPU6GD6gNL+gAD78CmbMg9w8aNsKnn0IQuqW5v/ve5g1HzKzIKY1PHk/1K93Me/sgqjFrxKFhDhWdxFERERERC5PFgt8+i1MnmGbPvFPGPcl3HMzTPnSCPrGfgTT55bu8+oHMHshvPk8/PCREfw9PNo4J8DrH8Nvf8Fj98CETyHQD/7zCBzJvHj3d4FqReCXnNyJiAiXcunbtrWjSxfPSr3WL79EcOutgQDExkbTt683AC+/XJ+77gqq1GuJiIiIiMhZSDwIdz0Bk6ZD3UDbvN+mww1DYGBfCA02WvoG9YGpf5ceO202jHkaOkZD0zB44VHIzoaEg3A0C36fCY/dDVdfAWH14flHwN0Nfp12se/0vKmr5zm68cbtFab7+jqQnl5wkUsjIiIiIiJs2Gp0y3zrBXhqjG3eMw9C0EnBoMkMWceM58vWgI+3EfSVCAuF2b8YzzdvN1r+2kaV5pvNEN4YYjdU+q1UlVrR4nc2IiNdmTy5OZs2tWXv3vZMmhRBQIADAB991JgXX6zPX3+1JD6+PVOntiA62o0ZM4ztSZMicHe3A+CPP1pwxx11bM59331BDB/ux113BfHVV00B6NnTizlzItm9O4b581vRu7e3df/k5E7cdVcQa9ZEs2NHDP/7X2McHEwX54UQEREREaltBvSBV54Ef9/yeTGtS8fqARw6bIzV69re2N6XYOTPmAfX3Q29r4cnXjHGAwIE+Bn/Hk62Pe/BJEjPqPRbqSq1JvCbMaMlcXExNg8fn9IGza+/bsasWem0arWW6Oh1eHjY2wRwN9wQwOOP7yEycg0BAQ788EM4jzyymzZt1hIS4sT11/uf8tqff57ElClpfPVVEnfdFUd4uAs//BDOhx8eoFmzWMaOTeCrr5rSvHlpd9Tu3T3p0WMD/ftv5oorvBk4sII3qYiIiIiIVJ70DHjgeSNAvOMGI+1YDuzdDz/8Bk/+H7z7IqQdgbtHQV4+1AmADtHw3hewLxEKCuHn32H7LiisOT3+ak1XzwEDtrB9+3GbtG3b2lmfjxy5jX378nB1NRMc7Eh6egF165ZOxjJ37hF27jSOX7/+GHl5FnbtygVg7dpjhIQ4nXVZhg71Y9GiTGbMOALAvHkZzJ59hOHD/RkzJgGA8eOTyM4uZs+eXFavzqJRI+fzu3ERERERETmzxINw/7PGxC3fvg8e7ka6vT1kZcN7L5W2DL73ktHyt3gl9OkOrz8DL7wFg28HOzN06wiDr4Ydu20u0bp1+MW9pwps2LCjwvRaE/idSXS0OxMmGF02t23LwcvLnrS0Qmt+Rkbp86IiOHq0dLu42OjGe7YCAhxITMyzSUtMzCM4uDTQTEsr/XWgsNCC2ayuniIiIiIiVWJbHPzfs+DpAT9+ZDvmr44/uDjbdgf18wEvTzhwyNgO9Ifx7xjjAi0W4zyPvQShdW0uc6qg61JQa7p6nk7duo588kljHnxwN1FRaxk5cjvbt+fY7FMyU2tlSEzMIzTUtoWwfn1nUlJqTlOwiIiIiEitEL8f7nkS6taB78eVn+ilbSs4ngt79pWmpaZDRqYxC6jFYgSNy2ONVkJPDziWDavWQeeYi3orF+KyCPzc3IzbPH68CIBevbwZPNivUidUyc8vtk4AM21aGl27ejJggA9ms3G9q6/24Y8/0irteiIiIiIichaefxOcHI3umoVFRlCXml66Bl+7KCP4e+Z12LAFdu6Gp8dCw1Do3hFMJvDygPfHw9adsHOPscZfYAAM7FO993YOLouunrt25fL++weYMqUF9vYmdu48zg8/HKZbN69Ku8b06emMH9+U0FAnRo7czu2372T06Pp8/HETEhLyuP/+ONavz66064mIiIiIyBnsTYDNJ7pfDr7dNi80GGb8aAR2H42B9z43Jn4pLIRObWHsM+BgrALAsw/DW5/AvU8Z2906wDsvlObXAKaAgNBK7OQoVSVl3nfVXQQRERERETmNgN63V3cRTumy6OopIiIiIiJyOVPgJyIiIiIiUsupq2cN0bp1+CU9PaycH9Vr7aR6rZ1Ur7WT6rV2Ur3WTqrXC6MWPxERERERkVpOgZ+IiIiIiEgtp8BPRERERESkltMYvxoi+fGE6i6CiIiIiIicQuD7odVdhNNSi5+IiIiIiEgtZ1/dBRAREREREakM9/4BRcXw1fDStE+WwScrICEDGvjA493grval+fmF8Oxs+Hk95BRA94bwyWAI84W9RyDs7YqvFeYDe56qwpupZAr8RERERESkRrNY4KV/YPwquDOmNP2zFfDMbPh8KHSuD//ugf+bBk52cGtbY597p8I/u2DCDRDoBg9Ph8E/wMZHINQLDj1ne63Nh6H/t/DclRfr7ipHje3qmZzcib172xMfX/pYsaI1N90UYN1n0aIorrzS67yvER/fnqZNnS+4rBERLiQnd7rg84iIiIiIiK096dDrK/hsJdT3ts37fCU80AluiYbGfkZL363R8O2a0mO/WwPfj4BejSEyCD4bCkfzYHca2JkhyKP04e8Kj8+A4ZG2rYY1QY1u8evXbzPbtx8HwGyGYcP8+OSTJqxenUVcXC49emy8oPOHha2ujGKKiIiIiEgVWb4PGvnCLzfADb/Y5n00qHwwaDbBESOEYE4cBLgZQV+J8ADY93TF1/p8Jew7ArP/W2nFv2hqbIvfyYqLYcqUNLKyiggPdwUgNjaavn29AaPVberUFuzZ057Vq9swfLgfACYTPPFEPTZsaEtcXAzff98MHx8jHk5O7kREhAsAQ4f6MXduJDt3xrBjRwzvvBNmvXZsbDTvvhvG9u3tePvtMEwmeO65ULZvb8fGjW0ZOtTPpqw9e3oxZ04ku3fHMH9+K3r39q7iV0dEREREpHa6ORq+Hm60yJ2sZyNjrF6J/Rnwywbo18zY3pliBI0T1kPrDyH4dRjxMyRmlj9XfiGM+Rce7Qp1PaviTqpWrQn8HBxM3HNPEA4OJtasOVYu7+efI1i8OJPw8FjuvjuOd99tRJMmztx2WyAjRwZw7bVbadlyDTk5xbz+ekOb40NDnfjgg0Y89VQ8zZrFMmjQFq691o/u3UtrPCTEiTZt1vLqq/v573/rMGiQL336bKJ79w3ExJS+C8PDXfjhh3A+/PAAzZrFMnZsAl991ZTmzV2q9PUREREREbmcpRyDAd9BkDs8c4WRdjQPtqfAe4vhg4Hw201w+Bj0/gpyC2yP/2UDHMuHh7tc7JJXjhrd1XPGjJZYLODoaMSv//6bwfDh2zh0KN9mvw4dPHB1NfP++wewWGD9+mwGDdpCUlIBw4b58+WXSezenQvA88/vJSDAweb4pKR8evTYSEJCHj4+9vj42JORUUTduo7Wff76K53cXAtQxJAhfnz99WESE41yvP12Aj16GGMNhw71Y9GiTGbMOALAvHkZzJ59hOHD/RkzRmv1iYiIiIhUtj3pxoQsOQWw8B7wOjGNh4MdZObC5JtLWwYn3wx1X4eZO+DayNJz/LgOhrcEP7eKr9G6dXjV3sRZ2rBhR4XpNTrwGzBgC9u3H6d+fSe++64ZaWmFrF17rNx+AQEOHD5cgKXMUvWbN+dY88oGiunphaSnF9ocX1ho4ZZbArn55gCys4vZuDEbBwcTJpPJuk9ycuk5AgMdSEoq3d6/P8+mLImJpdsAiYl5BAc7IiIiIiIilWvdQSPo83GBZfdBqHdpXj1PcHO07Q4a6A5+rhB/pDQt4zgsjIc/bzv1dU4VcF0qakVXz/3787jtth0MHOjLo48Gl8s/dCifOnUcKBOn8d//1qFtW3cOHconKKg06Kpf34lRo+rZHD9smB9Dh/rRq9cmOnZcz913x5GXV2yzT9mgMimpgJCQ0nOWbRlMTMwjNNTJ5tj69Z1JSTmpLVlERERERC7I9mTo8xU08IYl99oGfWCs2ZedD9uSS9OSsiA1BxqXCQZX7AcL0DOMGqtWBH4AiYn5jB69j1GjQmjRwtUmb+3aY2RmFvLQQ8HY2UF0tBvPPhtKVlYhU6akctdddWjY0AknJxNPPx1Co0a2Szh4eNhRUGAhL68YR0cTDz5YlwYNnHFwMFGR335L4Z576tK4sTPu7nY89VSoNW/atDS6dvVkwAAfzGbo1cubq6/24Y8/0ir/RRERERERuYzd9hs4O8CP10NBsRHUJWVBaraR3yPMCP5u+tWYHXTjIeN5uD9cU6bn5rpD0MgHXGtwJ70a3dXzZBMnpjB8uB/jxjWiX7/N1vSCAgu33LKDN98M46GHgklNLeCxx3YTF5dLXFwuAQEOTJ7cAg8POxYsyODJJ+PLnbd7dy/Wro0mN7eYZcuymDEjnWbNKp6QZcKEFOrUceTPP1tiMsH33x+2ztwZH5/H7bfvZPTo+nz8cRMSEvK4//441q/PrrLXRURERETkcrMzBVYnGs/D37fNa+wLu540Zvj/8zYYNRMGfA8FRdCnCfxwPTiWiZQOHTW6f9ZkpoCAUMuZd5Pqlvy4Jn4REREREblUBb4feuadqlGt6eopIiIiIiIiFatVXT1rs77z+lzyMwXJuWvdOlz1WgupXmsn1WvtpHqtnVSvtZPq9cKoxU9ERERERKSWU+AnIiIiIiJSyynwExERERERqeU0q2cNkXJT3+ougoiIiIiInCRgwtzqLsJZUYufiIiIiIhILadZPUVEREREpGabtxQsFujTrTRtw1bYsA2yssHTHaJbQmR4aX5RESyNhR17oLAQguvAFZ3By8PIz8uDxathz/4T+UHQowP4el/UW6ssavGrJHZ2ULeuo3Xb29sOd3e7aiyRiIiIiEgtZ7HA8rWw+aRlHjZuM4K6Dq3h5qFG0Pfvcti2q3Sfecsgbi/06wkjBkJhEUz/xzgnwOxFcDgVBvWBGwaDgz388bcRBNZACvzKmDy5OWPHNqgwb/XqNowc6X/KY8ePb0r//j7W7eXL2xAS4njK/Ut06eLJtm3tzr2wIiIiIiKXs8yj8Pss2LQdPNxs8zZth6jmENEEvD2Nlr6IxrA1rvTYbXFwVXcIDQZ/H+jVBfLzITPLCAKdHKF3F6gbaLTydWgNx3IgPfOi32plUOBXxo8/JjNsmD/29iab9B49PPH0tGfatLRTHuvr62Cz7efncIo9RURERETkgh1KAU8Po0XP08M2r2cnaBVhm2YyGd03AfYdBBdnI+gr4eMFd4w0AkV7O7i6JwQFGnnHc2H9ViPA9PWqsluqSgr8ypg5Mx2LBfr29bZJv/HGQCZOTKFNG3dmz44kLi6GWbMiiY42fll47bUGdOrkwSuvNOCVV+ozd24kAH//HWltBbz99jqsWNGa7dvb8d13zQgMVGAoIiIiInLeIhpD3+7g5lo+L6Ru6Vg9gKPHYOceaBBibGdkGvnbd8PPf8BXv8CM+cZ4wJMtXAHjJxhjAft0A/uaOU2KAr8yCgosTJqUwsiRAdY0T087+vf3YebMdH7+OZxx4w4QERHL//53kAkTIvD2tmP06H2sWJHFSy/t46WX9tO372YA+vXbzKxZRxg0yJeHHw7mP//ZSevWa9m3L5fx45tW122KiIiIiFw+co7Dn3PB1QViooy0/AKjy+a6zdCjI1zTy9jv91nlx/C1ijDG+EU0hunzIOXUvQAvZTUzXK1CP/yQzMKFUfj42HPkSCHXXefP2rXHaN/egyVLjjJr1hEApk9P57//rcOgQX78+GPyac95882BfPHFIXbsOA7AmDEJ7N7dnkaNnKv8fkRERERELluZR2HqHGPM3nX9jXF7AGazMZ7vml6lLYMDesFXv8LeRGjSsPQcJbN4BnaFQ8nGxDG9S2cPbd26zEyhl4ANG3ZUmK7A7yTx8bmsXp3FsGF+fPPNYW68MYBPPjlEly4e9OrlTVxcjHVfe3sTK1dmnfGc9eo58swzoYwaFWJNs1ggNNSJggJLldyHiIiIiMhlLTkNps0xgr3rB4CHe2meu6sxS2fZ7qCuLuDsBEezIC8f9iVCWCg4nBiiZTKBn7cxwUsZpwq0LjUK/Crw44/J3HdfXVasyCI42JGZM9Np3NiZadPSePDB3db96td3Ij39zNO5Hj5cwP/+d4hffkmxpjVt6szevXm0b+9xmiNFREREROScpWcYSy94ecCQq4yJXMoKrgMFhcZ+JS162TnGJC5ensYaf7MWwDVXQtMwI7+42AgmG1e8CsClTmP8KjBjRjqhoU488kgwEyakUFBg4Y8/0rjqKh+6d/cEoEMHdxYsiLJO8JKfX4yHR+m6fXl5pduTJqVw//11CQtzwmSCO++sw6xZkbi66uUXEREREal0cxYZC21f3dMI2LJzSgM7gHpBRvD39wKj+2ZKOvy90JjZs2GI0foX3thYwD3hIKQdgbmLjZbA6JbVemvnSy1+FSiZ5OX+++vSocN6wOgCevfdcYweXZ/GjZ1JSyvkxRf3sXjxUQB+/z2VN94IIzTUiVGj4vn11xR++605Tz8dz8SJqXh72/PLLxEEBDgQF5fLzTfvIDOzqBrvUkRERESkFjqSaSy8DvDDFNs8Lw+4fYTRbXNwHyOwmzbHCA7rB8NV/YyAEYw1/JatNRZyz8uD4CC47hpwP2nNwBrCFBAQqkFmNUDKTX2ruwgiIiIiInKSgAlzq7sIZ0V9DUVERERERGo5BX4iIiIiIiK1nMb41RB9tuyvMVPFytlr3Tpc9VoLqV5rJ9Vr7aR6rZ1Ur7WT6vXCqMVPRERERESkllPgJyIiIiIiUssp8BMREREREanltJxDDZHy/P7qLoKIiIiIyGUvYGz96i7CeVGLn4iIiIiISC2nWT1FRERERKRmmXgvWIrghq9K0xZ/YjwyEsCnAVzxOHS+q0z+pzDlQdvzmO3g/UJI2wuvhVV8Lb8wGL2n0m/hYlPgJyIiIiIiNYPFArNeguXjodOdpelLPoPpz8D1n0PDzhD3L0z+P7B3gva3Gvsc2gyRg+H6L0qPM5mMf31C4dVDttc6tBm+6A99nqvae7pILvvA79NPGzNkiB/t2q3j8OECAJ58MoSICBfuvDOumksnIiIiIiIApO6BX+80AjKfk8bZLfscuj0AMbcY2/6NYe9yWPVtaeCXtBma9gLPoPLnNtvZphcVwtTHofVw21bDGuyyHuPn5WVHnz4+TJ+ezu2316nu4oiIiIiIyKnsXQ5+jeDpTeB7UrfMaz+CrvfZppnMkHOkdDtpC9RpfnbXWvY5HNkHQz+4sDJfQi7rwO/66wNYseIo33yTxK23BuLgYCq3j50dPP10COvXR7NtWzu+/ropdeo4ADByZAC//hrBp582ZvfuGFatasOIEf7WY0ePrs+mTW3ZsqUdv/4aQYMGTgC4uZl5882GbN7cls2b2/L++43w8LC7ODctIiIiIlITxdwMN35dcYtdk57GWLwSR/bD2l8gop+xnXHACAK3zYLXI+DlUPjxFsg8WP5chfkwZwz0fBS86lbJrVSHyzrwu+WWQCZMSGH16mOkphYweLBvuX2efjqU/v19GDRoK23briMjo5Bvvmlmze/Vy5uFCzNp1iyWL79M4o03GuLkZKJ7d0+GDPGjR4+NREWt4eDBfJ58MgSAd99tRJMmLvTsuZGuXTcQGOjAu++eYjCpiIiIiIicvWMpMH6AESD2ecZIS9pi/GvnALf9Cjd+C8k74NPekH/c9vi1v0DeMejx8MUtdxW7bMf4tW/vjpeXHXPnGs2/33+fzJ13BjFlSprNfiNG+DN69D4SEvIAGD16H3FxMTRp4gxAQkIekyalAjBpUgpjxzbE39+Bo0eL8Pe355ZbApk5M50nntiDxQLOziYGDfLlmmu2kJZWCMBLL+1j6dLWPProHo4fL75YL4GIiIiISO2SuseYkKUgBx5cCC5eRnrEVTAmBdxLe+cR1BJeDoFtM42xfCVifzS23fwqvETr1uFVeAMXbsOGHRWmX7aB36231sHX14GNG9sCYGdnws/PgagoN5v9/P0drEEfQE5OMUeOFBIc7AhAWlqBNa+w0AKA2Wxiw4ZsHn54N3fcEcTTT4eQkJDH6NH72LgxG0dHM4mJpedMTMzDbDYRFORAfHxpuoiIiIiInKXEdUbQ5+IDjywzZuosq2zQB0Y3Tjc/OJJQmpaTAbsWwl1/nvIypwqsLnWXZVdPDw87Bg3y5brrttKr1yZ69dpEz54bmTo1jbvusu0zfOBAHqGhTtZtNzczvr4OpKQUnHxaG8HBjuzencvQoVsJD49lwoQUvvyyKampBeTmFtucs359J4qKLNYWQBEREREROQeHt8P/+hjr9z2ypHzQt/AjeDEYisp8h0/fZ3QLrduyNG3fCsBijBmsZS7LwG/ECH/27s1l1apjJCcXWB8TJiQzdKgfvr6lDaETJ6YyalQ9QkIccXEx8+qrDdixI4dt246f5grQtq07P/0UToMGTmRnF5OZWUhmZiHFxTB5ciqjR9fH19ceLy87XnqpAXPnHuHo0aKqvnURERERkdrn59vAwRlu+dEI7o4mGY9jxpAsWg6AvCz45U4jSNyzFL4dDmFdoVmf0vMkrjNmDnV0rZ77qEKXZVfPW28N5Pff08qlL1yYSXp6AbfcEsicOcbYv48/Poizs5np01vi4WHH0qVHuemmMzfv/vVXOi1bulqPi4s7bl0XcPTovbz0UgMWLozCycnM338f4YUX9lbqPYqIiIiIXBaSd8L+1cbz108af+ffGF7YZfx7/1z461l4v4MxyUvkEBj6Xuki7gBHD4FrxWP7ajpTQECopboLIWeW8vz+6i6CiIiIiMhlL2Bs/TPvdAm6LLt6ioiIiIiIXE7U4ldDtG4dXmNnEJJTU73WTqrX2kn1WjupXmsn1WvtpHq9MGrxExERERERqeUU+ImIiIiIiNRyCvxERERERERqOY3xqyGeT0mo7iKIiIiIiFy2xgaEnnmnS5ha/ERERERERGq5y3IBdxERERERqXkmAhbghjJpi088MgAf4Aqg80n5U046jxl4v4LzpwFvA9cCHSujwJcQBX4iIiIiInJJswCzgOVApzLpS4DpwPVAQyAOmIwR5LQ/sc8hIPLEPiVMFVyjGPgZyKvEcl9KakxXz+bNXfjiiyZs2tSWffs6sG5dNO+8E4aPjxG7LloUxZVXep33+YcP92PatBaVVdxzEh/fnqZNnavl2iIiIiIil7JU4FNgKUaLXlnLgG5ADOCP0dIXA6wqs08SUA/wLPPwqOA68078W2MCpHNUI+6rXTt3ZsyIZOfO41x11WYaNlzFkCFbcXMzM2lSBAA9emzk338zz/saU6akMWTI1soq8jkJC1tNXFxutVxbRERERORSthfwA54GfE/KuxboelKaCcgps50E1DnDNRKBf4GbzruUl74aEfi99VYYX36ZxHvvHeDQoXwsFti/P4/HH9/DokVH8fKyIzY2mr59vQGIinJj6tQW7NoVw9KlrRk5MgCAW28NZPbsSJtzT5vWgv/8J5CRIwOYM8fIe/LJEP73v8b89FM48fHtWbw4iiuuKG1NvOuuIBYsiGLXrhi2bGnLk0+GAEarYXx8e+tj//4OJCd3onFjZxYtirLJS0rqyOefNwEgObkTEREuVf0yioiIiIjUODHAjRgtdSdrghEUljgCrAUiTmxnYASB24DXgZeBH4GyzUWFGF08B2C0GtZWl3zgV6+eI1FRbvz8c3K5vNxcC6+9tp/MzCJrmp+fPVOmNGf69DQiItbw0EO7eeWV+vTq5c20aWlERLjSsKETAMHBjrRp4860aWnlzj14sB9ffHGIZs1imTcvg9dfbwhAx44ePPZYMP/9706aNInljjvieOKJeoSFOTFlShphYasJC1tN06axxMZm8f33h9m9O5cePTZa8+64YycZGYW8+25i1bxoIiIiIiKXmWPAeIwAsc+JtKQT/9oBt2EEkMkYXUfzT+RNP3HMyS2Htc0lP7lLUJAjAIcO5VvTnn8+lNtvNxpsHRxMPPlkvDXv6qt9OHAgn6+/PgzA2rXH+PHHZEaO9Gf+/AzmzDnC0KF+jBt3kGuv9WP+/AwyMoo4WWzsMRYvPgrA5Mmp3HdfXQA2bsymT5/NHDqUT0CAA46OJo4fL6ZOHUfi40uHgr71VkPMZhPPPrvX5rzNmrnw+edNuf/+Xezape6dIiIiIiIXKhX4AigAHgRK+tJFAGMA9zL7BmG0/G0DXIHVwFNncY3WrcMrqbRVa8OGHRWmX/KBX2pqAQB16jiQmGgEf2PHJjB2rLGg+Zw5kZjNpfPy+Ps7kJhoOxdPYmIenToZQzgnTUrh+efrnwj8/E/Z6paWVmB9XlhosV6juNjCE0/UY8AAX1JTC9iwIRvApgz33RdEz57eXH31JgoLLdZ0Hx97fvopnI8+OsD8+Rnn9XqIiIiIiEipRIygzwV4hPITwLiftO0FuGF0C90C5GJ0Ay1RDPwGrAPuK5N+qoCqprjkA799+/LYujWHm24K5O23z9w18sCBPEJDbXvn1q/vTEqKEcjNn5/BuHGNuPpqH+rVc2Lu3IxzKs9999UlIsKVDh3Wk5VVhL29iSFDSnsW9+7tzahRIQwZspW0tEJrur29iW+/bcbq1Vl8+umhc7qmiIiIiIiUdxj4H8bYvHsxArqyFmLM1vkSRndPgHSMbqF1gXZA35OOeQPofyKvNrnkx/gBPPHEHu65J4gnnqhHQIADAKGhTrz6agNatnS1tgoC/PNPBgEBDtx5Zx3s7U20bevOLbcEMmVKKgBFRfDHH2m88UZDpk1Lo6DAUuE1T8XDw478/GIKCopxczPz8sv1cXIy4+BgIjzchc8/b8LDD+9my5Ycm+PeeScMR0cTjz++5wJfDRERERERAWNSFgfgFqAIOHricexEfkuMdfl+wQgS9wDfAmFAM4xlHQJOeoDRSuh9MW7gIrrkW/wA1qw5Rt++m3n00WDmzo3Ey8uerKwili49yjXXbLF2twTIzCzihhu2M2ZMA557LpS0tELGjNnPjBlHrPtMmpTKPffU5bffUs65LJ9/fojPPmvC1q0xZGcXMXv2EVauPErTpi4MG+aHq6uZd99txCefmDGd6P35zDPx3HxzIJmZhWze3A57eyMjISGPHj02XtiLIyIiIiJyGUoG9p94/vpJef7ACyf+vR/4C3gfo9UvEhhKxYu412amgIDQc2vykmrxfEpCdRdBREREROSyNTYgtLqLcEFqRFdPEREREREROX8K/ERERERERGo5dfWsIVq3Dq/xU8hKearX2kn1WjupXmsn1WvtpHqtnVSvF0YtfiIiIiIiIrWcAj8REREREZFaToGfiIiIiIhILacxfjVE8uNazkFERERE5FwFvl+zl2GoLGrxExERERERqeXsq7sAIiIiIiJSu937BxQVw1fDS9M+WQafrICEDGjgA493g7val+avPQBPzYLYA+DqANeEw9v9wdfVyM84DqNmwvTtkJ0PPRrC+wMgIvBi3lnNoRY/ERERERGpEhYLvDgXxq+yTf9sBTwzG164EjY+YgR9/zcNflxr5B88Cn2+hjBfWH4//HYTrEqE6yeUnuPWSUZQOO1WiH0AXB2NY44XXLz7q0kU+J2QnNyJt98OK5ceGxtN377elXKNRYuiuPJKr0o5l4iIiIjIpWxPOvT6Cj5bCfW9bfM+XwkPdIJboqGxn9HSd2s0fLvGyJ+4EZzt4fOh0DwQujaETwfDvN2wPwPyCsHHBb4YCp3qG618o3vBgaOwPeWi3maNoa6eZdx2WyB//32E+fMzquT8PXpsrJLzioiIiIhcapbvg0a+8MsNcMMvtnkfDSofDJpNcOS48Xxwc4ipB3Zm23ww9qnvDT9cX5qXmg0fLjXSIwIq+UZqCbX4lfHTT8mMG9cIb2+7CvMDAhz47LMmbNvWjnXronnxxfo4OhrvwI8+aswXXzRhzZpoFixoRbdunixZ0poJE8LZsSOGLl08bVoP7703iLVro9m+vR3TprUgKsrtYt2miIiIiEiVuzkavh4OQR7l83o2MrpxltifAb9sgH7NjO3GftD9pM54by2Cep4QWcc2/dHpEDAGJmwwrufiUKm3UWso8Cvj66+T2LnzOO+806jC/O++M96JMTHr6N9/M126ePLUUyHW/C5dPLnmms0MGrSV4mJo1syFP/9Mp02btaxcedS6X8OGTjzzTCiDB28hImINS5Yc5bXXGlTtzYmIiIiIXIJSjsGA7yDIHZ65ouJ9nvkb/toO/xti2woIcF9HiH0QbmkDQ36ADYequMA1lLp6lmGxwMMP72bhwiiuvdaP339Ps+Y1bOhE+/Ye3HrrDrKzi8nOLuattxL4+OPGjBljrLG3ZMlRDh8uHU1aXGzh999Tyc+3XSoxJ6cYBwcTt95ah+nT03j33UTeeefi3KOIiIiIyKViTzr0/xZyCmDhPeDlbJtfVAwP/glfrILPhsDgFuXPUTKL5/hhsHw/fLocxl9bmt+6dXjV3cAlaMOGHRWmK/A7ycGD+Tz33F7efDOM5cuzrOn+/g5kZxeRnl5oTUtIyCMw0BF7e6O7Z3Jyvs25MjIKywV9xn4F3Hjjdh54IJh77w0iI6OQN99M5NdfNRJVRERERC4P6w4aQZ+PCyy7D0K9bfNzC+D6X+DvnfDT9XBTm9K8o7lG+oAIcHM00sxmaFnHmOClrFMFQpcbdfWswG+/pbJkSSYffdQI04lBpImJebi52eHrWxor16/vTHp6AYWFRnBnOSnGO3m7hJ+fPdnZxdxww3bCw2MZMyaBceMaUaeOOiSLiIiISO23PRn6fAUNvGHJveWDvuJiGDEB5u2C6bfZBn0AuYUw8heYVSamKywy1v5roXX8KqTA7xRGjYqneXNXQkOdAEhKKmDRokzGjm2Im5uZoCAHnn46hClTUs/53CEhTvz2WwStWrmSl2chLa2A3NxicnKKK/s2REREREQuObf9Bs4O8OP1UFAMSVnGIzXbyP9spTGm76NB0LpuaX5SFhQUQaA73NzGWMB9/m7Yehj+OxkycuHRrtV6a5csdfU8hfT0Qh5/fA8//RRhTbv//l2MGdOA1aujAZg8OZWxY/ef87k3bMhmzJgEvvmmGf7+DiQm5nH33XFkZRVVWvlFRERERC5FO1NgdaLxPPx927zGvrDrSfh5vbF91+/lj198L3RrCF8MgxfmGAu5HzkO3RvConugnpbNrpApICD0FB0S5VKS/HhCdRdBRERERKTGCXw/tLqLcElQV08REREREZFaTl09a4i+8/poRqJaqHXrcNVrLaR6rZ1Ur7WT6rV2Ur3WTqrXC6MWPxERERERkVpOgZ+IiIiIiEgtp8BPRERERESkltOsnjVEZsqm6i6CiIiIiMglySugVXUX4ZKnFj8REREREZFaToGfiIiIiIhcsEIepZCHbNKKGE8+7cknmHw6UsQPFR5rIY8CulLExLM+t5ybyyrwc3ExExDgUN3FEBERERGpNSxYKGQsxXxnk17E1xTxCnaMwoGl2PEARTxBEb+edHwWhdyChS1nfW45d5dE4Dd5cnPGjm1QYd7q1W0YOdK/Uq4zbVoL2rRxq5RziYiIiIhc7izspZBBFPMNEGKTV8w3mLkLO0ZiIgw7bsPMSIr5ucw+CyigO5B8TueWc3dJBH4//pjMsGH+2NubbNJ79PDE09OeadPSKuU6vr5q7RMRERERqSzFrMJEQxxYhgnbhhw73sKO/550hBnIKHP8HOy4BXvmnNO55dxdEoHfzJnpWCzQt6+3TfqNNwYycWIKbdq4M3t2JHFxMcyaFUl0dGmrXXJyJ958syE7d8bw8MPBREa6MnNmS+LiYli6tDX3318XgO++a0ZIiCNffdWMu+4KwmSCp58OYenS1uzZ055166K57bZAAEJDnYiPb8/jj9dj584YNm5sy913B1mvGRsbzahR9Vi7Nppdu2J4990wnJyMoNVshieeqEdsbDRbtrRj3LhGuLvbATByZAC//hrBp582ZvfuGFatasOIEZXTmikiIiIicrHZcT32fIKJOuXyzHTDREPrtoUEipmCiT7WNHtex45RmHA6p3PLubskAr+CAguTJqUwcmSANc3T047+/X2YOTOdn38OZ9y4A0RExPK//x1kwoQIvL3trPs6OZlp2XINX3+dxOuvN2T69HSaNo3ljjt28sQT9WjUyJnbb99JYmI+d921k6++SuK66/wZONCXYcO20qjRasaM2c9rrzXEzc14Sdzc7GjRwpU2bdZyyy07ePLJEK680st6zaFD/Rk8eAudO2+gVSs3nnzSaH6+//66DBjgy+DBW+jQYR0uLmbeeKOh9bhevbxZuDCTZs1i+fLLJN54o6E1aBQRERERqY0spFLISCAQOx6t7uJcluyruwAlfvghmYULo/DxsefIkUKuu86ftWuP0b69B0uWHGXWrCMATJ+ezn//W4dBg/z48UejL/DUqWkUFFgoKLBw9GgRfft6s2vXcZYsOUrTprFYKlipcNasIyxcmElycgF16zqSl2fBxcWMt3fpS/LCC3vJySlm48ZsJk5M4dpr/fn330wAPvggkcTEfADGjTvAmDENGTMmgZtuCmTs2P0cPGjkvfbaflavjmbUqD0AJCTkMWlSKgCTJqUwdmxD/P0dOHAgv2peWBERERGRamRhLwVcBxzHgRmY8DrjMeeqdevwSj9nTbVhw44K0y+ZwC8+PpfVq7MYNsyPb745zI03BvDJJ4fo0sWDXr28iYuLse5rb29i5cos63ZycmnQ9PDDu3nuuVDefjsMPz8Hpk5N49ln48nOLra5noODibFjG9KjhxcHDuSxeXMOAGaz0fp2/HgxSUkF1v0PHcqnWTOXMuXNsz4/eDCfwEBj/GC9eo588kkTiopKo82CAgv16hnN12lppecsLLTYXFNEREREpDYpZgOFjAC8cWA2piqapOVUwY6UumQCPzAmebnvvrqsWJFFcLAjM2em07ixM9OmpfHgg7ut+9Wv70R6eqF1u2yLXvPmrowevY9Ro+Jp0cKVL75owh13BPHxxwdtrvX886GYzRAVtYa8PAv16jlyww2lXU1dXMx4edmRmVkEQEiIk02rXFBQ6UQxoaFO1ha+5OQCHn98D0uWHAWMILVBAyf27s2lfXuPSniVREREREQufRZ2UshQTDTCnt8w4VvdRbqsXRJj/ErMmJFOaKgTjzwSzIQJKRQUWPjjjzSuusqH7t09AejQwZ0FC6JsJngp6/XXG/LQQ8HY2UFSUj7FxXDkiBEk5ucX4+FhjA308LAjL6+YwkILPj72vPyyMVNQ2ZlFX3ihPo6OJqKj3Rgxwp9Jk1KseQ89VA9/f3sCAx149NF6TJxo5E2cmMKoUSEEBjpgb2/i2WdD+fXXCExq1BMRERGRy0gh9wHO2PMFUICFwycelTNjv5ybS6rFr2SSl/vvr0uHDusBowvo3XfHMXp0fRo3diYtrZAXX9zH4sVHKzzHfffF8dZbYdxzTwz5+RamTEllwgRjLODEiSm8914jGjRw5q23Evnkk8bExbUnM7OQ335LJT4+l2bNXNi61ej2mZ1dxLp10eTkFPPCC3tZsaK0e+mWLdnMnBmJp6cdv/ySwocfHgDgww8P4uBgYtasSLy87Ni4MZubb95BUVEVvnAiIiIiIpcQC7uwsBaAAmJOyg3DkXUXv1CXOVNAQGgFU59c3kJDnVizJpqwsFXlxgaCsZzDs8/GM3duxkUrU2bKpot2LRERERGRmsQroFV1F+GSd0l19RQREREREZHKp8BPRERERESkllNXzxqidetwTVNbC6leayfVa+2keq2dVK+1k+q1dlK9Xhi1+ImIiIiIiNRyCvxERERERERqOQV+IiIiIiIitZzG+NUQKbfur+4iiIiIiIhcFAE/1i+XpjF+F0YtfiIiIiIiIrWcAj8RERERESlv7r0w567y6dt/ga+blE9PWg0Te8DHHkb+2o/O/dxSZRT4VbH69Z2quwgiIiIiImfPYoGlL8Km8eXz9vwFc+4sn56xByb1BPdguHEFXPkRrH4TVrx29ueWKqXA7ywkJ3ciIsLlnI+7+mofxo9vat1etCiKK6/0AuDaa/3Ytq0dO3fGMHKkP9Omtai08oqIiIiInJeMPfBbL9j4GXiUGWdXcBzm3gN/XgveTcsft+4jcK0D/X4E/5bQ6Bro8Q6sesM49nTnlotCgV8V8va2x1zmFe7RYyP//psJwI03BvDdd4dp1iyWiRNTGTJkazWVUkRERETkhEPLwasR3LYJvMJK048nQ8ZuuHE5NBlW/riMOKjbCewcStMCo6HwOBxeffpzy0WhwO8CRUa6MnlyczZtasveve2ZNCmCgAAH2rRx4513wmjVyo3Nm9sCEBsbTd++3kyaFEG3bl48+GAwP/4YzsiRAcyZE1nNdyIiIiIil73mN8PVX4NbkG26ZwMYMQ/qtKv4OLdgyEqwTcvca/ybk3z6c8tFocDvAn39dTNmzUqnVau1REevw8PDnjvuqMP69dk8+WQ8mzZlExm51uaY66/fzooVWbz00j5uvVVT0oqIiIhIDdfiVji4FNZ+CEX5RuvgstFGXlF+9ZZNALCv7gLUdCNHbmPfvjxcXc0EBzuSnl5A3bqO1V0sEREREZGLJ6QH9P0SFo2ChY+Diz90e8OYCMbJ65xP17p1+DmlS6lTrXWowO8CRUe7M2FCBO7udmzbloOXlz1paYXVXSwRERERkYur1V0QeSdkHwLXQEg7MYeFd+NzPlVFwYsWcL8wCvwuQN26jnzySWMGDdrK2rXHABg3rhFms6maSyYiIiIichHtnAxxk2HAr8aSDgC7phqzd/pGVGvRxKAxfmcpIMCBunUdrQ8/P3vc3IyX7/jxIgB69fJm8GA/HByMwC8/vxh3d7tqK7OIiIiIyEXh1wJ2/QFr3jcmddn0NawaC91er+6SyQlq8TtLU6bYrrO3cuVRBg3ayvvvH2DKlBbY25vYufM4P/xwmG7djH7My5YdBSAuLobIyDUXvcwiIiIiIheFXwsYMAmWPg9Lnje6d171LTS/qbpLJieYAgJCLdVdCDmzlFv3V3cRREREREQuioAfyy/wrjF+F0ZdPUVERERERGo5dfWsIfps7KtfOGoh/XJVO6leayfVa+2keq2dVK8i5anFT0REREREpJZT4CciIiIiIlLLKfATERERERGp5TSrZw2RmbKpuosgIiIiIlJlvAJanTZfYzcvjFr8REREREREajkFfiIiIiIiAkAhj1LIQ+XSi5hMPtHl0ovZSAEDySeEfFpSyItYyDvp2B/Ipx35BFFAT4pZWGXll1NT4CciIiIicpmzYKGQsRTzXbm8Yv6mqIJg0EIGhVyLiWY4sAh7PqaYXylijHWfIiZQxCjseBQHlmGiK4XchIV9VXk7UgGt43dCcnIncnKKsFg48bAQG3uMl17ax/btx6u7eCIiIiIiVcLCXgp5EAvbgJAy6ccp4hmKmYCJZljIOem4FUAqdryCCQ9MNMLMDVj4B3gNCxaKeAMzj2DHrQDYMQYLiyhmFXY0uHg3KWrxK6tfv82Eha2mUaPVhIevYdu2HH75JQKzXiURERERqaWKWYWJhida5MoGYylYiMeeuZgYWMGR/ieO/xoLhVhIwMIcTNYuoXFAAmautR5hwowDS7BjRFXdjpzCGUMaPz97HnusHoMH+1rTHnigLqtXtyE+vj3Tp7egUyePKi1kdSgstPDLLynUq+eEt7fRMDpggA8LF0YRFxfD5MnNadTIGYDQUCd27Yrho48aExcXw3XX+ePsbGLs2AZs2NCWjRvb8vLL9XFwMAGwaFEU8fHtrY+kpI58/nmTartXEREREbl82XE99nyCiTo26Sbq48CfmGlT4XFmYjAziiLGUkAdCmgF+GDHuwBY2HViz0wKGEQ+TSigP8WsrLqbkVM6beAXEuLIggVRPPVUCG3auAPw4IN1GT26PqGhTri4mGnf3oPffmtO27buF6XAF4uXlx133x3E1q05pKcXEh3txrhxjXnyyT00b76GOXOOMGFCOPb2RjDn6WlPQkIeLVuuYcaMdF5+uQFNm7pwxRUbufLKjbRu7c5jj9UDoEePjYSFrSYsbDV33LGTjIxC3n03sTpvV0RERETknFg4DuzBzEjs+Qd7fsRCAkU8diI/C4BC7sfMbdgzGRMtKGQwFrQsw8V22jF+Tz0VSkCAAxkZhWzenI2Dg4kHHgjGYoF1647x6acHue22OvTs6cXDDwdz++07L1a5q8SMGS0pLjae5+cXs2bNMe64w7inm24KZOLEFFatOgbA+PFJ3H13EN26ebJ7dy4Akyenkp9vASzccEMAAwdu4ciRQgDefjuBL75oyttvlwZ4zZq58PnnTbn//l3s2pV78W5UREREROQCFfMxFrZizzJMmIFo7PGkkCEU8yDgAIAdT1i7dppojYXlFPE19rxtc77WrcPPeM2z2edyd6q1Dk8b+HXv7klxMQwevJWdO4/Ts6cXPj72WCzw8sv7WLXqGMuXZ7F5cztiYmp+i9+AAVtOOZFLvXqOdO3qxciRAdY0BwcT9eo5WgO/5OR8APz97XF1tWPq1BZYLMa+JhM4OJhxcjKRl2fBx8een34K56OPDjB/fkaV3peIiIiISGUrJhYTUSeCPoOJmBPP4jFR90RayzL5phMTxZSf1fNMi7NrAfcLc9rALyDAgSNHCtm50wiGrrzSC4DMzEJry1d6eiEZGYV4eNTuCUIPHy7gf/87yFtvlbbYhYU5k5SUj7+/g82+6emF5OUV07v3JvbtM9YxcXU1ExjoQF6eBXt7E99+24zVq7P49NNDF/U+REREREQqg4lgLKy2STNmBgVojImGgBsW1sKJCV8sWLCwAxM9L2ZRhTOM8Tt2rAgPDzscHY1xbP36+WCxwJIlR637BAY64ONjb23tqq0mTkzhllsCadXKFYBrrvFh0aIogoMdy+1bXAxTpqTywgv18fS0w9XVzLvvhvHRR40BeOedMBwdTTz++J6Leg8iIiIiIpXFzB1Y2EkhT2JhN8UsppAHMHE1ZlpgwhUz91PEaxTzJxZ2U8RzWIjHjjuru/iXndM2023YkE2PHl6MG9eIo0eLaNjQGYsFpk9PByAy0pWxYxsCsGlTdpUXtjqtWJHFiy/u49NPmxAS4kRCQh733BPH7t25hIY6ldv/+ef38uKL9Vm8uDUuLmZWrszi7rvjqFfPkZtvDiQzs5DNm9tZJ4dJSMijR4+NF/u2RERERETOi5ko7JlGEa9RwBWAF2YGYMeL1n3seB4TrhTyHJCCiVbY8zsmmlZXsS9bpoCAUMupMrt29WTSpAjMZiM4MZlg8+Yc+vbdRGCgA+vXtwWguNhCv36b2bQp51SnkguUmbKpuosgIiIiIlJlvAJanTZfY/wuzGm7ei5depSbbtrB0qVH2bXrOD/+mMyIEduwWCAlpQCTCeLjcxkxYruCPhERERERkUvUGWdkWbgwk4ULM8ulFxdD27brOHiwdo/tExERERERqenOaipOe3sT7u5mMjKKbNJLgr4WLVx5/fWGDB26tfJLKAD06HOdmrZrIXVZqJ1Ur7WT6rV2Ur3WTqpXkfJO29XT0dHE22+HsWdPe7Zti2HNmmj69vW25ru5mXn99YbMnRtJx44eVV1WEREREREROQ+nbfEbNSqE224LtG7Xq+fI+PFN6dVrI97e9nz9dTPq1nXEZIIjRwqrvLAiIiIiIiJy7k7b4nfNNb5YLPDtt4e57bYd/PNPBs7OZh59tB6TJjUnONgI+qZPT6d79w0Xq8wiIiIiIiJyDk67nMOePe0pLrbQpEksAP7+9mze3A6LxVja4dChfJ5+Op45czIuVnkvWyk39a3uIoiIiIiInJeACXMv+Bwau3lhTtvV09XVzKFDpbN2pqaWduecOzeD++/fxbFjRRUdKiIiIiIiIpeIM87qaamgPTA/38J998WRnV1cFWUSEREREZHKNm+p8eW+Tzfb9B27YflauH1EadqcRbBtV8Xnuao7NG9qrO+2fC1sjYOCAmgQAld0BjeXqrsHOW9ntZzDydLTCxT0AfXrO7F/f151F0NERERE5NQsFlixDjbvgJbNbPP27Id/loCbq216z07QNcY2bd5SyDgKjRsa2yvXwbY4uKoHuDjBv8thxjy4fmCV3Yqcv9NO7gJQt64jhw51tD4sFggKsk07dKgjBw92vBjlvagaNXLm+++bsXNnDHv2tOfff1tx000BAERGujJjRsvzOm+XLp5s29au3HMRERERkUqVeRR+nwWbtoOHW2l6YSHMWwIz5oO3Z/njnByNYLDkcSAJ9iXCNVeCowMUFcH6rdAlBhrUg0B/6H8FHEqGg4cv2u3J2Ttji5/JdDGKcekxmWDixAh++SWFe++NIy/PQqdOHnz3XThHjxaRnl6Ivf1l+uKIiIiISM1wKAU8PaDfFTBrQWl6Ti5kZBmtc/H7YfvuU5+jsBAWr4boSPD3NdJS0iG/AEKCSvfz9ABPdyPwC65TFXcjF+C0gd+wYVsvVjkuOX5+9jRo4MyUKank5hoDHZcvz+LVV/fh5mbm008jcHExEx/fnrZt1/HNN81ISMijd28v1q/P5uabd3D33UHcc08QXl72rF9/jGef3cvu3bnVfGciIiIictmIaGw8TubpDsP7G8/j95/+HJt2QH4+tG9dmnYs2/jXzc12XzdXyMo+//JKlTlt4Ld8edbFKsclJzW1kCVLMvntt+ZMnpzK0qVHWbfuGD//nAJAQkI+X3/dlObN11iPiYpypVMnYz3DW28N5IEH6nLTTTuIizvOI48E8+uvEVrvUERERERqDosFNmyFqOZG988ShYVGFzm7k0aO2dkZ3UDlknPawG/cuEYcOVLIK6+U/grQooUr+fnF7NpV2nL1668R+PnZ07fv5qoraTW48cbt/Oc/dRg40JeHHgoGYMaMdJ59dm+F+8+enUFWlvFGHzHCny++SGLr1hwA3nvvALfeWofOnT3Jyzvl0okiIiIiIpeOg4chMwsiT5oUxs7eCAqLi8FcJvgrKgKH8iFG69bhlVKcyjpPbXaqtQ5PG/jdcEMABw/m2wR+8+e34sCBfNq1W2dNCw93ISjIsaJT1Gh5eRbGj09i/PgknJxMdOzowYsvNmDcuEZ88UVSuf2Tk0vXPPT3dyAhoXTGT4sFDhzIIzjYkfh4zQQqIiIiIjXAnv1Qxx+8TpoApmSimOwc8HAvTc/OKT9DKKcORs6FFnC/MGec1bMil8OEL0OG+LF6dRvrdl6ehUWLjvLBB4lERrpVeEzZNQ8PHMijfn0n67bJBCEhTqSkFFRVkUVEREREKtfBwxAaXD7d39eY3fNAmcaQo1lw9BjUCyq/v1S78wr8LgeLFmXi5mbHmDEN8Pc3GkbDwpz4z3/qMGfOEfLzi3F2NuPgUHEUPHFiKvfcE0Tz5i44OJh44ol6ACxZcvSi3YOIiIiIyHmzWIzZO/18yufZ20GrCGO2z72JkJxqzBpaLwjqBl70osqZndcC7peDI0cKGTRoC88+G8rCha1xczOTmlrI5MkpvPfeARwcTGzffpwdO2Lo3XtjueMnT07Fz8+e778Px9/fgXXrjjFixDZycrTwvYiIiIjUAHn5xpg9F6eK87u0M8b4zV5o/NsgBK7sfHHLKGfNFBAQesqZRpKSOnLwYD5t2647bdq6ddEEBTlSt+7Kqi3tZSzlpr7VXQQRERERkfMSMGHuBZ9DY/wuzBlb/FxczFx/vf9p01xc1GNURERERETkUnXGFj/LWaw8YDIZXYDV4ld19AtH7aR6rZ1Ur7WT6rV2Ur3WTqrX2kn1emFO2+KXmJiP5WwiPxEREREREblknTbwi4lZd7psERERERERqQFOOzhv2bLWPPVUCM2auVys8oiIiIiIiEglO+sxfjt3Hmfq1DSmTk0jPj73YpVPTkh5fn91F0FERERExCpgbP2Lej2N8bswp23x++67wxw6lI/JBOHhLjz1VAjLlrVm7txIHnigLqGhp1jTQ0RERERERC4Zp23xK9GmjRvXXONL//4+NG1qdPssaQlct+4YU6em8eefaSQlFVRpYS9navETERERkXIm3guWIrjhK9v0Nb/ArNHwwi7b9GlPwr/v2qb5Ny7dL+sw/PkU7JgD+cehQUcY+h7UjSx3abX41SxnXMcPYP36bNavz+b11xNo3NiZAQN86dfPh+hod+vjpZfqU6/eqqour4iIiIiIWCww6yVYPh463Wmbt+Uv+PVO8Aouf9yhzdDtAbjqhdI084mQoLgYvh5mnPvOaeDkDn+/DJ/2hme3gptfld2OVL1zXnl99+5cvvjiEP/73yFWrMgCjHX8zGZTpReuunXr5snkyc3ZvTuGnTtjmDatBf36+VR3sURERETkcpa6Bz7tBUs/A58yrW75x2HiPfDNtRDQtOJjkzZDaDvwDCp9uPsbeQc3wN7lcOM30KADBLWAW36E/GOwZUbV35dUqbNq8QNwdTXTt68PAwf60ru3Ny4uRsxoMkFBgYV//82oqjJWi2uv9eONN8J49dV93H77TnJzi7nqKm/eey+M+vWdGD8+qbqLKCIiIiKXo73Lwa8R3PYLfH9DafqxZEjdDY8uh83TYc1Ptscdz4SMRKjTvOLz+tSHu/+CwPDSNJPZaAE8fqTy70MuqtMGfm5uZvr182HQID969vTC2bk02CsqsrB06VGmTk3jr7/SOXq06KIU+GJwdjbx+usNeeKJPfz1V7o1febMI2RmFvHrrxH8/nsq/v4OvPlmGFFRbqSlFfDmmwlMmZKGnR2MGhXCjTcG4ORkZtmyozz33F4OHy5g5MgAhg3zIy2tgH79fEhLK+SddxL57bfUarxjEREREakxYm42HifzbQAPzDOeb55ePv/QZuPfld/CjzcZz5v3hwGvg4uX0ZWz5QDbYxZ9BIW5EH5V5ZVfqsVpA7+tW2NwdDS6cJpMRrC/cmUW06YZk7mkpRVelEJebO3be+Dqasfff5f/ZWPp0qMcPlxA//6+PPpoPSZMSGbEiG20bOnKH3+0YMOGbK6/PoCrrvJm0KCtpKYWMGZMA775phkDBmwBoFcvbx58cBcPP7ybO+4I4o03GvLnn2nk5Z1xnh0RERERkfOTZHwXxc3PGMOXHg9Tn4CkrfDAfOMLf1mb/4S/noUrHoegU7QSSo1x2sDPycmo/LVrjzFtmrGG3+HDtX/mzoAAB44cKaSwsOJALDk5Hx8fe1xdzbz//gEsFmMCnEGDtpCUVMCIEf6MHr2PhIQ8AEaP3kdcXAxNmjgDkJCQx6RJRgvfpEkpjB3bEH9/Bw4cyL84NygiIiIil5/Od0PUtaVj+oJbgXsdGNcJEtcaY/9KrPwOJt4NbW+AQW9XeLrWrcMrTK9K1XHNmuZUM5+eNvAbOzaBqVPTrAHM5SIlpYCAAAccHEwUFJQP/kJDnbBY4PDhAuuyFgCbN+cA4O/vYPOa5eQUc+RIIcHBjgCkpZUGzyXBZW2cHEdERERELiEmU2nQVyK4lfHvkYTSwG/OWJj5AnR/EK79qHxL4AkXe2kFLedwYU4b+B0+nE/nzh507uxxVicracWq6VauzCIjo5Dhw/359dcUm7wrr/TCx8ee2Ngs/u//6lq7wAL897912LAhmwMH8ggNdWLDhmzAGCvp6+tASkoBdetq0XsRERERqQbTRkHcvzBqTWlaQqzxb1AL4995bxtBX/9X4erRF7+MUmVOG/h99FFjmxat07FYak/gl59v4emn43nvvUaYzfDnn+kUFVno3dubt95qyOuvJxAbe4zMzEIeeiiYTz89SFSUG88+G8qAAZuZODGVUaPqsX79MdLSCnn11Qbs2JHDtm3HiYpyr+7bExEREZHLUdS1sHCcsUB753sgbQ9M/j9odzMENoODG2HGc9DxDqNb6NEys9g7eYCTW7UVXS7caQO/xMR8LGcb+dUy06enk5pawKOP1uPllxtgNsOWLTk8+WQ8M2cak77ccssO3nwzjIceCiY1tYDHHttNXFwuH398EGdnM9Ont8TDw46lS49y001qlhYRERGRahTWBe7601iUfcmnRjDX9iYY+LqRv/ZXKC6Cld8Yj7Kuec120XepcUwBAaGXZ2RXw6Q8v7+6iyAiIiIiYhUwtv6Zd6pEGuN3YcyVcZLAQAc++aRxZZxKREREREREKtkZA7+HHgpm9eo27N4dw9SpLYiOLu3bazLB/ffXZdmy1gwf7n+as4iIiIiIiEh1Oe0YvwcfrMvzz4datzt18mDChAh69tyIi4uZr75qSmSkGyaTMSGKVJ0+f/VV03YtpC4LtZPqtXZSvdZOqtfaSfUqUt5pW/yGD/fHYoHZs4/w/PN7Wb8+G29ve+67ry5Tp7awBn1r1x6jb99NF6vMIiIiIiIicg5O2+IXGurE8ePF3HHHToqKjAAwNjaa++831q/Lzi7i9dcT+PrrwxervCIiIiIiInKOThv4ubnZkZSUT1GRsX3wYL41b926bO66aycHDuSf4mgRERERERG5FJw28DOZsFnAvbjY+Lew0MJtt+0gJaWgKssmZbzxzz/VXQSpCv8kVHcJpCqoXmsn1WvtpHqtnVSvVeKagNAz7ySXrPNaziEtrUBBn4iIiIiISA1x2hY/MNboW726jU2av3/5NIsFOnRYX4lFExERERGRsl4HioEXTkqfDXwO/HGaY98ClgJ/lknbDdxQwb5fAm3Ou5RyKTpj4GdvbyI01OmMaRat5iAiIiIiUiUswBcYgd2Qk/IWA68BAac5fjkwGah7UvpuwBv45aR07/Msp1y6Thv4PfLI7otVjiqXnNyJHj02sH378Uo5X2ioE2vWRBMWtors7OJKOaeIiIiIyMkSgTEYQVpQmfRc4D3gLyAMONW33MwTx7cFDp2Ut/vEsf6VWF65NJ028Js4MRUAT087hg71o21bd/z9HbCzM5GWVsDatceYMiWVzMyii1JYEREREZHLzSagHkbw9nyZ9CMYQeE3GK1+s05x/JtAd4wWwWkn5e3BCPyk9jvj5C4jRvizbl00b70VxsiRAfTp482VV3oxfLg/Y8c2ZN26towcWbN/I/D2tuPTTxuzZUs7YmOjeeihYGuek5OJMWMasHVrO7Zvb8eHHzbCyclU7hzNm7vwxx8tiIuLYcGCKHr39rbmxcZG8+67YWzf3o633w7DZIInnqjHhg1tiYuL4fvvm+Hjc8ZetyIiIiJyGeoPjKZ8q1xd4DOg+WmOnQlsBx45Rf5ujFbA/wJXA/8HbLmQwsol67SB3xVXePHRR41xc7Pj+PFili49yh9/pPHHH2ksXpzJ0aNFuLqaGTeuMT16/H979x0eZZW3cfw7k5lMOiG9kwRChxAIZREsCCqKIqKLZUVFlgVfK4gsFkQU14a94rrWVXHN4tpQsAAqiISe0AJJCJCEVEJIT2bePwYmhNA0kDLcn+t6LjPnnOeZc+YI5Den+TRXnU+7V17phM0G/fuvY8yYzVx9dQDXXmufJT19egSJid5ccMFGEhPXExFhYdq0iAb3e3oa+eSTbnz+eSFduyZz//2ZvPZaJ2Jj3RxlIiIs9Omzljlzshg/Pohx4wK56qrN9OixhvJyK48/Ht2cTRYRERERJ5cLPAs8DLgfI78S2AscBO48VDYQ+BuQ0Ux1lOZzwmGm228Pw2CAL78s4q67djZay2Y2G3j88WhuvDGI//u/MJYvP3BGK3smBAWZufBCX7p1swdg5eVVvPpqNuPHB/Pxx/mMGRPAAw9ksm+f/fiK22/f2WjEb8SI9hQU1PD22/sAWLHiAIsWFXHttYE8/rj9HJkvvyyistIG1DFmTABvvpnLzp2VADzwQCaBgebma7SIiIiIODUb8AhwOcffndMN+B5wPXSBPUjcgn0jmOlHlY+P73La6/l7tYY6tHYbNmw7ZvoJA79evTyxWmHatPRjbmBSU2Nj9uxdXHttIPHxnqenps0sPNwVo9HAb7/1caQZjVBcbF+3GBhoJju72pGXk2P/+chdTSMiXOnc2Z20tERHmslk4Kuvihyv8/LqnxEYaHY8B6CoqJaiotrT1ygREREROavlAsnY1wcmHUqrPXSdC7wAJABeR91nBDoC+47xzOMFFM0lPr5Li9ehLTth4Oft7UJxce0JN28pK7NSXFxLQEDbHLHat6+GmhorPXqsobrafiZFu3YueHm5AJCbW01oqCsbN5YBEB/vSWKiF4sX72/wjOTkg4wevdmRFhrqSmVlfbB85HEXOTnVhIS4