beginners/03.f1_analysis_EDA.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Formula 1 Grand Prix Exploratory Data Analysis (EDA)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploratory based on the drivers, constructors or both \n",
    "### FIA Rules defined in the last 10 years\n",
    "\n",
    "Before begining the project we need to understand the history of F1 and the different eras in which a certain driver or tream dominated the whole grid. Here are some important eras of F1 in (relatively) recent history.  \n",
    "\n",
    "* 1994-2009 Schumacher (Scuderia Ferrari)\n",
    "* 2007-2010 Alonso (Renault,Scuderia Ferrari)\n",
    "* 2011-2013 Vettle (Redbull Racing)\n",
    "* 2014-Present Hamilton (Mercedes-Benz)\n",
    "\n",
    "An F1 team's performance is largely dependent on the FIA technical regulation for the season. After the 2013 season, new engine regulations were made (Hybrid era). Mercedes-Benz is the most dominant team since, followed by Red Bull Racing and Scuderia Ferrari. Rules are set to change for 2022, so whatever analysis is made here will not apply for 2022 season and after. Only data after 2010 will be considered in the following analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "start = time.time()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pickle\n",
    "from sklearn.preprocessing import StandardScaler,LabelEncoder,OneHotEncoder\n",
    "from sklearn.model_selection import cross_val_score,StratifiedKFold,RandomizedSearchCV\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.metrics import confusion_matrix,precision_score,f1_score,recall_score\n",
    "plt.style.use('seaborn')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = pd.read_csv(r'./data_f1/results.csv')\n",
    "races = pd.read_csv(r'./data_f1/races.csv')\n",
    "quali = pd.read_csv(r'./data_f1/qualifying.csv')\n",
    "drivers = pd.read_csv(r'./data_f1/drivers.csv')\n",
    "constructors = pd.read_csv(r'./data_f1/constructors.csv')\n",
    "circuit = pd.read_csv(r'./data_f1/circuits.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = pd.merge(races,results,how='inner',on=['raceId'])\n",
    "df2 = pd.merge(df1,quali,how='inner',on=['raceId','driverId','constructorId'])\n",
    "df3 = pd.merge(df2,drivers,how='inner',on=['driverId'])\n",
    "df4 = pd.merge(df3,constructors,how='inner',on=['constructorId'])\n",
    "df5 = pd.merge(df4,circuit,how='inner',on=['circuitId'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "\n",
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       "\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>raceId</th>\n",
       "      <th>year</th>\n",
       "      <th>round</th>\n",
       "      <th>circuitId</th>\n",
       "      <th>name_x</th>\n",
       "      <th>date</th>\n",
       "      <th>time_x</th>\n",
       "      <th>url_x</th>\n",
       "      <th>resultId</th>\n",
       "      <th>driverId</th>\n",
       "      <th>...</th>\n",
       "      <th>nationality_y</th>\n",
       "      <th>url_x</th>\n",
       "      <th>circuitRef</th>\n",
       "      <th>name</th>\n",
       "      <th>location</th>\n",
       "      <th>country</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>alt</th>\n",
       "      <th>url_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2009</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Australian Grand Prix</td>\n",
       "      <td>2009-03-29</td>\n",
       "      <td>06:00:00</td>\n",
       "      <td>http://en.wikipedia.org/wiki/2009_Australian_G...</td>\n",
       "      <td>7554</td>\n",
       "      <td>18</td>\n",
       "      <td>...</td>\n",
       "      <td>British</td>\n",
       "      <td>http://en.wikipedia.org/wiki/Brawn_GP</td>\n",
       "      <td>albert_park</td>\n",
       "      <td>Albert Park Grand Prix Circuit</td>\n",
       "      <td>Melbourne</td>\n",
       "      <td>Australia</td>\n",
       "      <td>-37.8497</td>\n",
       "      <td>144.968</td>\n",
       "      <td>10</td>\n",
       "      <td>http://en.wikipedia.org/wiki/Melbourne_Grand_P...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2009</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Australian Grand Prix</td>\n",
       "      <td>2009-03-29</td>\n",
       "      <td>06:00:00</td>\n",
       "      <td>http://en.wikipedia.org/wiki/2009_Australian_G...</td>\n",
       "      <td>7555</td>\n",
       "      <td>22</td>\n",
       "      <td>...</td>\n",
       "      <td>British</td>\n",
       "      <td>http://en.wikipedia.org/wiki/Brawn_GP</td>\n",
       "      <td>albert_park</td>\n",
       "      <td>Albert Park Grand Prix Circuit</td>\n",
       "      <td>Melbourne</td>\n",
       "      <td>Australia</td>\n",
       "      <td>-37.8497</td>\n",
       "      <td>144.968</td>\n",
       "      <td>10</td>\n",
       "      <td>http://en.wikipedia.org/wiki/Melbourne_Grand_P...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>18</td>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Australian Grand Prix</td>\n",
       "      <td>2008-03-16</td>\n",
       "      <td>04:30:00</td>\n",
       "      <td>http://en.wikipedia.org/wiki/2008_Australian_G...</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>...</td>\n",
       "      <td>Japanese</td>\n",
       "      <td>http://en.wikipedia.org/wiki/Honda_Racing_F1</td>\n",
       "      <td>albert_park</td>\n",
       "      <td>Albert Park Grand Prix Circuit</td>\n",
       "      <td>Melbourne</td>\n",
       "      <td>Australia</td>\n",
       "      <td>-37.8497</td>\n",
       "      <td>144.968</td>\n",
       "      <td>10</td>\n",
       "      <td>http://en.wikipedia.org/wiki/Melbourne_Grand_P...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>36</td>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Australian Grand Prix</td>\n",
       "      <td>2007-03-18</td>\n",
       "      <td>03:00:00</td>\n",
       "      <td>http://en.wikipedia.org/wiki/2007_Australian_G...</td>\n",
       "      <td>383</td>\n",
       "      <td>18</td>\n",
       "      <td>...</td>\n",
       "      <td>Japanese</td>\n",
       "      <td>http://en.wikipedia.org/wiki/Honda_Racing_F1</td>\n",
       "      <td>albert_park</td>\n",
       "      <td>Albert Park Grand Prix Circuit</td>\n",
       "      <td>Melbourne</td>\n",
       "      <td>Australia</td>\n",
       "      <td>-37.8497</td>\n",
       "      <td>144.968</td>\n",
       "      <td>10</td>\n",
       "      <td>http://en.wikipedia.org/wiki/Melbourne_Grand_P...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>55</td>\n",
       "      <td>2006</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Australian Grand Prix</td>\n",
       "      <td>2006-04-02</td>\n",
       "      <td>14:00:00</td>\n",
       "      <td>http://en.wikipedia.org/wiki/2006_Australian_G...</td>\n",
       "      <td>796</td>\n",
       "      <td>18</td>\n",
       "      <td>...</td>\n",
       "      <td>Japanese</td>\n",
       "      <td>http://en.wikipedia.org/wiki/Honda_Racing_F1</td>\n",
       "      <td>albert_park</td>\n",