Ol5HRVn4858DeOaZvWeiiSIiIiJylgkE/ntU2qfAd9jP+wvEPrI35dDrrofK1AHbgQubp5rSjE64xs9ohOrqkx9VUFdnw9B4v5NWJzDQTGioq+Py9zeRnV3Nr7+W8tBDUbi5GfD1deGttzpz//2RACQlFXDXXWEEBprx9nbhoYeiGk3LXLKkmE6d3Bkzxh+jEeLi3Pjmm56MHNn+mPVISipg4sRgoqMtWCwGZsyIaLAeUERERESkKUxA5FGXD+By6Gc3IA77BjGPAynYN3qZA+zn2Ie6S9t20q0k3dyM/PnPJ9610939pJuDtgpJSd0bvF616gCXX76ZyZN38OijHVizJgEXFwPff7+fGTMyAXjuub14eBj5/vtemEwGvviikHnz9jYYsdu/v45rr93CY49F89RTMZSV1fHOO/v48MP8Y9bjo4/yCQw08+mn3fH2dmHp0v1Mn64ltCIiIiLSfEzYp3y+CEzFfg5gPPaD4v1asF5yZhgCAyNtx8vMzR3YYIricR9isE9lDA1ddTrrJkf4On93S1dBRERERM5ilwZGtuj7a41f05xwxG/PnmpspxL5iYiIiIiISKt1wsAvMXFdc9VDTmLm8OH6hsMJ6Zsr56R+dU7qV+ekfnVO6leRxtrG4jwRERERERH5wxT4iYiIiIiIODkFfiIiIiIiIk7uhLt6SuuRf2NWS1dBRERERM5Cge9HtXQVAK3dbCqN+ImIiIiIiDg5BX4iIiIiIq3dkr/B4omN07d+BG91OvG93/8f/DP69z9bnIoCPxERERGR1spmg19mwab5jfPSv4TFt574/sxvYcOrv//Z4nTOmsAvL28QmZn9yciov379NZ7rrw9skfqMGxfI4sU9G/0sIiIiIgLA/nT4zzDY+Bp4H7HOrqYClkyCz68C37jj319RZA8MI8479WeL0zprAj+ASy5JISZmNTExq+nYcTVPP72HefNiiYtza+mqiYiIiIg0lLMS2sXC+E3QLqY+vSIP9u+E61ZCpzHHv//7ydDxCogafurPFqd1VgV+R7JaISmpkNLSOrp08QAgOTmBESN8HWVmz47ixRc7AtCzpwdff92DtLREfvklnilTQh3lHnooik2b+pKa2o+PP+5Khw4WAIxGmDYtnOTkBFJT+/H887F4ebk0XyNFREREpO3qdgNc/BZ4hjRM9+kA13wPwf2Of+/mD2DfWjj36d/3bHFaZ23gZzYbmDQpBLPZwJo1B09a/vHHo/niiyLi4pKZMGE706aFExvrxtChPowe7c+5526kd+81ZGdXM316BABTpoRy2WV+XHFFKgMGrMPd3cg//hF9hlsmIiIiIme10t2w9C645B0we7Z0baSVMLV0BZrTV1/1wGYDV1d7vPvjj/sZO3YLOTnVJ733wIE6RozwZceOCn7++QBxccnYbODt7UJAgIm//CWIr78uYtq0dGyHTka8/vog5s7NIjvb/vxHH81i9eoE7r03/Yy1UURERETOYjYbfHMz9JgA4UNOyyPj47ucluecDq2pLq3V8c46PKsCv8suS2Xr1gqioiy8805nCgtrWbv25KN9AHfeuZP774/kqadi8Pc389lnhcycmcGGDWXceedOJkwIYcaMCHbvruKhh3bx3Xf7CQ935eWXO1FXZ3M8p6bGRni45Uw1UURERETOZqVZsPsH+xq+ja/Z06w1UFcDL3nBmEUQMfR3PbK1HJquA9yb5qwK/A7Lyqpi/Pht/PBDb7KyKnn++WwArFYbrq4GR7n27es/nm7dPHjooV3ce28G3bt78MYbnZgwIYSkpAJ27qzkyis34+lpZMKEEN58M46OHVeTl1fD1Knp/PzzAQBMJgMdOljIzKykf3/v5m20iIiIiDg/r3C4Ja1h2oZXYfsncM1Se76clc7aNX579lQfCuQi6N7dvrnLzp2VXHGFP25uBnr29OCii9o7yj/+eDR33BGGiwvk5lZjtUJxcS19+3rxwQdd6NDBQlmZlZKSWkpKarFaYcGCfO69N4KgIDMmk4GZMyP5+OOuGAzHq5WIiIiISBMYTdC+U8PLza8+3eze0jWUFnJWjvgdtmBBPmPH+vP887FcckkKc+dm8fTTsWzenMjGjWUsWJCPn58ZgMmT03jyyRgmTUqkutpGUlIBH36Yh9UKPXp48MUXPfD2diEtrYJbb7V/y/LCC9mYzQYWLepJu3YubNxYxg03bKOuriVbLSIiIiIiZxtDYGCk7eTFpKXl35jV0lUQERERkbNQ4Put44B3rfFrmrN2qqeIiIiIiMjZQoGfiIiIiIiIkzur1/i1JcM3jtDQthPSlAXnpH51TupX56R+dU7qV5HGNOInIiIiIiLi5BT4iYiIiIiIODkFfiIiIiIiIk5Oa/zaiCVLlrR0FURERETkLBAU1DqOb5DTSyN+IiIiIiIiTk6Bn4iIiIhIK/O3v/2NiRMnNkr/6KOP6NSpU6P0zz//nISEBNzd3YmNjeWpp57CZrM58lNTUzEYDI2un3/++Yy2Q1oPBX4iIiIiIq2EzWZj1qxZzJ8/v1Hel19+ya233toofdWqVYwdO5brrruO1NRUnnnmGR599FFeeuklR5mUlBQCAgLIyclpcA0cOPCMtkdaj2YP/GJj3Xj33c5s355Ienp/fvyxF9dfH3jS+/LyBtG1q3sz1PD3S05OYMQI35auhoiIiIi0Yenp6QwbNozXXnuNqKj6dXYVFRVMmjSJq666iri4uEb37dmzhzvvvJP77ruP2NhYrrrqKoYPH87333/vKJOSkkL37t0JCQlpcJnN5mZpm7S8Zg38DAZYsKArGzaU0bv3Gjp2XM3992fy8MMdGDXKrzmrIiIiIiLSqqxcuZLY2Fg2bdpETEyMIz0vL4+dO3eycuVKxowZ0+i+sWPHMm/ePACsVis//PADy5Yt46KLLnKUSUlJoVu3bme+EdJqNWvg5+9vokMHN5KSCqistGGzwcqVpcyZswuz2YDBANOmhbNhQ1/S0hJ5993OtG9fv/Ho6NH+rFgRT0ZGf155pSNmswGAhQu7M2FCsKPchAnBLFzYHYDp0yN47rlYPvigCxkZ/fn++1707evFRx91JSOjP4sW9SQszBWA9u1NvPZaJ5KTE8jM7M/Spb0YMMDL8dybbw5m9eo+7NyZyKefdqNDB4sjb+jQdvz4Yy8yMvrz7393oV07FwCMRnubkpMTSE3tx/PPx+LlZc8bNy6Qzz/vzqJFPdmypR8xMfXPExEREZGzyw033MBbb71FSEhIg/QOHTrw/fff069fvxPen5+fj8Vi4cILL2TgwIFMmjTJkZeSksKuXbsYNGgQISEhDB8+nN9+++2MtENap2YN/AoKavn55xL+859u3HdfBOec44OHh5F//zufhQsLGT8+iHHjArnqqs306LGG8nIrjz8e7bi/Xz8vRozYxJAhG7jgAl+uuOLURgmvvjqAl17KJi4umZKSWpKSuvHss3vo1i2Zykorf/2r/Q/XrFn2IfUhQ9YTF5fMqlWlPPigPe2CC9oxc2YkkyalEReXzIYNZbz6av3C2qFDfbjmmi0kJKwlKsrCLbfYA9EpU0K57DI/rrgilQED1uHubuQf/6hv04AB3jz+eBYDBqwnI6OqKR+viIiIiJzFPDw8WLVqFZ9++ikbNmzg5ptvBuxTRdPT0ykpKeHpp5/m888/JywsjPPOO48tW7a0bKWl2TT7OX7XXbeVm24KZtQoP+64IwyAr74qYubMTMaMCeDNN3PZubMSgAceyCQwsH7e8bx5eykrs1JWVk1ycilRUW6n9J6rV5eyalUpAKtWlWK1wurVBwH49dcDdOpkXzv4j3/sprzcSm0tREZaKCmpIzTUPhp41VUBLFiQz7p1ZYfqsoe4uPo1h6++mkNBQS0Ay5eXOOp2/fVBzJ2bRXZ2NQCPPprF6tUJ3HtvOgD79tXw008Hfu/HKCIiIiLSgKenJ3379qVv377U1tZy7bXX8tRTTxEeHk5xcTEWiwWLxT7D7J133mHNmjW8+uqrDTaBAYiP79IS1T8lrblurcWGDduOmd7sgV9VlY3583OZPz8Xi8XAwIHezJrVgeefjyUw0ExOTrWjbFFRLUVFtY7XJSX1P9fU2DCZDKf0nvv3199ntTZ8jtVqn44JEBxsZu7caDp3dmfHjkqKi2sxGOzvERhoZvPmcsd95eVWNmwoO+Z71NTY8Pa23xce7srLL3eirs7WID883P6HLi+vvr0iIiIiIr9XcnIyVVVVnHPOOY60Xr16AZCdnU14eDg+Pj4N7jEajfTo0YPdu3c3et7xAoeWFh/fpdXWrS1o1qmeo0f7s3p1H8frqioby5cf4Lnn9tCzpyc5OdWEhLg68qOiLNx7b/hJn1tXZ8PVtT4I9PNrGM8ecYTJCc2fH8eiRcV07bqGUaNS+eKLQkdeTk61Y/QPwNPTyCOPRDnWGR5PXl4N48dvIy4umbi4ZLp1W8MFF2wkM7Pyd9VNRERERORY/vWvfzF58uQG5/b99ttvmM1m4uLiWLNmDT4+Pqxdu9aRX1dXx/r16+nRo0dLVFlaQLMGfsuXl+Dp6cJjj3UgIMAenMXEWLjppmAWLy4mKamAiRODiY62YLEYmDEjgtjYk0/nTE+vZORIP7y8XOjQwcLVVwf8ofp5e7tQXl4HQFycG7ffHuYI7JKSCrjmmgB69vTAxQXuuSecvn29qKk5ceS2YEE+994bQVCQGZPJwMyZkXz8cVcMpzZYKSIiIiJyQrfddhtpaWlMmzaNtLQ0kpKSmD59OlOnTsXX15f4+Hiio6OZNGkSq1atIjU1lVtuuYWCggLuuuuulq6+NJNmDfyKi2u5/PJUQkJcWbYsnszM/vznP91Zu/Ygs2bt4qOP8vnww3w+/bQ7Gzf2w2Qy8Pe/Z570uS++uJfaWhsbNiTw1ludWbCg4A/Vb9q0DP7v/8LYuTORt9/uwoIF+fj7m2jf3sTPPx9gzpws3nwzjm3bEune3YO//W3HSZ/5wgvZ/PrrARYt6snWrf1ISPDkhhu2UVf3h6ooIiIiItJAz549+fbbb1m5ciXx8fFMnTqVadOm8Y9//AMAk8nEokWL6NKlC5dffjkDBgwgNzeX5cuXExQU1MK1l+ZiCAyM1GTDNiAvL6ulqyAiIiIiZ4GgoKiTF2oBWuPXNM064iciIiIiIiLNr9l39ZQ/ZsSIEfqGwwnpmyvnpH51TupX56R+dU7qV5HGNOInIiIiIiLi5BT4iYiIiIiIODkFfiIiIiIiIk5Ou3q2Efnfv9PSVRARERERJxd44c0tXYXj0trNptGIn4iIiIiIiJNT4CciIiIi0trMeRYefqZx+tc/wGU3Nk7/cQX8+W/QfySM/Av862OwHWdi34bNkDACVq8/rVWW1k2BXxP4+rrg5eXieB0VZWnB2oiIiIhIm2ezwStvw6dfNc5bthJmHyMY3LgFps2GSy6AhW/BtL/B/A/gw4WNy5ZXwANPQJ31tFddWrezOvDLyxtEZmZ/MjLs19q1Cdx1V9gp379yZR8iIlwB6NnTg6++6nGmqioiIiIizm5PNkycBp98AaFB9emVVfDIs3DPbIgKb3zfvny4fgxMuBYiwmD4UBjUF1ata1z2mdcgOOCMNUFar7M68AO45JIUYmJWExOzmhtu2Mrf/hbKpZe2P6V7/f3Njp99fEyYTIYzVU0RERERcXYbNkNEKCT9E8JD69OL9sPubPjgJRg2pPF9I86Fe6fYf7Za7QFf8kYY3K9huZ9WwfJVMOP2M9YEab3O+sDvSFu2VLB6dSm9enk60v761xBWr+7D9u2JfPJJVzp2dANgyZKeAHzzTU+uuMKPjz7qir+/mYyM/rRvbyIqysJ773Vm3boEdu0awFdf9aBTJ/u94eGuJCV1Iy0tkd9+68OsWVHN31gRERERaV0uGw6PTIcAv4bpYcHwz2ege+cT31+0HxIvgb/eC726wthR9XnFJTB7HsyeBj7ep73q0vop8DtCz54e9O3rxfff7wfgxhuD+L//C+Wmm7bTo8cafvutlI8/7oqbm4ERI1IA+4jh558Xcd11WyksrCEmZjXFxbU8+2wsO3ZUkpi4jm7dkikoqOGee+xD8/ffH8mWLeV07pzM6NGbGTPGn3PP9WmpZouIiIiIM3CzwAcvw7yHYXs6PPRUfd6c5+C8QTBkQMvVT1qUqaUr0NK++qoHViuYzQY8PFz4/vv9bN5cDsA11wTwxhu5jtfz5u3lxhuD+dOffPjxx5ITPvfOO3dSVFSDyWQgIsJCcXEtkZH2zV8OHKhj8GAfRo3yY9myEvr2XXfcTZdERERERE6Jh7t9VLB7Z6irg/seg3v+Cr+uha07IOnNkz4iPr5LM1T0j2vt9WsNjnfW4Vkf+F12WSpbt1YAEBRk5vnnY3n99U6MH7+dgAAzu3dXOcrabLB3bxVhYa4nfW5cnDuzZnUhJMSVbdvKsdnAaLSvAZwzJ4v77ovgwQejeOMNC999V8y0aRnk59ecmUaKiIiIiPNK3QbVNZDQsz4tLsb+3/xC+Pxb+wYwF1xtTzs84HDbTLjiInjoHsdtrfmAdB3g3jSa6nmEvLwa3n57H+ee2w6wB3lHHtFgMEBEhOWkAZrZbODttzvz3HN76dFjDVddtYUVKw448rt39+Cll7IZOHA9gwevx9vbxH33RZyZRomIiIiIc1v4DTz6fMNz+1K2gskEURHw+Ez47F/wn/n26/Un7GVmT4Pbbm6JGksLUOB3BB8fF66/Pojk5IMALFhQwKRJIXTr5o7ZbGDaNPsavZ9/tgdxVVVWvL3t5/hVV1txczNiNhtwdTXg5makvNx+Pkq/fl7cdFMwZrN9xO+ee8J56KEoLBYD+fk11NXZKCqqbe7mioiIiIgzGHcFZO2xH9Wwaw8sWQ7PzofxV4OPFwQH2o+BOHyFhdjvCwoA/1PbzV7avrN+quc33/TEZrN/QVJdbeWnnw5w2207APj00wL8/U28+24XAgLMrFt3kGuu2eII6D7+OJ///KcbM2Zk8MUXRWzdWsG2bYlceOFGpk9P57nnYvH0NJKZWcV77+3jlltCcHGB++7LYN68WDZtsm+xu3hxMS+8sLfFPgMRERERacPiYuD1J+H5N+E/X0L7djD+Gvu5fiKHGAIDI7WtSBuQ//07LV0FEREREXFygRfe3NJVOC6t8WsaTfUUERERERFxcgr8REREREREnNxZv8avrRg+9R8a2nZCmrLgnNSvzkn96pzUr85J/SrSmEb8REREREREnJwCPxERERERESenwE9ERERERMTJ6TiHNiJo+IiWroKIiIiIOJm875a0dBVOmdZuNo1G/ERERERERJycdvUUEREREWlB2b/9gs1mI3zgkAbpJZk7ydu0lrjLr2mQfjB3L3kb11JVUoyLqwWfqBiCevXFaKr/1b545zYKtmyiprwMi48vwX364xUS1iztkdZJI34iIiIiIi3AZrORt3EtxTsbT18s3ZvF3t9+bpReWVxI1rIleIaEEXvJaMIGnMOBrAxy1qx0lNmfnkZO8koCuvWm48gxeAaFsPun76g+WHpG2yOtmwK/Y+jWzZ033ujEpk192bVrAOvWJfD00zG0b//HB0gjIy3k5Q3C01MfuYiIiMjZrvrgATJ/WETRjq2YPTwd6dbaWrJ/+5ndP/+Aq7dPo/uK09Nw8/UjuHc/LN7t8AqNIKh3P0oyd2KzWu3BZMo6Arr1pn3Hzli8fQhOGICrlw/lBXnN2URpZRSFHKVfPy+++qon27dXcNFFKURH/8bo0Zvx9DTyySddW7p6IiIiIuIEygvycfXypuPIKzF7eTvSa6sqqT5YSsyIUfhEdGh0X/uOXQhNHNww0WDAZrVira2hurSEmrKD+HSIOSLbQMeRV+Ib3fGMtUdaPwV+R3nyyRjefDOXefP2kpNTjc0GWVlVTJ2azvLlB2jXzoWePT349NNubNrUl8zM/nzySVcCA80A9Ozpwddf9yAtLZFffolnypTQRu/xwguxPPNM/R9GoxFSU/uSkODZqKyIiIiIOB/f6I6EDxyK2d2jQbqrpxfRw0bi7hdwzPvcfNvj7l+fZ7NaKdyagrt/IC6uFqoOHADAWl1N5veL2PrfD8n47ivK8/educZIm6DA7wjh4a707u3Jv//deBi8stLGo49mUVJSx1tvdWbRoiJ69VpLQsI6vL1NTJgQDMDjj0fzxRdFxMUlM2HCdqZNCyc21q3Bsz79tIDLLvPDxcX++rzz2lFaWse6dWVnvI0iIiIi4hxsVit7f11OVcl+Qvv9CQBrTTUAe39djm/HznQ4/yIs7dqT+cM3VJXsb8HaSkvTrp5HCAlxBSAnp9qR9sADkdx8sz2oM5sNTJ+ewbhxW9i1qwoPDyNhYa4UFdUQGmq/98CBOkaM8GXHjgp+/vkAcXHJ2Gz2NX6H/fzzAaqrbZx7bjt+/LGEMWMCSEoqbMaWioiIiEhbZq2tZc+KpRzM2UvkkAsco4AGo31cJ6BHvGNqp1t7f8rz91G0Yyuh/QY1eE58fJfmrXgTtbX6toTjnXWowO8IBQU1AAQHm9mzxx78zZ27m7lzdwOweHFPjEYDCQlefPhhV7y8XNiypZx27UwUFtYCcOedO7n//kieeioGf38zn31WyMyZGQ3ex2aDhQsLuPJKf1asOMDIke25+OKUZmypiIiIiLRVtVWVZC1bQlXJfqLOG9HgmAaTh33qqFs7P0eawWDA4tPumLt6tqUD0XWAe9NoqucRdu2qYvPmcq6/Pui4ZcLCXHn55Y7cfvtOevdey7hxW9m6tdyR362bBw89tIuEhHVcckkKCQmeTJgQ0ug5n35awCWX+HHhhb7s3FlJenrlGWmTiIiIiDgPa20tu5Z+S/XBUqIvHNnobD739gEYTSYqivIdaTabjaoD+3E9YhMZOfso8DvKtGnpTJoUwrRp4Y4NWyIjLcyZ04EePTzYv98+sldRUQfAsGG+XHGFP2azAbCv8bvjjjBcXCA3txqrFYqLaxu9T0pKOfv2VXPvvREkJRU0U+tEREREpC3L27SWyuIiwgcNxeTuQU1FueOy2WwYTSb8uvQgb+MaDuzOpKq0hNx1v1F9sBS/uG4tXX1pQZrqeZQ1aw4yYkQKd98dxpIlPWnXzkRpaR2//HKASy9NZcOGMvz8TCQldcdkMrB9ewXvvbePIUPaATB5chpPPhnDpEmJVFfbSEoq4MMP8wgPtzR6r6SkAmbMiOR//9P6PhERERE5uZJdO8FmI2vZkkZ5nUePw+zhSVCvvhhdTOSuXUVtZSVu7f3ocP7FWHzatUCNpbUwBAZG2lq6EmersWP9ueaaQK69dutJywYNH9EMNRIRERGRs0ned40DyNZKa/yaRlM9W4C3tws9enhw221hfPBB46MjRERERERETidN9WwBHTu6sXBhd775ppgvvyw6pXtC87P0DYcT0jdXzkn96pzUr85J/eqc1K8ijSnwawHr15cRE7O6pashIiIiIiJnCU31FBERERERcXIK/ERERERERJycdvVsI7Srp4iIiIhza0s7bLYErd1sGo34iYiIiIiIODlt7iIiIiIicoTs337BZrMRPnCII+1gzl72rV9NVWkJrl4+BPdJxDssEoC8TWvJT1l/zGcF9kogqGcCNquV/NT17E9Po666Crf2/gTHJ+IRGNwcTRJR4CciIiIiAmCz2cjftI7indvwje3sSK8sKSZr+XcE9ozHJzKa/Zk72f3T98ReMhq3du3x79qL9p26NnhWfsp6DuzOpP2h5xRs3kjxjm2EDzoXs5c3hVs3sWvZYjpdNhazu0eztlPOTk4z1fOjj7qSkdGfjIz+ZGcPZM+eAY7XTz8d02L1GjHCl+TkhBZ7fxERERE5ueqDB8j8YRFFO7Zi9vBskFe0bTPuAYEE9uiDxceX4N79cA8IomhbKgAuZjNmdw/HVVN2kOKdh4K8Q886sHcX7TrE4hUajsXbh5CEgVhraqgoyGv2tsrZyWlG/K67bqvj57feimPr1gqefnpPC9ZIRERERNqK8oJ8XL28iRh8PntWLG2Yl78Pn6joBmmeQaGUZKU3eo7NZiN3za/4RHTAOyzCkW6yuFGavRu/zt0xe3hStGMrBqMRi6/fmWiOSCNOM+J3POee68PSpb1IS0tk6dLeXH11AACDB/uwZUu/BmW3bOnH4ME+AOTlDWLixBDWrElg27ZEXn21I2azAYDAQDOvvdaJLVv6sW5dArNmReHqas+zWAzMmxfDjh2JrF7dhyFDfBq8x8SJISxd2psdOxJJTe3L9OkRiIiIiEjL8o3uSPjAocecdllTXobJveEooMndg9ryskZlS/dmUVFcSFB8YoP0kISBGAxG0r74D5s/eZe8DclEnHMBFm+fRs8QOROcPvB74YWOPPPMXuLiknnwwUyeeioGLy+XU7p36FAfzj13AyNHpnD++b6MGmX/Ruadd+xztRMT1zFyZAqDB/tw3332AO7vf4+ka1cPBgxYzxVXbOa889o5njdwoDf33BPGLbdsp1OnZCZMSGPatHBiYiynudUiIiIicrpY62oxujT8/dHoYsRaV9eobOG2VHwioxsFdNVlpRhcXIg453xiL7qc9h27sPfX5VQWF57Ruosc5jRTPY/nwIE6rrrKn/37a1m1qpSOHVdjO8WTC+fPz6WszEp6eiWrV5cSG+tGdLSF/v29ufHGbZSVWSkrs/Lkk7t56aWOPPbYbkaP9mfmzEyKimoBeOmlbGbOjAJg48Yyhg9PISenmsBAM66uBioqrAQHu5KRUXWmPgIRERERaQKjiws2a8Mgz1pnxWhq+Kt0TXkZ5Xm5RA8b2SC9rqaGPSuWEdZ/MO2iYgFw9wugcn8xeSnriRp6IWA/p05OTJ/RyR3vrEOnD/zGj9/GjBkRvPFGHO7uRt5/fx+PPrr7lO4tLKxx/Fxba8NoNBAQYKasrM4R2AHs3l1FUJArJpOBoCAzOTnVDfIOs1ptTJsWzmWX+VFQUMOGDfbpAUajoanNFBEREZEzxOzhRU1FRYO02opyzEdN/zywZxcmd3c8gkIapFcf2I+1pho3v4AG6e7+ARzM3et4rcPJT0wHuDeNUwd+rq4GoqPduO22nQAkJnrx7rudWbeujJycase6PACTyYC398mngO7ZU4Wnpwt+fiZH8BcV5UZRUQ21tTZyc2uIjHRl40Z7UBcS4uq4d/LkUMc00NLSOkwmA6NH+5/OJouIiIjIaeYRGER5Xg7Qx5FWlpeDR1DDM/jK8/fhERiCwdDwS33ToZ09q/YXNZgCWlVSjMW7HSLNwanX+Nls8MYbnbjhhkAAcnOrsdmguLiWjIxKPDxcuPTS9ri4wB13hGEynXzkLTe3huXLS5g7NxpPTyMhIWZmzIggKakAgP/8J5+pUyMIDjYTFGTmzjvDHfd6e7tQXW2lpsaKp6eR2bOjsFiMjk1jRERERKT18evcnfL8feRtWkvVgf3kbVxLRWE+/p17NChXWVyI2zF26TS7e+ATGU3u2lWUZu+hqvQAeZvWcTA3G/9uvZqrGXKWc+rAr6bGxoQJadxySwjp6f35+uuevPlmLsuWlZCXV8OcOVk89lg0mzcn4u3twqZNjXdmOpYpU3ZgNMLq1Qn88ENvVq0qZc6cLADmzdvLypUH+OmneBYv7smyZSWO+15/PYe6OhubNyfy6699cHMzsmrVAeLi3M9I+0VERESk6dx8/YgcciEHsjLZueh/lO7NIurc4Vja+TYoV1tRgYvl2Jv2hQ8aik9ULDnJK0j/5jMO5u4l+oJL8PAPbIYWiIAhMDDyFLc6kZYUNHxES1dBRERERM6gvO+WtHQVWjWt8Wsapx7xExEREREREQV+IiIiIiIiTs+pd/V0JqH5WRradkKasuCc1K/OSf3qnNSvzkn9KtKYRvxEREREREScnAI/ERERERERJ6fAT0RERERExMnpOIc24oH83S1dBRERERH5A+YGRrZ0FZyC1m42jUb8REREREREnJx29RQRERGRs8ICwAZce0TaVuBzIB8IAC4Huh+RXwt8CawBqoGOwFjA/xjPXwKkAbed7oqLnAYa8RMRERERp2YDvgZWHpWeC/wT6APcC/QC3gJyjijzCbAeuBG4G6g5dM/Ra6VWHHoPkdaqVQd+eXmDyMzsT0ZG/fXrr/Fcf33gKd3/9NMxzJxpn1O9cGF3JkwIblRm8GAftmzpd9xnLF/emwsuaMddd4Xxyisd/1hDRERERKRFFACvAL8A7Y/KWwZ0AC4CgoFLgRhg+RH3/gZcD3QGQoGrgcpDeQAHgX8BnwGn9huqSMto9VM9L7kkha1bKwAwGmHMGH9efrkTq1eXkpZWecJ7p0/PaPL7n3vuRgB+/LGkyc8SERERkeaViX1a5njg3aPy0rGP9h2pE7D20M/bAC/sQd9hwcDDR7zed+i/04HFgH5jlNaqVY/4Hc1qhaSkQkpL6+jSxQOAnj09+PTTbmza1JfMzP588klXAgPNALz4Ykdmz45q9JyxY/1JTe1Hjx4eDdK9vFz49tuezJsXA0BgoJnXXuvEli39WLcugVmzonB1NTiePXduBz7/vDsZGf1ZvLgnvXrVP++yy9qzbFlv0tIS+fTTbsTGugEQGWkhLS2RO+4IIyWlL6mp/Zgzp8Pp/7BEREREhETgOsDnGHn7Ad+j0todSgfIwx40rgGeAmYBbx+RD/Y1fxPQaJ+0fm0q8DObDUyaFILZbGDNmoMAvPVWZxYtKqJXr7UkJKzD29t0zCmdh116aXvmzOnAuHFbSE0td6S7uxv597+7kJpazrRp9pHCd96xf7+TmLiOkSNTGDzYh/vui3Dcc801gcycmUm3bslkZFTy4IP2IDMhwZPnn+/I9OnpdOu2hsWLi/nwwy6YTPagsV07E1FRFvr2Xcf48du45ZZgEhO9Tu+HJSIiIiInVEPj6W8u2Dd0AajCPqL3I3AlcDNQin3qaE2z1FDk9Gn1Uz2/+qoHNhu4utpj1B9/3M/YsVvIyakGYNy4LezaVYWHh5GwMFeKimoIDXU95rPOPbcdF17oy3XXbSUlpT7oc3Ex8M47nbFaYerUdACioy307+/NjTduo6zMSlmZlSef3M1LL3XkscfsZ+p9+22xI3j83/8KeeQR+8jd9dcHsWBBPr/9Zg9O58/P5a9/DWHIEB927rRPT33ppWyqq22sWXOQHTsqiI11Izn54On++ERERETkOMzUB3mH1QGHf5M0Yl/Pdwv1u3jegn3kbzMQf4rvEx/fpWkVFQd9lid3vLMOW33gd9llqWzdWkFUlIV33ulMYWEta9fWB0gJCV58+GFXvLxc2LKlnHbtTBQWHv1H2O6cc3xISSln7NgAfv75gCPd19eE0Qh9+ngSG+tGenolAQFmysrqKCqqf9bu3VUEBbk6Ru4KC+u/66mpsWEw2NPDw10555x2jBtXP+hvNhsID3d1BH7Hu1dEREREmocvcOCotBLs0z0P57vS8OgGb8ATKPod76NDx08PHeDeNG1mqmdWVhXjx29j1Cg/7r47DIDQUFdefrkjt9++k9691zJu3Fa2bi0/7jPmzdvD5MlpjBnjz9Ch9TO99++v5c9/3kpSUgHPPhsLwJ49VXh6uuDnVx8bR0W5UVRUQ23t0Rv4NrRvXw2vvppNXFyy47rggk3897+FTfkIREREROQ0igV2HpWWhn3d3uH8auzHPhx2ACjj2Of4ibRmbSbwA9izp5qHHtrFvfdG0L27B56e9upXVNQBMGyYL1dc4Y/ZfOzRs+pqG7t2VfHcc3uZNy8Wd3f7/XV1Nmw2ePTRLOLi3Bg/Pojc3BqWLy9h7txoPD2NhISYmTEjgqSkgmM++0gLFuTzl78EOTZ7ufTS9ixf3puwsGNPQRURERGR5jcUe+C3CPtavq+BLODcQ/kdsQd/7wMZQPahnwNpeMi7SFvQpgI/sAdVK1Yc4PnnY0lPr+TZZ/eSlNSd7dsTmTo1nPfe20dcnPsJn/HKKzlUVlr5+98jGqSXlNQxa9YuZs2KIiTEzJQpOzAaYfXqBH74oTerVpUyZ07WSev466+lzJq1i1de6UR6en9mzIhk0qQ0xzRPEREREWl5Ydh35NwAPA2kABOBkEP5hkOvI4E3gRcAN+A22sB6KZGjGAIDI088b1FahQfyd7d0FURERETkD5gbGNnSVXAKWuPXNG1uxE9ERERERER+H41StxFfDh+ubzickL65ck7qV+ekfnVO6lfnpH4VaUwjfiIiIiIiIk5OgZ+IiIiIiIiTU+AnIiIiIiLi5LTGr41YsmRJS1dBREREpM0KCopq6SqItCiN+ImIiIiIiDg5BX4iIiIi0iz+9re/MXHixAZpixcvpk+fPri7u9O7d28WLVrUID8vL48///nP+Pr6EhQUxIwZM6itrXXk19bWMnv2bDp06IC3tzdDhw5lxYoVzdIekbZEgZ+IiIiInFE2m41Zs2Yxf/78BumbN2/miiuu4JprrmHdunWMHj2aK6+8ktTUVEeZsWPHkpuby7Jly3jnnXd4++23efjhhx35TzzxBG+88QZvvvkm69ato0ePHowcOZKcnJxma59IW2AIDIy0tXQlTpe8vEGUl9fRo8caysqsjnSTycCmTX0pK7OSmLiuReqWkdGfiy7aRFpa5R+6Py8v6zTXSEREROTMS09P59ZbbyUlJQUPDw9GjBjBP//5T8A+Arht2zaWLl3qKH/BBRcQFxfH/PnzWblyJYMHDyY9PZ2YmBgA3n33Xe644w7y8/OxWCwkJiZy3nnnMW/ePADKy8vx9PQkKSmJq666yvFcrfFr+3Q+Y9M43YhfRYWVkSP9GqQNG9YOV1dDC9XILiZm9R8O+kRERETaqpUrVxIbG8umTZscwdthP/30E+eff36DtPPPP5+ffvrJkd+hQ4cG951//vmUlpayfv16AAIDA/nyyy/JyMigrq6ON954A1dXV3r37n1G2yXS1jhd4Pfll0WMGePfIG3s2AC++qq4QdrEiSEsXdqbHTsSSU3ty/TpEYfK+pOR0d9xZWUNIC9vEB07ugFw883B/PprPFu39uOddzoTFGQGYPBgH5Yv782TT0aTnt6f1av7cOWV9fXIyxtE167uREZaSEtL5I47wkhJ6Utqaj/mzOlwJj8SERERkRZzww038NZbbxESEtIob8+ePYSHhzdICwsLY/fu3SfMBxxlnn32WUwmE7GxsVgsFmbMmMGCBQvo1KnTmWiOSJvldIHfZ58Vcs45PrRvbz+pwtPTyJ/+5MPixfWB38CB3txzTxi33LKdTp2SmTAhjWnTwomJsZCUVEhMzGpiYlYTF5dMcnIp7767j507K7n8cj/uvDOMm27aTnz8WnbtqmT+/DjHc7t29aC62kbXrslMn57Biy92pEsX90Z1bNfORFSUhb591zF+/DZuuSWYxESvM//hiIiIiLQi5eXluLm5NUizWCxUVlYeN99sNmMwGBxlMjIysFgsLFiwgFWrVjFp0iRuuukmNmzY0DyNEGkjnO4cv8LCGlauLGXUKD/efz+PUaP8WLKkmKqq+jV/GzeWMXx4Cjk51QQGmnF1NVBRYSU42JWMjCpHuSefjMZoNDBzZiYAN9wQxBtv5LBtWwUAjz22m507+xMba/8L6eDBOh57LIvqahtLl5bw44/7GT3an6ee2tOoni+9lE11tY01aw6yY0cFsbFuJCcfPIOfjIiIiEjr4u7uTlVVVYO0qqoqPD09j5tfU1ODzWbD09OTgwcPcv311/P666/z5z//GYB+/fqxadMm5syZQ1JSkuO++PguZ7g10hzUjyd3vHWQThf4Afz3vwVcd10g77+fx9ixATz33F68vFwc+VarjWnTwrnsMj8KCmrYsKEMAKOxfh3g5MkhnHeeLxdfvInaWvv+N+Hhrvz975Hce2+Eo5zNBpGRFmpqbGRnV1NVVb9XTnZ2tWMq6NEKC2scP9fU2DAYWnYNooiIiEhzi4yMbLT7ZnZ2tmN6Z2RkJF9//XWjfIDw8HC2bNlCSUkJiYmJDcoMGDCAxYsXN0jTpiBtnzZ3aRqnm+oJ8PXXRfTp40WvXh5ER7uxcmVpg/zJk0Pp2tWDAQPWM3ToRu6+Ox2TqT7wuvBCX+69N4KbbtpGYWH9OTH79tVw//2ZxMUlO67hwzeyYsUBAAIDzRiP+EQjIizs3Vt9ZhsrIiIi0kYNGTKEZcuWNUj78ccfOffccx356enpjvV8h/O9vb3p06cPERH2L+M3btzY4BkpKSnExcUhIvWcMvArK7OyZEkxr7zSic8+K2yU7+3tQnW1lZoaK56eRmbPjsJiMWI2G+jSxZ3XX+/EnXfuJDW1vMF9n3ySz5QpocTEWDAY4NZbg1m0qCceHvaPsX17E3feGYbJZGDYMF+GDPHhs88KmqXNIiIiIm3NHXfcwfLly3n44YfZunUrs2bNYtWqVdx1110A/OlPf2LQoEGMGzeOtWvXsmjRImbMmMHUqVNxdXUlNDSUa665hrvvvptvvvmGHTt28Mgjj7BkyRLuu+++Fm6dSOvilFM9AZKSCvjgg65MnJjWKO/113N47bVObN6cSFlZHd9+W8yqVQeIi3NnzBh/PDyMPPNMLC+/bOTwDMx7703nk08K8PU18dFHXQkMNJOWVskNN2yjpKQOgP37awkLs5CS0pf8/BomTkxrsGZQREREROr16tWLhQsXct999/Hkk0/StWtXvvjiC7p16waAwWBg4cKFTJkyhaFDh+Lt7c2tt97KrFmzHM94++23eeSRR5gyZQoFBQX06tWL7777jgEDBrRUs0RaJac6wL0lDR7sw1tvxdGt25oz8nwd4C4iIiLyx+kA97ZPa/yaximneoqIiIiIiEg9BX4iIiIiIiJOzmnX+DW3FSsOnLFpngAjRozQ0LYT0pQF56R+dU7qV+ekfnVO6leRxjTiJyIiIiIi4uQU+ImIiIiIiDg5BX4iIiIiIiJOTmv82ohR333HqJauRCs3NzCypasgIiIiItIqacRPRERERETEyWnET86YJUAacNtR6WuB74ACwAcYBAyj/luIXOAzIAP7/6DxwOWA+xmvsYiIiIiIc9KIn5wRK4Cvj5G+GfgA+BNwHzAK+B57kAhQBbwKeABTgYlAOvDRGa6viIiIiIgzOysDv7y8QXTtWj9+ZDYbePfdzixb1pvgYPMJ7x082IctW/odNz8joz9xcW6nra5tzUHgX9hH7AKPkb8C6A0MBQKAPsD5wG+H8ouAWGAcEAzEYA8St5+5KouIiIiIOL2zfqqnm5uBd97pQrt2JkaPTmX//romPS8mZvVpqlnbtO/Qf6cDi4GSo/IvAlyPSjMA5Yd+DgVuPiIvD0gGupzWWoqIiIiInF3OyhG/wzw8jPz7310xmQxcffVmR9A3fXoEb70V5yjXtas7eXmDHK+NRgMPPxxFamo/fv45nlGj/Bx5R44m/ulP3nz7bU8yMvqzfHlvzj+/HQDt25