       "      <td>Albert Park Grand Prix Circuit</td>\n",
       "      <td>Melbourne</td>\n",
       "      <td>Australia</td>\n",
       "      <td>-37.8497</td>\n",
       "      <td>144.968</td>\n",
       "      <td>10</td>\n",
       "      <td>http://en.wikipedia.org/wiki/Melbourne_Grand_P...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 51 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   raceId  year  round  circuitId                 name_x        date  \\\n",
       "0       1  2009      1          1  Australian Grand Prix  2009-03-29   \n",
       "1       1  2009      1          1  Australian Grand Prix  2009-03-29   \n",
       "2      18  2008      1          1  Australian Grand Prix  2008-03-16   \n",
       "3      36  2007      1          1  Australian Grand Prix  2007-03-18   \n",
       "4      55  2006      3          1  Australian Grand Prix  2006-04-02   \n",
       "\n",
       "     time_x                                              url_x  resultId  \\\n",
       "0  06:00:00  http://en.wikipedia.org/wiki/2009_Australian_G...      7554   \n",
       "1  06:00:00  http://en.wikipedia.org/wiki/2009_Australian_G...      7555   \n",
       "2  04:30:00  http://en.wikipedia.org/wiki/2008_Australian_G...        18   \n",
       "3  03:00:00  http://en.wikipedia.org/wiki/2007_Australian_G...       383   \n",
       "4  14:00:00  http://en.wikipedia.org/wiki/2006_Australian_G...       796   \n",
       "\n",
       "   driverId  ...  nationality_y                                         url_x  \\\n",
       "0        18  ...        British         http://en.wikipedia.org/wiki/Brawn_GP   \n",
       "1        22  ...        British         http://en.wikipedia.org/wiki/Brawn_GP   \n",
       "2        18  ...       Japanese  http://en.wikipedia.org/wiki/Honda_Racing_F1   \n",
       "3        18  ...       Japanese  http://en.wikipedia.org/wiki/Honda_Racing_F1   \n",
       "4        18  ...       Japanese  http://en.wikipedia.org/wiki/Honda_Racing_F1   \n",
       "\n",
       "    circuitRef                            name   location    country      lat  \\\n",
       "0  albert_park  Albert Park Grand Prix Circuit  Melbourne  Australia -37.8497   \n",
       "1  albert_park  Albert Park Grand Prix Circuit  Melbourne  Australia -37.8497   \n",
       "2  albert_park  Albert Park Grand Prix Circuit  Melbourne  Australia -37.8497   \n",
       "3  albert_park  Albert Park Grand Prix Circuit  Melbourne  Australia -37.8497   \n",
       "4  albert_park  Albert Park Grand Prix Circuit  Melbourne  Australia -37.8497   \n",
       "\n",
       "       lng alt                                              url_y  \n",
       "0  144.968  10  http://en.wikipedia.org/wiki/Melbourne_Grand_P...  \n",
       "1  144.968  10  http://en.wikipedia.org/wiki/Melbourne_Grand_P...  \n",
       "2  144.968  10  http://en.wikipedia.org/wiki/Melbourne_Grand_P...  \n",
       "3  144.968  10  http://en.wikipedia.org/wiki/Melbourne_Grand_P...  \n",
       "4  144.968  10  http://en.wikipedia.org/wiki/Melbourne_Grand_P...  \n",
       "\n",
       "[5 rows x 51 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df5.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['raceId',\n",
       " 'year',\n",
       " 'round',\n",
       " 'circuitId',\n",
       " 'name_x',\n",
       " 'date',\n",
       " 'time_x',\n",
       " 'url_x',\n",
       " 'resultId',\n",
       " 'driverId',\n",
       " 'constructorId',\n",
       " 'number_x',\n",
       " 'grid',\n",
       " 'position_x',\n",
       " 'positionText',\n",
       " 'positionOrder',\n",
       " 'points',\n",
       " 'laps',\n",
       " 'time_y',\n",
       " 'milliseconds',\n",
       " 'fastestLap',\n",
       " 'rank',\n",
       " 'fastestLapTime',\n",
       " 'fastestLapSpeed',\n",
       " 'statusId',\n",
       " 'qualifyId',\n",
       " 'number_y',\n",
       " 'position_y',\n",
       " 'q1',\n",
       " 'q2',\n",
       " 'q3',\n",
       " 'driverRef',\n",
       " 'number',\n",
       " 'code',\n",
       " 'forename',\n",
       " 'surname',\n",
       " 'dob',\n",
       " 'nationality_x',\n",
       " 'url_y',\n",
       " 'constructorRef',\n",
       " 'name_y',\n",
       " 'nationality_y',\n",
       " 'url_x',\n",
       " 'circuitRef',\n",
       " 'name',\n",
       " 'location',\n",
       " 'country',\n",
       " 'lat',\n",
       " 'lng',\n",
       " 'alt',\n",
       " 'url_y']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(df5.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#drop the columns which are not important\n",
    "data = df5.drop(['round','circuitId','time_x','url_x','resultId','driverId',\n",
    "                 'constructorId','number_x','positionText','position_x',\n",
    "                 'positionOrder','laps','time_y','rank',\n",
    "                 'fastestLapTime','fastestLapSpeed','qualifyId','driverRef','number','code','url_y','circuitRef',\n",
    "                 'location','lat','lng','alt','number_y','points','constructorRef','name_x','raceId','fastestLap','q2','q3','milliseconds','q1'],1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['year',\n",
       " 'date',\n",
       " 'grid',\n",
       " 'statusId',\n",
       " 'position_y',\n",
       " 'forename',\n",
       " 'surname',\n",
       " 'dob',\n",
       " 'nationality_x',\n",
       " 'name_y',\n",
       " 'nationality_y',\n",
       " 'name',\n",
       " 'country']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(data.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## F1 Grand Prix structure\n",
    "\n",
    "a F1 Grand Prix runs for 3 days over the weeekend, and is made of 3 parts: Practice session, Qualifying session and the actual race.\n",
    "\n",
    "In the practice sesssion there are 3 stages: FP1, FP2 and FP3. This is a free practice session for teams to test their cars on Friday and Saturday.\n",
    "\n",
    "Qualification rounds are also comprise 3 stages: Q1, Q2 and Q3. In this session, all drivers compete to set the best lap time. The bottom 5 drivers will be eliminated after Q1; the top 15 drivers will participate in the Q2 and try to set best lap time. The top 10 drivers will move to Q3 where they again compete to set the best best lap time. The cars' starting positions will be decided based on their qualifying time. The driver with the best time will get to start at the front.\n",
    "\n",
    "Sunday is the race, and points will be awarded to top 10 drivers. The top three will get to enjoy the podium.\n",
    "\n",
    "This happens for a full season, for a whole year, at diffrent circuits. The driver with the highest points will be awarded World championship, and the team with highest point will get Team Championship (each team have two cars and two drivers)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#considering data points from 2010\n",
    "data = data[data['year']>=2010]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#rename the columns\n",
    "data.rename(columns={'name':'GP_name','position_y':'position','grid':'quali_pos','name_y':'constructor','nationality_x':'driver_nationality','nationality_y':'constructor_nationality'},inplace=True)\n",
    "data['driver'] = data['forename']+' '+data['surname']\n",
    "data['date'] = pd.to_datetime(data['date'])\n",
    "data['dob'] = pd.to_datetime(data['dob'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "#creating a driver age parameter\n",
    "data['age_at_gp_in_days'] = abs(data['dob']-data['date'])\n",
    "data['age_at_gp_in_days'] = data['age_at_gp_in_days'].apply(lambda x: str(x).split(' ')[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cleaning Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Some of the constructors changed their name over the year so replacing old names with current name\n",
    "data['constructor'] = data['constructor'].apply(lambda x: 'Aston Martin' if x=='Force India' else x)\n",
    "data['constructor'] = data['constructor'].apply(lambda x: 'Aston Martin' if x=='Racing Point' else x)\n",
    "data['constructor'] = data['constructor'].apply(lambda x: 'Alfa Romeo' if x=='Sauber' else x)\n",
    "data['constructor'] = data['constructor'].apply(lambda x: 'Alpine F1' if x=='Lotus F1' else x)\n",
    "data['constructor'] = data['constructor'].apply(lambda x: 'Alpine F1' if x=='Renault' else x)\n",
    "# Correction for 2021\n",
    "data['constructor'] = data['constructor'].apply(lambda x: 'Alpine F1' if x=='Alpine F1 Team' else x)\n",
    "data['constructor'] = data['constructor'].apply(lambda x: 'AlphaTauri' if x=='Toro Rosso' else x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['driver_nationality'] = data['driver_nationality'].apply(lambda x: str(x)[:3])\n",
    "data['constructor_nationality'] = data['constructor_nationality'].apply(lambda x: str(x)[:3])\n",
    "data['country'] = data['country'].apply(lambda x: 'Bri' if x=='UK' else x)\n",
    "data['country'] = data['country'].apply(lambda x: 'Ame' if x=='USA' else x)\n",
    "data['country'] = data['country'].apply(lambda x: 'Fre' if x=='Fra' else x)\n",
    "data['country'] = data['country'].apply(lambda x: str(x)[:3])\n",
    "data['driver_home'] = data['driver_nationality'] == data['country']\n",
    "data['constructor_home'] = data['constructor_nationality'] == data['country']\n",
    "data['driver_home'] = data['driver_home'].apply(lambda x: int(x))\n",
    "data['constructor_home'] = data['constructor_home'].apply(lambda x: int(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#reasons for DNF(did not finish)\n",
    "data['driver_dnf'] = data['statusId'].apply(lambda x: 1 if x in [3,4,20,29,31,41,68,73,81,97,82,104,107,130,137] else 0)\n",
    "data['constructor_dnf'] = data['statusId'].apply(lambda x: 1 if x not in [3,4,20,29,31,41,68,73,81,97,82,104,107,130,137,1] else 0)\n",
    "data.drop(['forename','surname'],1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "font = {\n",
    "    'family':'serif',\n",
    "    'color':'black',\n",
    "    'weight':'bold',\n",
    "    'size':10\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dnf_by_driver = data.groupby('driver').sum()['driver_dnf']\n",
    "driver_race_entered = data.groupby('driver').count()['driver_dnf']\n",
    "driver_dnf_ratio = (dnf_by_driver*100/driver_race_entered).sort_values(ascending=False)\n",
    "plt.figure(figsize=(30,10))\n",
    "bars = plt.bar(x=driver_dnf_ratio.index,height=driver_dnf_ratio,align='center',width=0.5)\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('Drivers')\n",
    "plt.ylabel('Driver DNF ratio')\n",
    "plt.title('DNFs ratio due to Driver error')\n",
    "for bar in bars.patches:\n",
    "    yval = bar.get_height()\n",
    "    plt.text(bar.get_x()-0.1,yval+0.15,f'{round(yval,1)}',fontdict=font)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dnf_by_constructor = data.groupby('constructor').sum()['constructor_dnf']\n",
    "constructor_race_entered = data.groupby('constructor').count()['constructor_dnf']\n",
    "constructor_dnf_ratio = (dnf_by_constructor*100/constructor_race_entered).sort_values(ascending=False)\n",
    "plt.figure(figsize=(30,10))\n",
    "bars = plt.bar(x=constructor_dnf_ratio.index,height=constructor_dnf_ratio,align='center',width=0.8)\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('F1 Teams')\n",
    "plt.ylabel('F1 Temas DNF ratio')\n",
    "plt.title('DNFs ratio due to F1 Team error')\n",
    "for bar in bars.patches:\n",
    "    yval = bar.get_height()\n",
    "    plt.text(bar.get_x()+0.21,yval+1,f'{round(yval,2)}',fontdict=font)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "driver_home_points_finish = data.loc[(data['position']<11)&(data['driver_home']==1)].groupby('driver').count()['position']\n",
    "total_home_races = data[data['driver_home']==1].groupby('driver').sum()['driver_home']\n",
    "driver_home_point_finish_ratio = (driver_home_points_finish*100/total_home_races).sort_values(ascending=False).fillna(0)\n",
    "plt.figure(figsize=(30,10))\n",
    "bars = plt.bar(x=driver_home_point_finish_ratio.index,height=driver_home_point_finish_ratio,align='center',width=0.8)\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('Drivers')\n",
    "plt.ylabel('percentage')\n",
    "plt.title('Drivers point finish percentage at home race')\n",
    "for bar in bars.patches:\n",
    "    yval = bar.get_height()\n",
    "    plt.text(bar.get_x(),yval+1,f'{round(yval,2)}',fontdict=font)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "driver_home_podium_finish = data.loc[(data['position']<4)&(data['driver_home']==1)].groupby('driver').count()['position']\n",
    "total_home_races = data[data['driver_home']==1].groupby('driver').sum()['driver_home']\n",
    "driver_home_podium_finish_ratio = (driver_home_podium_finish*100/total_home_races).sort_values(ascending=False).fillna(0)\n",
    "plt.figure(figsize=(30,10))\n",
    "bars = plt.bar(x=driver_home_podium_finish_ratio.index,height=driver_home_podium_finish_ratio,align='center',width=0.8)\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('Drivers')\n",
    "plt.ylabel('percentage')\n",
    "plt.title('Drivers podium finish percentage at home race')\n",
    "for bar in bars.patches:\n",
    "    yval = bar.get_height()\n",
    "    plt.text(bar.get_x(),yval+1,f'{round(yval,2)}',fontdict=font)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "constructor_home_points_finish = data.loc[(data['position']<11)&(data['constructor_home']==1)].groupby('constructor').count()['position']\n",
    "total_home_races = data[data['constructor_home']==1].groupby('constructor').sum()['constructor_home']\n",
    "constructor_home_point_finish_ratio = (constructor_home_points_finish*100/total_home_races).sort_values(ascending=False).fillna(0)\n",
    "plt.figure(figsize=(30,10))\n",
    "bars = plt.bar(x=constructor_home_point_finish_ratio.index,height=constructor_home_point_finish_ratio,align='center',width=0.8)\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('F1 Teams')\n",
    "plt.ylabel('percentage')\n",
    "plt.title('F1 Teams points finish percentage at home race')\n",
    "for bar in bars.patches:\n",
    "    yval = bar.get_height()\n",