t47bVOJCcnkJnZn6VLezFggFdzNPmM6whM4NijfQBRQMgRryuBX4Cuxyj7FPA49lHEMaexjiIiIiIiZ5uzNvDz9nZhwYKu+Pi4cP31Wykrs57yve3b2wdKExLW8sADmbz6aic6dWo4vTMgwMQHH3Th7bf30bHjah57LIu33+6Mj48Ls2ZFATBkyHri4pJZtaqUBx+MOn2NayOqgbeAGuybtxztOuAOoB3w8qHyIiIiIiLy+521Uz3feCOOtLQK+vTxok8fT3777eAp33vwYB2PP76bmhoby5aV8OOP+7niCn+efXavo8zw4e3JzKzi44/zAVi8eD9XXbWZ6mor//jHbsrLrdTWQmSkhZKSOkJDj54A6dwOAv/EvoPnbYDfMcocPpXvFmA2sAk4/upKiI9vmxNC22q95cTUr85J/eqc1K/OSf3qnNSvJ7dhw7Zjpp+1gd833xRz//2ZPPBAJPPnx3HhhZsoLKw9pXv37aumpsbmeJ2dXd1oU5jAQDPZ2Q3HqNatKwMgLs7M3LnRdO7szo4dlRQX12IwGJrYorajEHgd+w6edwJhR+VlA72OSGsHeNJ4veDRjvc/eWsWH9+lTdZbTkz96pzUr85J/eqc1K/OSf3aNGftVM/33rNvQ/LEE7vJzq7mtdc6cTj2qquzYTbXB2KHp3Ye5u9vxnjEJxcRYWHPnoZBXm5udaNRvLvvDiM21o358+NYtKiYrl3XMGpUKl98UXgaW9a6lQKvADbgLhoGfQBZwNuHyh1WiH2EMLg5KigiIiIi4oTO2sDvsLo6mDx5B337ejFtWjgAO3dWMnCgD9HRFry8XJg8ObTBPb6+JqZODcfV1cCIEb6cc44P//1vQYMy3323n8hIC1dfHYDRCBdd5MuUKWEUF9fi7e1Cebl9I5m4ODduvz2sQaDpzD4FyoDxgBk4cOg6HOj1APyB97GP/GVgDwSjgW7NXFcREREREWdx1k71PFJWVhXTp2fw6qud+O23Ur7+uogLL/Tlm296cvCglRde2MvIkfWr0NLTKwgNdWXr1kSysqq4+eZt7N3bcMSvuLiWG27Yypw5HXjiiWiysqq46aZtFBfXMm1aBo8+2oFZs6LIyanho4/ymDkzkvbtTRQXn9p007aoGtiIfbTv2aPyjIfSXIHJ2M8BfAn7UQ+9gCvRtxQiIiIiIn+UITAw0nbyYtLSHsjf3dJVaPXmBkaevFAro7nqzkn96pzUr85J/eqc1K/OSf3aNBpEERERERERcXKa6tlGfDl8uL7hEBERERGRP0QjfiIiIiIiIk5OgZ+IiIiIiIiTU+AnIiIiIiLi5BT4iYiIiIiIODkFfiIiIiIiIk5OgZ+IiIiIiIiTU+AnIiIiIiLi5BT4iYiIiIiIODkFfiIiIiIiIk5OgZ+IiIiIiIiTU+AnIiIiIiLi5BT4iYiIiIiIODkFfiIiIiIiIk5OgZ+IiIiIiIiTU+AnIiIiIiLi5BT4iYiIiIiIODkFfiIiIiIiIk5OgZ+IiIiIiIiTU+AnIiIiIiLi5BT4iYiIiIiIODkFfiIiIiIiIk5OgZ+IiIiIiIiTU+AnIiIiIiLi5BT4iYiIiIiIODlDYGCkraUrISIiIiIiImeORvxEREREREScnAI/ERERERERJ6fAT0RERERExMkp8BMREREREXFyCvxEREREREScnAI/ERERERERJ6fAr5VzdTXwzDMxbN+eSEpKX26/PbSlqySnIDrawvvvd2H79kTWr0/gkUeisFgMAEREuPLJJ13JyOjPzz/HM2yYb4N7zznHh6VLe5GZ2Z+FC7sTE2NpgRbIyTz7bCwLF3Z3vFa/tl0mk4E5czqwZUs/tm7tx1NPxeDqqj+vbV27di68+mpHtm1LZMOGvjz4YCTGQ7/1qF/bHldXA8uW9ebcc30caU3tx1tvDWb9+gTS0/vzwguxeHjo1+Lmdqx+HTrUh2+/7UlGRn9WrIjn+usDG9yjfv3j9Em0cg8/HEX//t5cffUW7r03g3vuCefKK/1bulpyAmazgfff70J1tZXLLkthypQdjBzpx/33RwLw3ntdKCqq5eKLU1iwIJ9//SuOqCj7X1phYa68/34XPv20gIsuSiEvr5p33+2CwdCSLZKjDR3qw1/+EtQgTf3adj38cBSXXurHTTdt48YbtzFsmC9Tp4YD6te27MknYwgNtTB6dCq33baDceMCmTLF/uWp+rVtsVgMvPFGHN26eTRIb0o/XnZZe2bOjGTGjEzGjNlMnz5ePPJIh+Zu2lntWP0aE+PGBx905euvixg2bCPz5u3hiSdiuOgiX0D92lQK/FoxDw8jf/lLMA89lMnGjWV8800xL7+cw623Brd01eQE+vb1IibGjTvv3ElaWiUrV5byxBO7GTs2gCFDfOjY0Z1p09LZvr2Cl17KJjn5oOPbrBtvDCI1tYyXX85h+/YK7r47nfBwV4YO9TnJu0pz8fAwMm9eLKtWHXCkqV/bLh8fF26+OZhp09L57beDrF59kKef3kN8vJf6tY0bPtyX+fNz2Lq1gl9+OcB//1vAkCHt1K9tTOfO7ixa1JPo6IajOk3tx0mTQvnnP3P59ttiNmwo4777Mhg3LhBPT/1q3ByO169XXulPamoZL7yQTUZGFUlJhXzyST5jxwYA6tem0qfQivXo4YHFYmDVqlJH2qpVpfTp44WLSwtWTE5ox44Krr9+K2VlVkeazQaurkb69fMiJaWsQd6qVaUkJnoD0K+fFytX1vd3RYWVjRvLHfnS8mbOjOSXXw7wyy/1gZ/6te0aONCbykory5aVONIWLMjnuuu2ql/buOLiWsaODcDd3UhwsJkLLvBlw4aD6tc2ZtAgb5YuLeHSS1MbpDelH41G6NPHi19/rc9PTi7FZDLQs6fnGW6RwPH79X//K+Tvf89sVN7NzR6yqF+bRoFfKxYc7EpxcS1VVTZHWn5+NRaLEX9/cwvWTE6ksLCW5cvrgwKDAW69NYRffz1AcLArubnVDcrn59cQFuYKQFDQifOlZSUmenHFFf7Mnr2rQbr6te2KjnZj9+4qrrrKn+XLe7NmTQKzZ0dhNhvUr23cffdlMHiwD+np/dm0qR95eTU8/fQe9Wsb8957ecyZk0VFhbVBelP6sV07E+7uxgb5dXVQXKx+bi7H69f09Eo2bixzvA4MNHPllf6sXGn/vUr92jSmlq6AHJ+7u5HqaluDtMOvLRbF7G3FnDkd6NnTg4svTmHy5NBGfVpVZcXV1d6fHh7H6vP6fGk5rq4GnnsulgcfzKSkpK5B3rH+rKpf2wYvLxeioixMnBjC9OkZeHq68NRTMbi4GNSvbVxMjBspKWU888wevLxMPPFENLNnd1C/Oomm9KO7u/FQ+aPvt6mfWxEPDyNvv92Z3Nwa3n03z5Gmfv3j9Cm0YpWVVsfOcocdfl1RUXesW6SVeeyxDkyYEMzkyTvYtq3i0D9KDfvUYjE6+vPYfW5Uf7cC06ZFkJ5eyRdfFDXKU7+2XbW1Nnx8TNx22w5WrSrlhx/2M3v2LsaPD6amxqZ+baOioy089lg0d91lX7v5ww/7ueeedG69NUT96iSa8vduVZX1UPmj7zeon1sJb28XPv64Kx06WPjLX7Y6RgbVr02jwK8Vy82txtfXhNlc/z9wUJArlZVWiotrW7BmcjIGA7zwQiw33xzMpElpfPNNMQA5OdUEBTWcphsUZGbfvhrA3ucnypeWc9VV/lxwgS8ZGf3JyOjP7beHMWiQNxkZ/dWvbdi+fdXU1FjJzKxypO3cWYG7u5G8PPVrW9W7tycHD9aRk1M/5WvDhjJMJgP79qlfnUFT/t4tKqqlosLaIN/FBdq3Vz+3Bn5+JhYu7E6HDm5ceeXmBn8/q1+bRoFfK5aSUk51tY3+/esXlA8c6M3GjWXU6YuLVu2RRzpw1VUB3HLLdr76qtiRvmbNQXr29GxwpsyAAd6sWXPQkT9wYP3Oce7uRnr18nDkS8sZM2Yz5523gWHDNjJs2EY++CCP9evLGDZso/q1DVu9+iBms5Fu3dwdaZ07e1BaWktysvq1rdq3rwZfX1ODdT2dO9v7OC2tQv3qBJry967NBuvXN8xPTPSmttZGSkr9+jJpfmazgQ8+6IKfn4nRo1PZubOyQb76tWkU+LViFRVWPvkknyefjCYhwZOLL27PbbeF8uabuS1dNTmBfv28mDw5lKee2sOGDWUEBZkd14oVB9i9u4oXX+xIly7u3HFHGP36efHBB/a56x9+mE/fvl7cfXcYnTu789xzsezZU83y5SUneVc50/bsqSYjo8px7d9fS2WllYyMKvVrG5aRUcmiRUW88EJHevf2ZOBAbx58MJIPPshj+fIS9WsblZxcyqZNZbz4Yke6d/egXz8v5s2L4ZNP8vnyyyL1qxNo6t+7b7+9jylTQrnssvbEx3vy5JMxfPRRXoNdQqX5TZ4cSny8J3fdtZPycqvj9ydfX/t29urXpjEEBkbaTl5MWoq7u5Gnnoph1Cg/SkvreO21HF57LaelqyUnMHt2FLfdFnbMvNDQX4mKsvDccx3p29eLzMxKZs3axdKl9b9QDBvmy6OPdiA83JU1aw4ybVp6g2kO0jr8/e8RDBzow5gxmwGIiVG/tlWenkbmzo1m1Cg/amttfPJJAXPmZFFba1O/tmHBwWYeeyyaIUN8qKmx8cUXhTz6aBaVlerXtiovbxBXX73ZsXN2U/vxjjvCmDw5BFdXI19/XcSMGRlUVurX4uZ2ZL8uXtyTPn28GpVZteoAl19u//dW/frHKfATERERERFxcprqKSIiIiIi4uQU+ImIiIiIiDg5BX4iIiIiIiJOToGfiIiIiIiIk1PgJyIiIiIi4uQU+ImIiIiIiDg5U0tXQEREpDksXNidc87x4emn9/D003tOWt5iMbBpUz98fU2kpVVwzjkbGpV58cWOXHttoOO11WqjqspGXl41H3+cz7PP7sV2xKFJ48cH8Ze/BNGpkzsmk4E9e6r44osiXnhhL+Xlxz9gODk5gagoi+N1XZ2N0tI6Nm0q4+WXs/nxx/qzy8aNC+Sllzo2uN9qtVFWVsfu3VUkJRXy0kvZjZ59xx07CQ428+CDUVRVWenefQ2lpXUNnvPEE9FMmBBCenoFgwZtaFSvo338cT533rmTwYN9+Oyz7ofqt6VBfQ/nZWVVkZi47rjPEhGRptGIn4iIyDFccokfvr7270fj4tzp37/xocKHlZXVkZ1dRUFBDUYjdOjgxowZkcyaFeUoM2NGBM88E0ufPl4YDFBVZaVTJ3fuuSec99/vckp1Ki6uJSenmv37a/HxcWHo0HZ89FFXxo0LaFS2ttZGdnYV2dlV7NtXg9FooHt3Tx56KIo77ww75vM/+6wQAIvFyCWXtG+Uf/HF7RuUO7Jeh9/ryGv//tpGz5g7Nxqz2XBK7RURkdNHgZ+IiMgxHB7Jq6iwj8Rdd13Qcct+8UURffqso2fPtcTFrWbhwgIAJkwIwWgEs9nAlCmhADzwQCYxMauJi0tm8uQ0AIYObcegQd4nrdOsWbuIj19Lt25r6NZtDV9+WYjRaOCJJ2Lw9XVpUDY7u5o+fdbRp8864uPX0rlzMosWFQFw003Bx3x+VlYVa9YcBGDUKL8GeQkJnoSH20f3/ve/hoHfrFm7HO915DVr1q5G79GpkzuTJ4eetK0iInJ6KfATERE5SlCQmfPOa4fVamPOHHvwMnq0Hx4eJ/9ns7LSxoIF9sDP3d1IQIAZX18THh72wCw/v8ZR9r//LeSpp3bz6qvZVFYef6rnsRQX13LnnemUldXh6enClVc2HvU7Uk2NjZ9+OgCAn9/xV3r873/2up9/vi+envXtvfRSeyC4bVs5W7ZU/K66Hm3q1HBCQ12b9AwREfl9FPiJiIgc5ZprAjCZDKxaVco77+wjP78Gb28Tl1/uf9J7PT2N3HSTfXTw4ME6iopqyc+vYccOe7A0f34cX33Vg3vuCSc+3pNnntnL7NlZrF9f9rvrefBgHWvX2kfo+vY9/lRUFxeIiHDl6qvtwWFKyvHf67PPCrFabbi7G7noovrpniNH+jny/6i8vGr27KnC09OF2bOjTn6DiIicNgr8REREjvLnP9uneX76aQF1dfDZZ/ZRsOuvDzxm+csv92P9+gRSU/uSltbfESTNn59Dba19d5fbb99JYaF9tK9/f29mzoxkyZJerFgRz0UX+f7huh4eQQwIaDiKFxVlIS9vEHl5g8jJGcTatX3p29eL/ftrmT0767jPy82tYdWqUqB+umenTm507uwOHDvwe+mljo73OvLq2dOjQbnKSptj+ueYMQGcc47PH2y1iIj8Xgr8REREjhAf70m3bh5UVVn5/HN7kHN46uaf/uRDTIxbo3s8PV0IC7Pg52emqsrKli3lPPzwLp54on730LVrDzJo0HoeeiiTn38uoarKPrWzUyd33nmnywk3jzmRw7uGurg03DClttZGbm41NTX1U0hffTWbc8/d4FjHdzyH1/ANG+aLu7vRMc1z06Yydu6sbFT+eJu7VFfbGpX98ssili7dD8Djj0dj0v7iIiLNQn/dioiIHGHcOPuonsViJC2tf6P8664L5PHHdzdIO3xswYm4uRlwdTXyxhu5vPFGLu7uRoYP9+WJJ2IIDDRz443BrF594oDsWA6P9B0eTTwsO7uaxMR1BAWZee+9LvTt68WYMQG8++6+kz7z888LeeyxaDw9XbjwQt+TTvOcNWsXCxbkn3KdZ87MZOnS3nTr5sGtt4ac8n0iIvLHacRPRETkELPZwJgxJ17HN25cIMbf+a/nNdcEkJU1kJ9+6o3Loc03KyqsfPFFkWN0LTDQ/Lvr6+pqID7ePlK4du2x1+3l5dUwceJ2Dh6sIzTUlX/+s7OjDsdTUFDLL7/Yz9qbODGEhARPAMcIaFPt3FnJ66/nAPVrB0VE5MxS4CciImcVs9mAp6ex0WU0wkUX+eLvb6a8vI5u3ZKJifnNcQ0atB6r1UZoqCsXXOD7u97zl18OUFdnw8/PzNy50Vgs9mmZXbq4O87LO9GGK8fi6Wlk7txofH1NlJXVkZRUcNyye/ZUO0Ype/XyPKXjFA6P7g0e7IPRaGDNmoPs2lX1u+p4Is8+u5c9e07f80RE5MQU+ImIyFnl7rvDycgY0Oi6+OL2jk1dli4tobCwlrIyq+NKT690rI073iYvx5OdXc28efb1fhMmhJCe3p+tW/vx00/xRERYyMmp5s03c0/6nDlzOrB+fQKbNvVl27ZEx3l899+fSXFx48PSj/TWW7kkJ9s3bZk2LYLg4BOPMH75ZRHV1fXrAw8f83Cieh19LVjQ9bj3VFRYj3nOn4iInBkK/ERERACTycCFF/oC8NVXRccsc3gU7KKL2p/wLLxjeeaZvdx663ZWrjzA/v21eHq6sHt3FR98kMcll6SQl1dz0me0b28iLMxCYKCZ8nIry5eXMG7cFj766OTr62w2mDo1nepqK15eLjz88ImPUygpqWPpUvt0T6vVxuefH/szObJeR18nm7765ZdF/PDD/pPWXUREms4QGBjZeMstERERERERcRoa8RMREREREXFyCvxEREREREScnAI/ERERERERJ6fAT0RERERExMkp8BMREREREXFyCvxEREREREScnAI/ERERERERJ6fAT0RERERExMkp8BMREREREXFy/w+2R/pZMjthLgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "driversLaps = raceResults.groupby('Driver')['Laps'].sum().sort_values(ascending=False)\n",
    "c = assign_color('drivers', driversLaps.index)\n",
    "plt.figure(figsize=(14,8))\n",
    "plt.axis([0, max(driversLaps.values)+30, 21.65, -0.65])\n",
    "plt.barh([driver.split()[1] for driver in driversLaps.index], driversLaps.values, color=c)\n",
    "plt.title(\"Formula 1 - 2021 Season\\nLaps Driven by Drivers in Race Sessions\", fontsize=22, fontweight='bold', color='#bbbbbb')\n",
    "for i in range(len(driversLaps)):\n",
    "    plt.text(driversLaps.values[i]-60, i+0.25, \"{:4}\".format(driversLaps.values[i]), fontsize=15, color='k')\n",
    "plt.xlabel('LAPS DRIVEN', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.xticks(fontsize=14, color='#ffff55')\n",
    "plt.ylabel('DRIVERS', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.yticks(fontsize=13, color='#ffff55')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2354a3be",
   "metadata": {},
   "source": [