    "    plt.text(bar.get_x()+0.2,yval+1,f'{round(yval,2)}',fontdict=font)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "constructor_home_points_finish = data.loc[(data['position']<4)&(data['constructor_home']==1)].groupby('constructor').count()['position']\n",
    "total_home_races = data[data['constructor_home']==1].groupby('constructor').sum()['constructor_home']\n",
    "constructor_home_point_finish_ratio = (constructor_home_points_finish*100/total_home_races).sort_values(ascending=False).fillna(0)\n",
    "plt.figure(figsize=(30,10))\n",
    "bars = plt.bar(x=constructor_home_point_finish_ratio.index,height=constructor_home_point_finish_ratio,align='center',width=0.8)\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('F1 Teams')\n",
    "plt.ylabel('percentage')\n",
    "plt.title('F1 Teams podium finish percentage at home race')\n",
    "for bar in bars.patches:\n",
    "    yval = bar.get_height()\n",
    "    plt.text(bar.get_x()+0.2,yval+1,f'{round(yval,2)}',fontdict=font)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>year</th>\n",
       "      <th>date</th>\n",
       "      <th>quali_pos</th>\n",
       "      <th>statusId</th>\n",
       "      <th>position</th>\n",
       "      <th>dob</th>\n",
       "      <th>driver_nationality</th>\n",
       "      <th>constructor</th>\n",
       "      <th>constructor_nationality</th>\n",
       "      <th>GP_name</th>\n",
       "      <th>country</th>\n",
       "      <th>driver</th>\n",
       "      <th>age_at_gp_in_days</th>\n",
       "      <th>driver_home</th>\n",
       "      <th>constructor_home</th>\n",
       "      <th>driver_dnf</th>\n",
       "      <th>constructor_dnf</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2011</td>\n",
       "      <td>2011-03-27</td>\n",
       "      <td>18</td>\n",
       "      <td>11</td>\n",
       "      <td>18</td>\n",
       "      <td>1977-05-10</td>\n",
       "      <td>Ger</td>\n",
       "      <td>Alpine F1</td>\n",
       "      <td>Fre</td>\n",
       "      <td>Albert Park Grand Prix Circuit</td>\n",
       "      <td>Aus</td>\n",
       "      <td>Nick Heidfeld</td>\n",
       "      <td>12374</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2010</td>\n",
       "      <td>2010-03-28</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>1984-12-07</td>\n",
       "      <td>Pol</td>\n",
       "      <td>Alpine F1</td>\n",
       "      <td>Fre</td>\n",
       "      <td>Albert Park Grand Prix Circuit</td>\n",
       "      <td>Aus</td>\n",
       "      <td>Robert Kubica</td>\n",
       "      <td>9242</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2017</td>\n",
       "      <td>2017-03-26</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>1987-08-19</td>\n",
       "      <td>Ger</td>\n",
       "      <td>Alpine F1</td>\n",
       "      <td>Fre</td>\n",
       "      <td>Albert Park Grand Prix Circuit</td>\n",
       "      <td>Aus</td>\n",
       "      <td>Nico Hülkenberg</td>\n",
       "      <td>10812</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2018</td>\n",
       "      <td>2018-03-25</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>1987-08-19</td>\n",
       "      <td>Ger</td>\n",
       "      <td>Alpine F1</td>\n",
       "      <td>Fre</td>\n",
       "      <td>Albert Park Grand Prix Circuit</td>\n",
       "      <td>Aus</td>\n",
       "      <td>Nico Hülkenberg</td>\n",
       "      <td>11176</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2019</td>\n",
       "      <td>2019-03-17</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>1987-08-19</td>\n",
       "      <td>Ger</td>\n",
       "      <td>Alpine F1</td>\n",
       "      <td>Fre</td>\n",
       "      <td>Albert Park Grand Prix Circuit</td>\n",
       "      <td>Aus</td>\n",
       "      <td>Nico Hülkenberg</td>\n",
       "      <td>11533</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    year       date  quali_pos  statusId  position        dob  \\\n",
       "26  2011 2011-03-27         18        11        18 1977-05-10   \n",
       "30  2010 2010-03-28          9         1         9 1984-12-07   \n",
       "34  2017 2017-03-26         11        11        12 1987-08-19   \n",
       "35  2018 2018-03-25          7         1         8 1987-08-19   \n",
       "36  2019 2019-03-17         11        11        11 1987-08-19   \n",
       "\n",
       "   driver_nationality constructor constructor_nationality  \\\n",
       "26                Ger   Alpine F1                     Fre   \n",
       "30                Pol   Alpine F1                     Fre   \n",
       "34                Ger   Alpine F1                     Fre   \n",
       "35                Ger   Alpine F1                     Fre   \n",
       "36                Ger   Alpine F1                     Fre   \n",
       "\n",
       "                           GP_name country           driver age_at_gp_in_days  \\\n",
       "26  Albert Park Grand Prix Circuit     Aus    Nick Heidfeld             12374   \n",
       "30  Albert Park Grand Prix Circuit     Aus    Robert Kubica              9242   \n",
       "34  Albert Park Grand Prix Circuit     Aus  Nico Hülkenberg             10812   \n",
       "35  Albert Park Grand Prix Circuit     Aus  Nico Hülkenberg             11176   \n",
       "36  Albert Park Grand Prix Circuit     Aus  Nico Hülkenberg             11533   \n",
       "\n",
       "    driver_home  constructor_home  driver_dnf  constructor_dnf  \n",
       "26            0                 0           0                1  \n",
       "30            0                 0           0                0  \n",
       "34            0                 0           0                1  \n",
       "35            0                 0           0                0  \n",
       "36            0                 0           0                1  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.to_csv('./data_f1/data_filtered.csv', index = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analysis dataset only for 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "data2021 = df5[df5['year']==2021]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      raceId  year  round  circuitId                 name_x        date  \\\n",
      "1224    1052  2021      1          3     Bahrain Grand Prix  2021-03-28   \n",
      "1227    1052  2021      1          3     Bahrain Grand Prix  2021-03-28   \n",
      "1252    1052  2021      1          3     Bahrain Grand Prix  2021-03-28   \n",
      "1263    1052  2021      1          3     Bahrain Grand Prix  2021-03-28   \n",
      "1295    1052  2021      1          3     Bahrain Grand Prix  2021-03-28   \n",
      "...      ...   ...    ...        ...                    ...         ...   \n",
      "8624    1054  2021      3         75  Portuguese Grand Prix  2021-05-02   \n",
      "8627    1054  2021      3         75  Portuguese Grand Prix  2021-05-02   \n",
      "8628    1054  2021      3         75  Portuguese Grand Prix  2021-05-02   \n",
      "8633    1054  2021      3         75  Portuguese Grand Prix  2021-05-02   \n",
      "8634    1054  2021      3         75  Portuguese Grand Prix  2021-05-02   \n",
      "\n",
      "        time_x                                              url_x  resultId  \\\n",
      "1224  15:00:00  https://en.wikipedia.org/wiki/2021_Bahrain_Gra...     24979   \n",
      "1227  15:00:00  https://en.wikipedia.org/wiki/2021_Bahrain_Gra...     24983   \n",
      "1252  15:00:00  https://en.wikipedia.org/wiki/2021_Bahrain_Gra...     24972   \n",
      "1263  15:00:00  https://en.wikipedia.org/wiki/2021_Bahrain_Gra...     24969   \n",
      "1295  15:00:00  https://en.wikipedia.org/wiki/2021_Bahrain_Gra...     24973   \n",
      "...        ...                                                ...       ...   \n",
      "8624  14:00:00  http://en.wikipedia.org/wiki/2021_Portuguese_G...     25017   \n",
      "8627  14:00:00  http://en.wikipedia.org/wiki/2021_Portuguese_G...     25022   \n",
      "8628  14:00:00  http://en.wikipedia.org/wiki/2021_Portuguese_G...     25024   \n",
      "8633  14:00:00  http://en.wikipedia.org/wiki/2021_Portuguese_G...     25015   \n",
      "8634  14:00:00  http://en.wikipedia.org/wiki/2021_Portuguese_G...     25020   \n",
      "\n",
      "      driverId  ...  nationality_y  \\\n",
      "1224       847  ...        British   \n",
      "1227       849  ...        British   \n",
      "1252       817  ...        British   \n",
      "1263       846  ...        British   \n",
      "1295       832  ...        Italian   \n",
      "...        ...  ...            ...   \n",
      "8624       841  ...          Swiss   \n",
      "8627       854  ...       American   \n",
      "8628       853  ...       American   \n",
      "8633       842  ...        Italian   \n",
      "8634       852  ...        Italian   \n",
      "\n",
      "                                                  url_x  circuitRef  \\\n",
      "1224  http://en.wikipedia.org/wiki/Williams_Grand_Pr...     bahrain   \n",
      "1227  http://en.wikipedia.org/wiki/Williams_Grand_Pr...     bahrain   \n",
      "1252               http://en.wikipedia.org/wiki/McLaren     bahrain   \n",
      "1263               http://en.wikipedia.org/wiki/McLaren     bahrain   \n",
      "1295      http://en.wikipedia.org/wiki/Scuderia_Ferrari     bahrain   \n",
      "...                                                 ...         ...   \n",
      "8624  http://en.wikipedia.org/wiki/Alfa_Romeo_in_For...    portimao   \n",
      "8627          http://en.wikipedia.org/wiki/Haas_F1_Team    portimao   \n",
      "8628          http://en.wikipedia.org/wiki/Haas_F1_Team    portimao   \n",
      "8633   http://en.wikipedia.org/wiki/Scuderia_AlphaTauri    portimao   \n",
      "8634   http://en.wikipedia.org/wiki/Scuderia_AlphaTauri    portimao   \n",
      "\n",
      "                                    name  location   country      lat  \\\n",
      "1224       Bahrain International Circuit    Sakhir   Bahrain  26.0325   \n",
      "1227       Bahrain International Circuit    Sakhir   Bahrain  26.0325   \n",
      "1252       Bahrain International Circuit    Sakhir   Bahrain  26.0325   \n",
      "1263       Bahrain International Circuit    Sakhir   Bahrain  26.0325   \n",
      "1295       Bahrain International Circuit    Sakhir   Bahrain  26.0325   \n",
      "...                                  ...       ...       ...      ...   \n",
      "8624  Autódromo Internacional do Algarve  Portimão  Portugal  37.2270   \n",
      "8627  Autódromo Internacional do Algarve  Portimão  Portugal  37.2270   \n",
      "8628  Autódromo Internacional do Algarve  Portimão  Portugal  37.2270   \n",
      "8633  Autódromo Internacional do Algarve  Portimão  Portugal  37.2270   \n",
      "8634  Autódromo Internacional do Algarve  Portimão  Portugal  37.2270   \n",
      "\n",
      "          lng  alt                                              url_y  \n",
      "1224  50.5106    7  http://en.wikipedia.org/wiki/Bahrain_Internati...  \n",
      "1227  50.5106    7  http://en.wikipedia.org/wiki/Bahrain_Internati...  \n",
      "1252  50.5106    7  http://en.wikipedia.org/wiki/Bahrain_Internati...  \n",
      "1263  50.5106    7  http://en.wikipedia.org/wiki/Bahrain_Internati...  \n",
      "1295  50.5106    7  http://en.wikipedia.org/wiki/Bahrain_Internati...  \n",
      "...       ...  ...                                                ...  \n",
      "8624  -8.6267  108  http://en.wikipedia.org/wiki/Algarve_Internati...  \n",
      "8627  -8.6267  108  http://en.wikipedia.org/wiki/Algarve_Internati...  \n",
      "8628  -8.6267  108  http://en.wikipedia.org/wiki/Algarve_Internati...  \n",
      "8633  -8.6267  108  http://en.wikipedia.org/wiki/Algarve_Internati...  \n",
      "8634  -8.6267  108  http://en.wikipedia.org/wiki/Algarve_Internati...  \n",
      "\n",
      "[219 rows x 51 columns]\n"
     ]
    }
   ],
   "source": [
    "print(data2021)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "#reasons for DNF(did not finish)\n",
    "data2021['driver_dnf'] = data2021['statusId'].apply(lambda x: 1 if x in [3,4,20,29,31,41,68,73,81,97,82,104,107,130,137] else 0)\n",
    "data2021['constructor_dnf'] = data2021['statusId'].apply(lambda x: 1 if x not in [3,4,20,29,31,41,68,73,81,97,82,104,107,130,137,1] else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['raceId',\n",
       " 'year',\n",
       " 'round',\n",
       " 'circuitId',\n",
       " 'name_x',\n",
       " 'date',\n",
       " 'time_x',\n",
       " 'url_x',\n",
       " 'resultId',\n",
       " 'driverId',\n",
       " 'constructorId',\n",
       " 'number_x',\n",
       " 'quali_pos',\n",
       " 'position_x',\n",
       " 'positionText',\n",
       " 'positionOrder',\n",
       " 'points',\n",
       " 'laps',\n",
       " 'time_y',\n",
       " 'milliseconds',\n",
       " 'fastestLap',\n",
       " 'rank',\n",
       " 'fastestLapTime',\n",
       " 'fastestLapSpeed',\n",
       " 'statusId',\n",
       " 'qualifyId',\n",
       " 'number_y',\n",
       " 'position',\n",
       " 'q1',\n",
       " 'q2',\n",
       " 'q3',\n",
       " 'driverRef',\n",
       " 'number',\n",
       " 'code',\n",
       " 'forename',\n",
       " 'surname',\n",
       " 'dob',\n",
       " 'driver_nationality',\n",
       " 'url_y',\n",
       " 'constructorRef',\n",
       " 'constructor',\n",
       " 'constructor_nationality',\n",
       " 'url_x',\n",
       " 'circuitRef',\n",
       " 'GP_name',\n",
       " 'location',\n",
       " 'country',\n",
       " 'lat',\n",
       " 'lng',\n",
       " 'alt',\n",
       " 'url_y',\n",
       " 'driver_dnf',\n",
       " 'constructor_dnf']"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(data2021.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "#rename the columns\n",
    "data2021.rename(columns={'name':'GP_name','position_y':'position','grid':'quali_pos','name_y':'constructor','nationality_x':'driver_nationality','nationality_y':'constructor_nationality'},inplace=True)\n",
    "data2021['driver'] = data2021['forename']+' '+data2021['surname']\n",
    "data2021['date'] = pd.to_datetime(data2021['date'])\n",