    "Well, the visualization above reveals that **Carlos Sainz had the most laps driven** in 2021 Season! The major fact could be that he **never failed to finish any races**, hence the number is the highest among all, which should not be surprising...\n",
    "\n",
    "Then, **Hamilton has come in the 2nd place** for total number of laps, but this did not help him obtain the world championship title against Verstappen, who has completed 1211 laps and the difference appeared to be **more than 50 laps**.\n",
    "\n",
    "Taking to the bottom, it seems that Mazepin was the driver with **the least driven laps** (if we exclude Kubica), stayed **very slightly above 1000 laps**. Above the Russian, it's **Raikkönen** the Iceman but consider that he missed two races due to his positiveness of Covid-19.\n",
    "\n",
    "Lastly, by adding the total laps of Raikkönen and Kubica, it will equal to **1184 laps**, which will place them between Perez and Stroll."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "350513dc",
   "metadata": {},
   "source": [
    "As we've seen the total laps driven for all drivers, can we do the same for **the teams** as we merge all the teammates' numbers?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "5f513bc4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "teamsLaps = raceResults.groupby('Team')['Laps'].sum().sort_values(ascending=False)\n",
    "c = assign_color('teams', teamsLaps.index)\n",
    "plt.figure(figsize=(14,7))\n",
    "plt.axis([0, max(teamsLaps.values)+30, 9.65, -0.65])\n",
    "plt.barh(teamsLaps.index, teamsLaps.values, color=c)\n",
    "plt.title(\"Formula 1 - 2021 Season\\nLaps Driven by Teams in Race Sessions\", fontsize=22, fontweight='bold', color='#bbbbbb')\n",
    "for i in range(len(teamsLaps)):\n",
    "    plt.text(teamsLaps.values[i]-160, i+0.2, \"{:4}\".format(teamsLaps.values[i]), fontsize=20, color='k')\n",
    "plt.xlabel('LAPS DRIVEN', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.xticks(fontsize=14, color='#ffff55')\n",
    "plt.ylabel('TEAMS', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.yticks(fontsize=13, color='#ffff55')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "842c085f",
   "metadata": {},
   "source": [
    "Yep, with regards to teams, we can imply that **McLaren Mercedes** had the most driven laps according to the bar chart above. That's **87 laps** more than Mercedes factory team!\n",
    "\n",
    "**Ferrari** and the customer team **Alfa Romeo** almost equalized their total driven laps, where the difference is **just 1**!\n",
    "\n",
    "About the top two teams fighting for the titles in 2021 Season (yes, we mean **Mercedes** and **Red Bull**), they placed 6th and 7th, respectively for total laps and the German team was **only 6 laps** ahead."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f8cf383",
   "metadata": {},
   "source": [
    "Similar to laps driven analysis for all drivers, lastly, what about the **total distances driven** for each of them in racing sessions?\n",
    "\n",
    "_Although this requires lots of data extraction below, believe me, this one is also worth to explain; and again, the calculation was performed on full driven laps..._"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "f27b1ed5",
   "metadata": {},
   "outputs": [],
   "source": [
    "drivers = raceResults['Driver'].unique()\n",
    "driversLapsEachTrack = {}\n",
    "for driver in drivers:\n",
    "    laps = raceResults[raceResults['Driver'] == driver]['Laps'].values\n",
    "    if driver == 'Kimi Raikkönen':\n",
    "        for i in [12, 13]:   laps = np.insert(laps, i, 0)\n",
    "    if driver == 'Robert Kubica':\n",
    "        for i in range(12):  laps = np.insert(laps, i, 0)\n",
    "        for j in range(8):   laps = np.append(laps, 0)\n",
    "    driversLapsEachTrack[driver] = laps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "90bf3d27",
   "metadata": {},
   "outputs": [],
   "source": [
    "circuitLength = calendar['Circuit Length(km)'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "47b7f489",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "driversRaceDist = {}\n",
    "for driver, laps in driversLapsEachTrack.items():\n",
    "    driversRaceDist[driver] = round(laps@circuitLength, 2)\n",
    "driversRaceDistSr = pd.Series(driversRaceDist.values(), driversRaceDist.keys()).sort_values(ascending=False)\n",
    "c = assign_color(\"drivers\", driversRaceDistSr.index)\n",
    "plt.figure(figsize=(14,8))\n",
    "plt.axis([0, max(driversRaceDistSr.values)+100, 20.65, -0.65])\n",
    "plt.barh([driver.split()[1] for driver in driversRaceDistSr.index], driversRaceDistSr.values, color=c)\n",
    "for i in range(len(driversRaceDistSr)):\n",
    "    plt.text(driversRaceDistSr.values[i]-530, i+0.22, \"{:8.2f}\".format(driversRaceDistSr.values[i]), fontsize=15, color='k')\n",
    "plt.title(\"Formula 1 - 2021 Season\\nDistance Driven by Drivers in Race Sessions\", \n",
    "          fontsize=22, fontweight=\"bold\", color=\"#bbbbbb\")\n",
    "plt.xlabel('DISTANCE DRIVEN (km)', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.xticks(fontsize=14, color='#ffff55')\n",
    "plt.ylabel('DRIVERS', fontsize=16, color='#ffff55', fontweight='bold')\n",
    "plt.yticks(fontsize=13, color='#ffff55')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a8990ff",
   "metadata": {},
   "source": [
    "Here above, just like the total laps driven, **Carlos Sainz went the most distance** (in kilometres) through all race sessions! It is noticeable that the difference between him and **Ricciardo** is more than 100 km.\n",
    "\n",
    "Remarkably, Verstappen became the champion of this season with **slightly less than 6000 km** total race distance driven, while the runner-up **Hamilton** travelled **300 km more** than the Dutchman.\n",
    "\n",
    "On the one side, it was revealed that Mazepin was the only driver who covered **not more than 5000 km** race distance. Could this be because of his high number of DNFs he had?\n",
    "\n",
    "In addition, if we sum the distances of Raikkönen and Kubica together, that will be **5863.33 km** which could be placed between Latifi and Perez."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f29b4cb",
   "metadata": {},
   "source": [
    "## Conclusion & Discussions for 2022 Season"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "619cbb20",
   "metadata": {},
   "source": [
    "**And dear Formula 1 fans, this concludes our analysis of 2021 Season! I want to thank a lot if you come here without skipping any parts. I hope you enjoyed all the explanations and visualizations presented here, gained lots of insights and remembered all the things happened throughout this action-packed season!**\n",
    "\n",
    "At the time of the publication of this analysis, we know that the 2022 Season has already started and we have already watched several races with those cars from new era! As always, let's make many discussions about the drivers, teams and how well they are performing this season so far...\n",
    "\n",
    "* First things first, 2022 Season is where **the brand-new cars** are introduced and the primary aim is to **reduce the gap** between the fastest and slowest team in order to make all the races more exciting and more competitive. Therefore, the rims of the tyres were increased to **18 inches**; the chassis, aerodynamics, front and rear wings, sidepods, bargeboards were re-designed and the rules were changed accordingly, to especially decrease the **dirty air** that left behind by cars and let drivers follow each other more easily while still DRS is available and the structure of engines are kept as **1.6 litre turbo hybrid**. In addition, **ground effect**, where the last period the usage of this technology was between **late 1970s and early 1980s**, was re-enabled for more downforce overall. Despite this evolution, the biggest problem that all the teams faced is **porpoising** which causes the car to bounce upwards and downwards at high speeds and can badly affect the drivers' health and backs! It is certain that any team which overcomes this annoying problem will probably step ahead of the rivals in terms of car stability and have more chance to score high in all remaining races!\n",