    "data2021['dob'] = pd.to_datetime(data2021['dob'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Some of the constructors changed their name over the year so replacing old names with current name\n",
    "data2021['constructor'] = data2021['constructor'].apply(lambda x: 'Aston Martin' if x=='Force India' else x)\n",
    "data2021['constructor'] = data2021['constructor'].apply(lambda x: 'Aston Martin' if x=='Racing Point' else x)\n",
    "data2021['constructor'] = data2021['constructor'].apply(lambda x: 'Alfa Romeo' if x=='Sauber' else x)\n",
    "data2021['constructor'] = data2021['constructor'].apply(lambda x: 'Alpine F1' if x=='Lotus F1' else x)\n",
    "data2021['constructor'] = data2021['constructor'].apply(lambda x: 'Alpine F1' if x=='Renault' else x)\n",
    "data2021['constructor'] = data2021['constructor'].apply(lambda x: 'Alpine F1' if x=='Alpine F1 Team' else x)\n",
    "data2021['constructor'] = data2021['constructor'].apply(lambda x: 'AlphaTauri' if x=='Toro Rosso' else x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "data2021['driver_nationality'] = data2021['driver_nationality'].apply(lambda x: str(x)[:3])\n",
    "data2021['constructor_nationality'] = data2021['constructor_nationality'].apply(lambda x: str(x)[:3])\n",
    "data2021['country'] = data2021['country'].apply(lambda x: 'Bri' if x=='UK' else x)\n",
    "data2021['country'] = data2021['country'].apply(lambda x: 'Ame' if x=='USA' else x)\n",
    "data2021['country'] = data2021['country'].apply(lambda x: 'Fre' if x=='Fra' else x)\n",
    "data2021['country'] = data2021['country'].apply(lambda x: str(x)[:3])\n",
    "data2021['driver_home'] = data2021['driver_nationality'] == data2021['country']\n",
    "data2021['constructor_home'] = data2021['constructor_nationality'] == data2021['country']\n",
    "data2021['driver_home'] = data2021['driver_home'].apply(lambda x: int(x))\n",
    "data2021['constructor_home'] = data2021['constructor_home'].apply(lambda x: int(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "data2021.to_csv('./data_f1/data_filtered_2021.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      year       date  quali_pos  statusId  position        dob  \\\n",
      "1224  2021 2021-03-28         15        11        15 1998-02-15   \n",
      "1227  2021 2021-03-28         17        31        17 1995-06-29   \n",
      "1252  2021 2021-03-28          6         1         6 1989-07-01   \n",
      "1263  2021 2021-03-28          7         1         7 1999-11-13   \n",
      "1295  2021 2021-03-28          8         1         8 1994-09-01   \n",
      "...    ...        ...        ...       ...       ...        ...   \n",
      "8624  2021 2021-05-02         12        11        12 1993-12-14   \n",
      "8627  2021 2021-05-02         19        12        19 1999-03-22   \n",
      "8628  2021 2021-05-02         20        12        20 1999-03-02   \n",
      "8633  2021 2021-05-02          9         1         9 1996-02-07   \n",
      "8634  2021 2021-05-02         14        11        14 2000-05-11   \n",
      "\n",
      "     driver_nationality   constructor constructor_nationality  \\\n",
      "1224                Bri      Williams                     Bri   \n",
      "1227                Can      Williams                     Bri   \n",
      "1252                Aus       McLaren                     Bri   \n",
      "1263                Bri       McLaren                     Bri   \n",
      "1295                Spa       Ferrari                     Ita   \n",
      "...                 ...           ...                     ...   \n",
      "8624                Ita    Alfa Romeo                     Swi   \n",
      "8627                Ger  Haas F1 Team                     Ame   \n",
      "8628                Rus  Haas F1 Team                     Ame   \n",
      "8633                Fre    AlphaTauri                     Ita   \n",
      "8634                Jap    AlphaTauri                     Ita   \n",
      "\n",
      "                                 GP_name country              driver  \\\n",
      "1224       Bahrain International Circuit     Bah      George Russell   \n",
      "1227       Bahrain International Circuit     Bah     Nicholas Latifi   \n",
      "1252       Bahrain International Circuit     Bah    Daniel Ricciardo   \n",
      "1263       Bahrain International Circuit     Bah        Lando Norris   \n",
      "1295       Bahrain International Circuit     Bah        Carlos Sainz   \n",
      "...                                  ...     ...                 ...   \n",
      "8624  Autódromo Internacional do Algarve     Por  Antonio Giovinazzi   \n",
      "8627  Autódromo Internacional do Algarve     Por     Mick Schumacher   \n",
      "8628  Autódromo Internacional do Algarve     Por      Nikita Mazepin   \n",
      "8633  Autódromo Internacional do Algarve     Por        Pierre Gasly   \n",
      "8634  Autódromo Internacional do Algarve     Por        Yuki Tsunoda   \n",
      "\n",
      "     age_at_gp_in_days  driver_home  constructor_home  driver_dnf  \\\n",
      "1224              8442            0                 0           0   \n",
      "1227              9404            0                 0           1   \n",
      "1252             11593            0                 0           0   \n",
      "1263              7806            0                 0           0   \n",
      "1295              9705            0                 0           0   \n",
      "...                ...          ...               ...         ...   \n",
      "8624             10001            0                 0           0   \n",
      "8627              8077            0                 0           0   \n",
      "8628              8097            0                 0           0   \n",
      "8633              9216            0                 0           0   \n",
      "8634              7661            0                 0           0   \n",
      "\n",
      "      constructor_dnf  \n",
      "1224                1  \n",
      "1227                0  \n",
      "1252                0  \n",
      "1263                0  \n",
      "1295                0  \n",
      "...               ...  \n",
      "8624                1  \n",
      "8627                1  \n",
      "8628                1  \n",
      "8633                0  \n",
      "8634                1  \n",
      "\n",
      "[219 rows x 17 columns]\n"
     ]
    }
   ],
   "source": [