    "* **Mercedes** have clinched their success by taking **the 8th consecutive constructors' championship title**, but this time, unfortunately, they could not take the crown of drivers' title for Hamilton, due to the incidents in the last few laps in Abu Dhabi last season. By entering the new era, Hamilton now has a compatriot **George Russell** as his new teammate. The German team, in 2022, appears to be the **3rd best** in terms of speed and admit that they cannot match Red Bull and Ferrari for now. Within the completed races, Russell had a superb consistency as he achieved to place in the top 5 each race, thus earned him **Mr. Consistent** nickname (in additon to **Mr. Saturday** from last season), while Hamilton often struggled with his car and fell behind the young British driver in the standings. We wish him for regaining strength and fighting for the wins for the upcoming races this season.\n",
    "* **Red Bull** enjoyed the triumph achieved by **Max Verstappen** who took **the world championship title** for the first time after Vettel in the same team, in 2013. Eventually, the Dutchman decided to take **number 1** as his personal racing number for the new season. At the same time, year 2021 was **Honda's last season** in Formula 1; however, the Japanese engine supplier will still continue to support Red Bull until the team is able to build their own engine independently (that's why, the engine name now appears as **RBPT** which means **Red Bull PowerTrain**). For drivers, **Verstappen** (leading the championship) and his teammate **Perez** can compete for the title in 2022 Season, as long as the car is strong, durable and reliable to challenge with Ferrari.\n",
    "* **Ferrari** recovered the strength by **finishing 3rd** in 2021, thanks to coherent drives by **Charles Leclerc** and **Carlos Sainz**, as compared to 2020 which was one of the worst season the prancing horse had. With the aim to prepare the new-era car for winning races and fighting for the title, the Italian team presented **F1-75** to the world. The first few races pointed out that Ferrari is now **able to take the top spot** in both drivers' and constructors' standings and make the Tifosi happy and proud, while also doing their best to outperform Red Bulls every race! Besides, one thing from the team taught us that there should be **no room for errorneous calls for pits** and **no lack for durability of engine components** as they could affect the drivers and the team substantially in a long term.\n",
    "* **McLaren** had another decent season and even achieved to get a race win which was ensured with 1-2 double finish **after waiting for 9 years**! However, they failed against Ferrari for the 3rd place in constructors' standings. In the season of new-era cars, they still adopt to continue with **papaya orange** livery, supplied with some black and blue ones. Of course, we still see **Lando Norris** and **Daniel Ricciardo** as the main drivers. Despite a poor start of the season, the British team tidied up later by scoring points regularly, especially with Norris, while Ricciardo had some difficulties from time to time and usually ended races behind his teammate and outside of top 10.\n",
    "* **Alpine** has been re-branded from **Renault** which was known as the yellow color. In 2021, this blue-weighted team had some good battles within the middle group and they achieved **finishing 5th** in the standings, thanks to **Fernando Alonso** and **Esteban Ocon**'s solid drives; both have stepped on the podium once while the Frenchman won a race for the first time! Now, they want to continue the trend and do their best to go further in 2022, with some **pink liveries** on their cars (Yes, you guessed that right, **BWT** is one of their main sponsors, known with the pink color during the Force India & Racing Point period!).\n",
    "* Another team with decent results was **AlphaTauri**. They had the struggles mostly with Alpine but could not keep up with the French team later in 2021 Season, thus finishing behind them. Speaking of drivers, it is safe to say **Gasly** shouldered the Italian scuderia by scoring more than 100 points. **Tsunoda**'s whole season was not so bad at all but the points gap between them was so high for a midfield team. Now in 2022, they expect to sustain the accomplishments within the mid-pack and similar to Red Bull, their engine supplier name appeared as **RBPT**, as they previously used Honda engines.\n",
    "* It is great to see **Aston Martin** name back in Formula 1; the last time we saw the luxury car manufacturer here was around **early 60s** and was re-branded from **Racing Point**, which was known well with pink liveries. Now, the team adopted to **shiny green color** which reflects the **British racing green** (that's the best expression)! The 4-time world champion **Seabstian Vettel** joined the squad for new adventures of his career, after leaving from Ferrari. With his teammate **Lance Stroll**, the team finished in a reasonable place last season. About 2022, with the same drivers, currently they were far behind where they needed to be as they earned significacntly less points in the first several races. Could we see them coming back stronger for the rest of the season?\n",
    "* **Alfa Romeo** finished the season **9th** in the constructors. It is sad to know that **Kimi Raikkönen** retired from Formula 1 and we, the spectators, will always miss him personally and remember his unique attitudes and sympathies. Meanwhile, **Giovinazzi** also left the team and we see him racing in **FIA Formula E** branch. In 2022, the Swiss/Italian team had a agreement with another Finnish driver **Valtteri Bottas**, who departed from Mercedes. With this new chapter of his career, it seems that he didn't lose any pace and consistency as the results show he could continuously earn points. Moreover, Bottas could even challenge with the top teams and his old teammate Hamilton! Together with that, he's accompanied by a rookie, **Guanyu Zhou, the first Chinese driver** in Formula 1 history and we'd like to see him some good achievements to not put himself much behind the veteran.\n",
    "* **Williams** finally scored some points after waiting for almost **two and a half years** and saved themselves from the bottom of the constructors' standings. As George Russell moved to Mercedes in 2022 expectedly, the team made a deal with **Alexander Albon** who had raced for Red Bull previously. Here, the Thailand driver achieved race finishes with points which made all the team workers proud (that's because his **red-dyed hair** might've brought luck, what do you say?). On the other hand, **Latifi**'s races were not bright, compared to Albon, as he had accidents in some race weekends due to his errors that might even affect state of the sessions, putting his seat in risk for the future.\n",
    "* **Haas** was the only team that had no points in 2021 season. Rather, they focused on the development for rookies **Mick Schumacher** and **Nikita Mazepin** through all races and it ended with both drivers usually completing the races with 1-2 laps behind the leader! The main reason was that almost no enhancements were made on their cars due to shifting all the resources into the car for new era. Before the start of 2022 Season, the American team **terminated the contract with Mazepin** because of the war ongoing between Russia and Ukraine although FIA stated that Russian and Belurisian drivers might continue racing, but under neutral flags. Similarly, their name sponsor **Uralkali** left the team, too. Consequently, they returned back to the white-based livery with some red and black. Plus, their former driver **Kevin Magnussen** was called to replace the seat of Mazepin. So far, the Danish driver succeeded to finish in the top 10 in a few races, thus brought points to the team while Schumacher had **terrifying crashes** that could cost much as it is known that all the teams are struggling to manage **the budget cap** in the best way.\n",
    "\n",
    "Keep in mind that during your free time for entertainment, you may want to watch **Formula 1: Drive To Survive** episodes available in **Netflix** or you may want to play the official videogame **F1 2021**, which was published by **Electronic Arts** and developed by **Codemasters**, in front of your PC/console or wait for the new videogame which is exactly called **EA Sports F1 22** (set to be released **on 1st of July**), to drive and get a glimpse of the handling of these new era cars at home! Well, if this is not enough, do you want to take your role as a team principal? Then, you should also wait for **F1 Manager 22** (developed by **Frontier Developments** and expected to be released **on 30th of August**) which looks quite exciting and puts the player behind the team to manage everything such as the drivers, cars, facilities, in all details with stunning graphics..."
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    "## Once again, thank you very much for reading the analysis, and keep up with Formula 1!"
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