    "print(data2021)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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sW3rhhRdKPUKDtM8++8yzrPoJJ5xgWfV6xp5hFLLbbrvl6KOPzoknnli1jmzfvn0zevTo0g5Wzz388MMZOXJk3n333Wy33XbZfvvt07Zt20yfPj19+vTJI488UuoR66X5rYVdUVGRhx9+uATT1H8jRozIzTffnPfeey8dOnSoVobJrXa/+MUv8u6776ZTp07V3jT7IGXBPvnkk4wePTprrbVWunfvng8//DDPPvtsBgwYUOrR6qVnn312gbc7y33Bpk+fnr/+9a/58Y9/nJVWWikTJkzIv/71r2yyySalHq3eO+644/L2229n8803r/bfOPu+fnsffvihvdZqUVlZmVtuuSVPPfVUkmSjjTbKTjvtVO2MWeblve+388EHHyzwdvuXLtgtt9xSVVgn3yyReNNNN+XMM88s4VT13z//+c8cc8wxmTp1aiorK9O6deucddZZWWONNUo9Wr2266675tprr80JJ5yQ5ZZbLu3bt8/IkSNzzz33lHq0em306NE599xz89Of/jSVlZX5+9//niOPPDK/+MUvSj1avXbwwQfntddey4Ybbljtfa89nBassrIy99xzT95///0MGjQoH330UT755JOsvfbapR6tXhswYEAOOeSQnH322VXLqtt/rf5RhlHIDjvsUHXVydx/qbfbbruMGjWqtIPVc8ccc0x23HHH+a5P/NRTT2XDDTcswVSUq5NOOimnnHJKqcdocGr6QMUHKSwuM2fOrFoeZuWVV84SSyxR2oHqsalTp6Zly5b57LPP5nu7qyZqV9NeJpbCXjCrInx7s2fPTp8+ffLggw+WehS+Rz744IP85z//yUYbbZSvvvoqX3/9teXoF8Ls2bPz6aefZvbs2VXHlP0LZ+rUqUniz9lC+uCDD9K2bdt8/fXXue666zJlypT8+te/zoorrljq0eq9CRMm5OWXX06SrL322mnXrl2JJ6r/aroix5L1C3bSSSelUaNGefrpp/PAAw/k888/z957750777yz1KPVa9tvv33uuuuuvPPOO1XLqt95552uDKtnLJNIIW3atMm7775btf7/gw8+6C/ihTB8+PAab1OEzWtuQfinP/1pvrdvtdVWdTxRwzD3w+LDDjtsvh8Y+7B4wTp16pSxY8fmP//5T3bYYYdMmjQpX375ZanHqvfmtxl28+bN89xzz5V6tHrtmWeeybHHHptOnTqlsrIyH330UYYPH25T5xocccQRueKKKzJw4MBUVFS48rWAuaXX3P+utWjRopTjNBjDhg2rWhUhSdZYY40ceeSRyrAFaNy4cVZeeWVX0BUwffr0XHvttfnoo49y2mmn5Z133snbb7+dLbbYotSj1Wu33XZbbr311nz++ecZM2ZMPv7445x00km5/vrrSz1avXbjjTfmoosuynLLLVe1H1FiVYSaXHvttQu83ZXWC/bfJxg6EWfhPffcc1lzzTXz85//PKNGjcrVV1+dPfbYwwmbtdh+++2deFjAuHHjctddd1Wt8tK6dWt7vi4Ey6o3DMowCjnppJMybNiw/Pvf/86mm26aFVZYIeecc06px6q3unXrNt9N1m1CuWB///vfs+GGG+Yvf/nLfG9Xhs2fD4u/m4svvjivvPJK3n777eywww6ZNWtWjjrqqNxyyy2lHq1esxl2McOHD88111yTVVZZJck3V58cccQRGTlyZIknq5+uuOKKVFZW5sYbb/ThekH/+te/cvTRR1ftB9OmTZsMHz48q622Woknq9+mT58+z9Iwlvqr3RdffJE+ffpk7bXXTrNmzaqO2xdxwYYOHZouXbpU7dnRoUOHHHLIIcqwWtx00025/fbbs/POOyf55sOoSZMmlXiq+u/666/Pgw8+mDZt2pR6lAZh7skkb7/9dl5++eWqZU3/8pe/ZK211irlaPWavf2+m5NPPjn33HNPXnvttVx33XXZcccdc8wxx+TGG28s9Wj1mhMPi2nSpElmz55d9TnmpEmTqp0swfxddtllVV83b948F154YT788MMSTsT8KMMo7Lrrrsu0adMyZ86ctGzZMu+9916pR6q3bD5ZzJAhQ5LEevXf0hVXXJEk9qAr6M9//nPuvvvuqqUTOnTo4MqwhWQz7G9v1qxZVUVY8s3Zis66W7CKior89re/9aFJQSeeeGKOPfbY/OxnP0vyzYcEw4YNU/jXwqoIxRxyyCGlHqFBevfdd3PBBRfkvvvuS5I0a9YsdjeoXdOmTavtCfP111+XcJqGo2PHjmnVqlWpx2gw5l7NtOuuu2bkyJFVyyMOHjw4v/3tb0s5Wr029ySIm266Kck322wkyT333DPfE4eprkmTJqmoqMiYMWPy61//OjvttFPuuOOOUo9V7znxsJjdd989gwYNysSJE3P++efnwQcfzKGHHlrqseq9LbfcMltvvXVOP/30qpPABg0aZJnEekYZRiFDhgzJXXfdlebNm1cdO+SQQ/yFUot33303HTt2TNOmTfPMM8/k9ddfz4ABA7L00kuXerR6bfLkybnkkkvy3HPPpaKiIuutt14GDRrk7MVa7LnnnvMsCzO/Y1S3xBJLpKKiouqXsmnTppV4ooahWbNmmTlzZtZcc82cffbZad++febMmVPqseq9rl275vjjj0///v2TfHNWbNeuXUs8Vf33k5/8JOPGjbOJcwHTpk2rKsKS5Kc//an/zi0EqyIUs8EGG1Tbw2n69OnV9iRi/po2bZqvvvqq6r3Iu+++W63kYf569OiRyy+/PF999VWeeOKJ/PGPf6y6aoeade7cObvvvns233zzan/OLPe3YJ9++mm1vJo2bZpPP/20hBPVb3OX83vyySer9p1PkqOOOirbb799jjzyyBJN1jC0aNEiV1xxRe69997ceOONmTNnjsJ/ITjxsJj+/funS5cuefrpp1NZWZlLL700q666aqnHqvdWW221rL/++vn1r3+dCy+8MD/84Q+dzFQPKcP4Vt566628+eabmTJlSrV9nKZOnZoZM2aUcLKG4eCDD86dd96Z//znPznxxBPTq1evHHHEEbnqqqtKPVq9dvjhh6d79+75wx/+kOSbD4sPO+ywXHfddaUdrJ6aMWNGpk+fnsmTJ+fzzz+v+st36tSpGT9+fImnq/+23XbbnHjiifniiy9y22235c4776xaboeanX322amsrMyJJ56Y6667Lh999FEuvvjiUo9V751yyim56aabcsMNNyRJunfvnl//+tclnqr+e+mll3Lvvfdm+eWXr7b0mqvFate5c+dccskl1c7I7ty5c4mnqt9mz56dP/7xj/OsikDt/ncPp/Hjx9vDaSEcfPDB2XffffPRRx/liCOOyAsvvGClhIVw5JFH5o477siPf/zj3Hrrrdlss82y0047lXqsem/55ZfP8ssvn1mzZvmQ+FsYMGBAdtxxx/Tu3TtJMmbMmAwcOLDEU9V/lZWVee6557L++usnSZ5//nkn0C2E888/P6NHj87pp5+edu3a5cMPP8w+++xT6rHqPSceFrfSSiulZcuWVScx2QO2dhUVFdl1112zxhpr5IADDsiRRx7pytd6qKJSRcm3MGbMmDz88MN55JFHqp1l16JFi/ziF7/IeuutV8Lp6r/tt98+d911V66++uosueSS2X333TNgwIBqZ0Yxr759+2b06NHVjvXr18+HnjW4/vrrc/3112fChAnp0KFDVRnWsmXL7Lzzztltt91KPGH998QTT+Rvf/tbkmSTTTbJxhtvXOKJ6r/rr78+e+65Z63H+D+zZ89Onz598uCDD5Z6lAalsrIyY8eOne8vYzYRr93nn3+eiy66qOpq6/XXXz+DBw9O69atSz1avbbzzjvntttuK/UYDc52221XtYfT3Pe73sMtnMmTJ+ell15KZWVl1llnnSy77LKlHqlB+eyzz/Lxxx9njTXWKPUolKHKysp8/PHHmTRpUsaOHZvkmysTf/KTn5R4svrvlVdeyXHHHZepU6emsrIySy+9dM4444x06dKl1KNRhmbOnJmbbropzz33XJL/O/HQ1dYLdsMNN+Tiiy/OcsstV22vMO/fFuy/P9+dMGFCDj300Lz66qt56aWXSjsY1bgyjG9lyy23zJZbbpm///3v82w4OfcvF2rWpEmTjB49OnfffXfVxoouba/dxhtvnPvuuy/bbrttkm/26dhkk01KPFX9teeee2bPPffMDTfckN13373U4zRIP/7xj6uWJ/rxj39c6nEahLvvvnue4uuuu+5Shi1A48aNs/LKKzvL7luqqKjIqaee6pexglq3bp0TTjih1GM0OGuuuWYOOOCAbLPNNtWWCd9qq61KOFX9Zw+n4mbOnJmll146s2fPzltvvZW33nprnt+/qG733XfPZZddlq+//joDBw5M27Zt061btxx33HGlHq1eOv3003P88cfngAMOmO/tc/d4Yl4VFRXZf//9c++99ypxvqWuXbvmnnvuyZQpU5LEfnUL6U9/+lPOOeecTJw4MZWVlamsrExFRUWef/75Uo9Wr918883Za6+9qi376oTN2o0YMSIPPvigrUm+pSuvvLLq6/bt22fEiBF54YUXSjgR86MMo5Azzjhjng0Af/e739kUsBZnnnlmbrnllhxwwAHp3Llz3nvvvarLtanZbbfdluuvvz5HHXVUKioqMnv27DRr1iy33HKLN4ALsPvuu+df//pX3nzzzcycObPq+IABA0o3VANw++2355JLLsnPfvazVFZW5ne/+10OOuig7LjjjqUerV4aPXp0Ro8enffff7/ahylffvmlK00WwhdffJE+ffpk7bXXrrbcnw+gFsyeYcXttddeufDCC6v2K/38889z+OGH55prrinxZPXbzJkz06ZNmzzzzDPVjivDFsweTsX8/ve/zwMPPJAf/ehH1c7IVoYt2JQpU9KyZcvcfvvtGTBgQIYMGZJ+/fqVeqx6a+5yuXvvvXeJJ2mYvBcpZsqUKbn44ovz97//Pck3e0sOGjRIKVaL3//+97n88svt2/QtOWGzmI4dO/p3soD27dvn0UcfzRtvvFFtKyHv3+oXZRjfygsvvJAXXnghkyZNyrXXXlt1fOrUqTbDXgg/+tGPqp2N3blz5+y///4lnKhhcCZFMRdffHGeeeaZvPXWW9lss83y+OOPZ/3111eG1eLqq6/OXXfdVXUW1OTJk/OrX/1KGVaDbt26pV27dpk8eXK1D1NatGiR1VdfvYSTNQyHHHJIqUdokOwZVtzkyZOrirDkmyvFJk6cWMKJGgb7NRVjD6dixowZkwcffNAyTt/S7NmzM2HChDzwwAM59NBDSz1OvTd335wNNtigxJM0TN6LFHPcccdltdVWy4UXXpgkGTVqVIYOHWqv4Vq0bdtWEfYtOGGzmLmf83bu3Dm77757Nt9882rvRf77CjvmdeKJJ+arr77KM888k5122ikPPfRQ1lprrVKPxf9QhvGtzJo1K9OmTcvs2bPz5ZdfVh1v2bJl/vCHP5RwsobhnXfeyXnnnZc333yz2lkCDz/8cAmnqv8qKytzzz335P3338+gQYPy0Ucf5ZNPPnEWXi0eeuihjBo1KgMGDMiZZ56ZTz/9NEcddVSpx6r32rRpkxYtWlR936JFC8sDLECnTp3SqVOndO/efZ4PU37/+9/7M1eLxx57bJ6Mfv/73/tgqhauYiquUaNG1Zbm/OCDD2zsvBDefvvtnHzyyZk4cWJGjx6d1157LY888kgOOuigUo9WrzVq1Cg777xzdt5551KP0qB07tw5s2bNUoZ9SwcddFD22WefrL/++ll77bXz3nvvZaWVVir1WPWe31GL8V6kmHfffTcXXXRR1feDBw+uukqRmnXt2jWHHnpottxyy2p/N7hCff6csFnM3M95l19++Sy//PKZNWtWZs2aVeKpGo4XXngh9957b/r165fBgwdnr732yn777VfqsfgfyjC+lQ022CAbbLBBtt9++3Tq1CnTp0+vdhYUCzZ06NAMGTIkZ5xxRkaMGJGRI0dmzpw5pR6r3jv55JPTqFGjPP300xk0aFCaN2+eU045JXfeeWepR6vXllxyyTRq1ChNmjTJ1KlT07Zt23z00UelHqve++EPf5idd945P//5z1NRUZGHH344q6++etVZUs6Gmr8nn3xynmOPP/64MqwWciumU6dOee2116o2re/evXvWWGONEk/VMBx66KH59a9/nR49eqSysjLPPfdcTj311FKPVS/dfPPN2WCDDbLqqqtm2LBhOfroo3PiiScmSdZYY40ceeSRyrAa1LY0nSsnFqxZs2YZMGBANtxww2ofetrvb8G23Xbbqj2Gk29Kxf/+0J358ztqMZ06dUqSTJw4sVqJyIIttdRSGTt2bLp3757km73nl1pqqRJPVf99+eWXadasWZ544olqx5Vh8zf3hM1bb7211KM0KIMHDy71CA3a3P+WNWvWLOPHj0+bNm3yySeflHgq/pcyjEImTJiQ/fbbL9OmTcujjz6a1157LbfccktOPvnkUo9Wr82YMSMbbrhhkm/+cj744IMzcOBAy2TVYty4cbnrrruqlvdr3bq1s1MWQteuXfPFF19kp512ysCBA9O8efN069at1GPVez/84Q/zwx/+sOr7n//850lS7WpY/s8f//jH3HzzzXn33Xerffj55ZdfZr311ivhZPXb3Nzee+89uRVw/fXX5/bbb0/v3r2TJEcddVR23nnn7L777iWerP7r2bNnRo4cmZdeeinJN8sVLbvssiWeqn7q379/TjvttJx11lmZPn36PFekN27cuEST1X/2PfxuevXqZW+1As4+++wcdNBBWXLJJbPvvvvm9ddfz9ChQ111Ugu/oxbz8MMPZ/jw4ZkwYUKWXXbZfPjhh1l11VVz3333lXq0eu2UU07J0UcfnalTp6aysjKtW7fOWWedVeqx6j3LNX873bp1m+/KB5WVlfadXwj2GC5m8803zxdffJF99tknAwcOTEVFhe026iFlGIWcccYZueaaa3LggQcm+ebs2LlnZ1Ozpk2bZs6cOVlxxRVz4403pkOHDj5gXwhNmjTJ7Nmzq97MTJo0qdpm4szf3HJ6l112yaabbpqpU6da7m8hzD0baurUqUm+WQaWmvXr1y89e/bMeeedlyOOOKLqeIsWLbLMMsuUbrB6Tm7fzR133JHbbrstzZs3T5Lst99++eUvf6kMq8XMmTNz77335s0330zyzV6m/htXsxYtWuS0005L8s0Suu+++27Ve5EHH3ww7dq1K+V49drcKybee++9tG/fPksuuWSS5Kuvvsqnn35aytEahO233z4zZ87MO++8kyRZeeWVs8QSS5R2qAbgiSeeyNFHH50///nP6dSpUy6++OLsuuuuyrBa+B21mAsvvDC33npr9tprr9x99915+umnc88995R6rHpvjTXWyD333ON3rW/p448/zmmnnVZV4nTv3j3HH398OnbsWOLJ6if7zn83kyZNssdwAYMGDUqSbL311tliiy0yY8aMtGrVqsRT8b+UYRT2gx/8oNr3yonaHXfccZk+fXpOOOGEXHjhhXn66aczfPjwUo9V7+2+++4ZNGhQJk6cmPPPPz8PPvigTbG/pRVWWCHJN2eqPProo6Udpp57+eWXc9xxx1V9CNCyZcucccYZVZuMU12rVq3SqlWrnHfeefMsW6fUqVmTJk3SoUOHnHfeeUmSf//733n88cez/PLLW+5kIf33VTmu0Kndm2++mQMPPDDrrbdeunTpkiR59tlnc/nll+eyyy7Lj370oxJPWD/NLSBOOumkDBs2LP/+97+z6aabZoUVVsg555xT4unqv0MOOSS33HJL1feNGjXKIYccYqnrGrz11ltZddVV88wzz+TYY49Np06dUllZmY8++ijDhw9Pjx49Sj1ivTZ79uwkyaOPPpptttnGB1ALye+oxTRp0iRt2rTJnDlzMmfOnPzsZz/LGWecUeqx6r2ZM2fmoYceygcffJCvv/666rjl2RZs6NCh6du3by688MIkyT333JOhQ4dWLeVPdVOnTk3Lli3z2Wefzfd2v6cuWOPGje0xXNDzzz+fDz74oOo9SZKqVa6oH5RhFPKDH/wgzz//fCoqKjJr1qyMGDEiq666aqnHqvfmLq/TokULl7l/C/3790+XLl3y9NNPp7KyMpdeeqk/bwVVVlaWeoR677jjjstJJ51UtY792LFjM3ToUPub1GLEiBG57bbbLFu3kPbdd9+cfvrpWWmllfKf//wnv/rVr9KvX7/85S9/ybhx43LkkUeWesR6beDAgdlpp52q/ryNGTMmO+ywQ4mnqt9OO+20nHzyydl4442rHX/yySdzyimn5IYbbijRZPXfP//5z/znP//JsGHD8oMf/CBz5sxxJvtCmj17drU9r5o2bWqp6wW47rrrctppp2X48OG55pprssoqqyRJ3n777RxxxBEZOXJkiSes3zbffPNss802WWqppXLyySdn0qRJVVclUrP//h312GOPzdJLL+1Dz4Ww9NJL58svv0yPHj1y5JFHZtlll626Yp2aHXjggWnVqlW6dOlS7e8HFmzSpEnV3usOHDgw119/fQknqt+OOOKIXHHFFVVL1f335yBz9wWnZvYYLuaoo47Ke++9lzXWWKPqZM2KigplWD1TUemTUb6FWbNmZYkllsikSZNy+umn56mnnkplZWU23njjHH/88ZZgq8HYsWPz/vvvV/0HcMiQIVVnqBx44IFVa7Qzf8cdd1x23333rLnmmlXHLrroohx88MElnKphcmVY7QYMGJC777672rHtt98+d911V2kGaiD69euXW2+9tepDgGnTpuWXv/ylErEG/fr1q8rmggsuyOeff56TTjopM2fOzA477CC3hfDKK69UWyrmJz/5SYknqt+22WabPPjgg/O9bdttt80DDzxQxxM1DBdffHHuvffedOnSJS+99FJ++9vfZueddy71WA3GXnvtld12261q/80xY8bkhhtu8AFeDV599dV06dKl2t8Rc83vGPP67LPP0qpVqzRu3DjTp0/P1KlTLWlag4svvjjbbrttVl111cycOTP77LNPXn/99TRu3DjnnntuNtpoo1KPWK9NmzYtSy65ZCorK3PvvfdmypQp6devn89EatG3b9+MHj261GM0OHvuuWcGDhyYvn37JklGjx6dkSNH+vuUxWbSpElVewyvs8469hheCNtuu23uv/9+J5TUc64M41vp2bNnevXqlb59++acc87xL/hCuuiiizJs2LCq799+++2ceeaZmT59ei6//HJlWC3+9re/5ZVXXsnee+9dVSg+8sgjyrAanHbaaTVuFvvFF1+UYKKGpUePHjnxxBPTp0+fVFRU5P77788GG2yQV199NUmqlhdjXpatK+bpp5/Ovvvum+Sbqyb83bpwunbtavnSb6GysjIzZ86c5yzsGTNmVFvGg+oeeOCB3H333WnWrFkmT56cfffdVxn2LZxyyik58sgjc+qpp6aioiIdO3a0/NoC3H333enSpUu6du2a448/Pv3790+S3Hvvvf57txD+92SmuZyRPX8PPPBA1f4mc0/6euqpp/LOO+/kmGOOUYbV4r+vAtt+++1LOEnD0q1bt7z++utZffXVSz1Kg3LGGWfktNNOy5lnnpmKiop069bNakML6bXXXptn2TrL0teucePGadu2bWbMmJG33norb731luWaa7Haaqvlk08+Sfv27Us9CgugDONbuf/++/PQQw/l0ksvzTHHHJOtttoq/fr1yzrrrFPq0eq1qVOnVtuLY8UVV6z6hfbcc88t1VgNRtu2bTNixIgcddRReemll3L88cdb7m8BFvRhiQ9Savfaa68l+eZs2f/2j3/8IxUVFRkxYkQpxqr3LFv37ay++uoZPnx4OnTokHfffbdq6TqF9YJ169atqiysrKys+nr27NmZNWtW/vGPf5RyvHptu+22y8EHH5wTTzwxnTp1SpK8//77+d3vflf1gTvzatq0aZo1a5YkadOmjfcf39IPf/jD3HbbbVX7cLZo0aLEE9Vvxx9/fJJvSsSbbrqpavnS7t27Z5dddinlaA3Cyy+/XPX1jBkz8tRTT6VLly7KsBosscQSVX+P/u1vf0ufPn3SuHHjrLrqqk6SWIBddtklN998c7X3JMn/vS+Ze9U68/fcc8/lrrvuSqdOnaqdoOPK1wXr1KlTLr/88lKP0eAMHTo0r7/+elZbbbU0atSo6rgybMFuv/32jBgxIh9//HHWWGONvPTSS1l33XV9FlKLyZMnp0+fPll77bWr9h1O4t/desYyiRQ2fvz4PPjgg7n//vszceLE9OnTJ4cddlipx6qXttpqq/zpT3+a7229e/fOn//85zqeqGH572XrLrroojz55JOZMGGCdZ6hnnn11Vfz3HPPJbFsXW2++uqrjBgxIhMmTMiOO+6YNdZYI8k3G+6+++67PrhbSF9++WVuuumm3Hrrrendu3eOPfbYUo9Ur9144425+uqrM3369CTfnNW+995729tvAbp37161h2TyzdLX//29X24X7NNPP815552XCRMm5Oqrr86bb76ZF154ITvttFOpR6vXLrzwwhxyyCFV38+ePTtHH320k+i+pS+++CKHHXZYrrnmmlKPUi/tvPPO+d3vfpflllsu22yzTe6888507tw5yYKX1oXv4oMPPpjv8bkn6lBdTau+zHXCCSfU4TQNzy9+8Yvcf//9pR6jwenXr1/uuOOO7Lzzzhk1alTeeuutnH/++fOcMEx1zz777HyPb7DBBnU8CQviyjAK69ChQ3bccce0bt061157bW6//XZlWA1WWWWVPProo9l8882rHf/LX/6SlVdeuTRDNSC9evWq+vrggw9Oly5dct1115VuIMreo48+mjfeeCMzZsyoOjZ48OASTtQwdOnSJausskrefPPNdOzYsdTj1GtLLbVU9t9//3mOr7feellvvfVKMFHD8sUXX+T666/P3Xffnb59++aOO+6wR8dC2G233bLbbrtl6tSpSZKWLVuWeKL679JLL632/d57712iSRqmY489NgMHDqwqDVdaaaUcdthhyrBafPzxx7niiivy29/+NjNnzsyhhx5abe9cFk6zZs3y/vvvl3qMeuv444/PkCFDMnny5Oy5555VRdhjjz3mhKaF8OKLL+ZHP/pR1d+lU6dOzVtvvWXVnFpYDvzbsbLLd7Puuuvmzf+vvXuPy/n+/wf+uCophclptBxGLXPYhPBBaDPn6eA4MqdGREyiKBKiYWtymm0iwxxKR2drxgdbzqd85FRLk1ZSOl9dvz/69v510Xl4vS973P/qel9sD906vN+v5+v1fMbFqXVqoorp6uqiZs2aAIC8vDy0atUK9+7dE5xK/lj00gw8GUZVlpubixMnTiAyMhIXL15Er169MGjQIPTo0YMzYsrw4MEDfPHFF7CwsJAeLK5fv46LFy9i06ZNLIgRyYiXlxdycnJw7tw5jBgxAocPH0b79u2xYsUK0dFk6fjx41i+fDnq1q2L2bNnw9vbGw0aNEBiYiJcXV05Q4FeqtTUVGzduhVRUVGwt7eHg4MDateuLToWEZXB3t4e+/fvVzvlP2zYMISGhooNJnMqlQqurq4wMzPDuXPnYGVlhQkTJoiOJXvTpk2TPlapVIiLi8OAAQMwb948ganoTWVjY4OQkBCpuFNYWAh7e3tp/hqVbujQodLHubm5+PPPP9GyZUtERkYKTKV5itflBg4cKDqKrP3+++9wcnJCgwYN2JazCmbMmAFfX19s27YNZ8+eRZ06dVBQUIAtW7aIjiZLbJ+rWXgyjKpk7ty5+O9//4suXbpg6NChWLNmjbRbgMrWvHlzhIeHIywsDHFxcQCK2u54e3vz81cJly5dgo+PD+7evYv8/HwolUrUqlVLasdG9DJdvHgR4eHhGDp0KJydnTFx4kQ4OjqKjiVb/v7++OGHH5CRkYHPP/8cYWFhMDExwd9//40JEyawGEYvlbW1NYyMjGBnZwd9fX3s27dP7f2JEycKSkZEpalVqxbS0tKkhYFLly6xgF2O69evSx+PHz8eXl5esLCwQJcuXXD9+nW0bdtWYDr5K3lyU1tbG8bGxjypTq9MydmlAKClpYWCggKBiTTD80WI69evY+fOnYLSaBalUolTp04hIiICp0+fRufOnVkMq8DChQvh5+cHMzMztZlhVL7169cDKOrM1LVrV2RkZKBXr16CU8nXrl27ABStJZH8sRhGVdKrVy94e3uzrU416OrqYvjw4aJjaKSlS5fi66+/houLC/bv348DBw7g/v37omPJnp+fH6ZPn46aNWtiypQpuHXrFtzd3TFs2DDR0WRNT08PQFFrnUePHqFevXp4/Pix4FTypaWlJZ1ufeedd6QWO/Xr1+dp4SrIzs6Gvr6+6BiyN3nyZGnh6dmzZ4LTEFFFFixYACcnJ8THx2P06NFIS0uDv7+/6FiytXLlSrXXderUQVxcHFauXAmFQsHB9eVQKpVo3bo1jIyMABS1dQoJCUFgYCAOHjwoOB29iUxMTLB9+3aMGTMGALBz507pPpgqr23btrhy5YroGLL2+++/IyIiAr/++is6dOiACxcu4Pjx43x2qAQjIyN89NFHomNopPT0dCQlJcHAwAAGBga4ffs2N+VUYNmyZRg8eDA6duwoOgqVg8UwqhIbGxvREehfqnnz5lAqldDW1oa9vT1sbGwwd+5c0bFk7fTp03Bzc8PRo0dhbGyMgIAAjB07lsWwCvTp0wdPnz7F5MmTYWdnB4VCwUJ2OQoLC5Geno7CwkIoFAqkp6ejuANzYWGh4HTyd+HCBSxatAhZWVmIjo5GbGwsdu/ejSVLloiOJkszZ84UHeGNcOHCBSQmJkKpVErXeI9XOcVFWAMDA8FJNEPbtm2xY8cO3Lt3DyqVCi1btsSJEydgbm4uOposBQUFAShqf/V894i0tDQRkTRCZGQkvLy8oK+vjxYtWmDatGnw8PBA+/btsXr1atHx6A3l7e2NZcuWYePGjVAoFOjevTt8fHxEx5K9rVu3Sh8XFhbi+vXraNSokcBE8mZlZYWmTZti9OjRcHNzg6GhIaytrVkIq6Q2bdpg7ty56Nu3r1qbxE8++URgKvn75ptvEBISAhMTE2kjIjflVKxt27bYsGED7t27h379+mHQoEFo37696Fj0HBbDiEj29PX1kZeXhzZt2sDPzw+NGjXiInslFC9yRkdHY8CAAWxLVEmOjo7Q1dVF//790bdv31IXpOj/y8zMhJ2dnVQAK9kWkQOyK+br64sffvgBTk5OAABzc3PExMQITkVvsnnz5iEhIQHm5ubS6U2FQsFiWAVu3bqF+fPnSwV/IyMjrFy5EmZmZqKjyZ6Ojg5MTU2l176+vujfv7/ARPI3c+ZMbNiwATo6RY/rjx8/xtSpUxEcHCw4mTxt3LgRwcHBaN68Oa5fv45Ro0bh22+/hbW1tehoGuHgwYPo1asXDA0NsWHDBty4cQNOTk48AVCB+vXr4+uvvxYdQ+OUPNmvra2NPn368HdCOfr374/jx4/j4MGD0NbWxkcffcRnrCrIzc2Frq4uTp8+rXadxbDyHTx4EEePHlUrIFLFbG1tYWtriydPnuDIkSNYvXo1kpKScOTIEdHRqAQWw4hes5ycHDx8+BDvvvuu6Cgaw8/PD4WFhfDy8kJgYCCSkpKwbt060bFkr0+fPhgwYAD09PSwZMkSpKamsqhTCaNGjZIGX+vq6kJXVxe2trYchl2GEydOiI6g8Zo0aaL2mv3s6VW6du0aoqKiuJBSRYsXL8aCBQvQrVs3AMC5c+fg5eWF3bt3C06meYo3T1DZPv74Y7i4uODbb79FUlISnJycMH/+fNGxZKtGjRpo3rw5gKJd2S1atGAhrAo2bNiAgQMHIiYmBmfOnMHkyZOxZMkS7N27V3Q0WZs/fz4WLlyIOnXqAChqKbZy5Ur4+voKTiZvzs7O0seFhYXIysriM2o5Fi5cCA8PD5w7dw6RkZH46quvkJGRgaioKPTu3Zsn1SvA78fqMTMzQ0ZGBurXry86ikaKj4/H3bt38fDhQ7Rq1Up0HHoOi2FUbWyxU3UnTpzAqlWrkJ+fjxMnTuDmzZvw9/fHpk2bREeTNWNjY+njkjfPVD5XV1dMmTIFtWvXhra2NvT19bFhwwbRsWTr8ePHePToEXJycnDjxg1psS4zMxPZ2dmC09GbqkmTJrhw4QIUCgXy8/Oxfft23jDTK2VqaorHjx+zJVEVZWVlSYUwAOjatSuysrIEJtJcLMRWbOTIkcjPz8eMGTOQmJgIb29vWFhYiI4lW3///bda67WnT5+qvZ44caKIWBqj+JTwr7/+ipEjR6JPnz745ptvxIbSALdu3ZIKYQBQt25d3Lx5U2AizTB37lx4e3tDS0sLw4cPR2ZmJsaPH48pU6aIjiZbCoUC3bp1Q7du3ZCfn49Tp04hIiIC3t7eOHfunOh4spabm4t9+/bh9u3byM3Nla6zSFa+L774AjY2NjAzM0ONGjWk61y7LJ+fnx+OHTsGExMTDBo0CNOnT1f7PUHywGIYVQtb7FRPQEAA9u3bBwcHBwBF/YsTExMFp5KvoUOHlvt+eHj4a0qiuZKTk/Hf//4XeXl50jV+n5bu1KlTCA4Oxl9//YWVK1dKxTADAwN8+eWXgtPRm2rJkiVYvnw5Hj16BCsrK/To0QNeXl6iY8leRkYG1q1bJ7WUtLS0xIwZM9gOthLS0tIwePBgdOjQgQ+3VWBiYoL169dLczfDwsJgYmIiOJV8lXcPl5KS8hqTaJaSBRyVSoWHDx/C3Nwcly9fxuXLl1nUKcPIkSPVWq89/5rK17hxY3h5eeH06dNwdHREXl4eW9JXQvHc3Lp16wIAnjx5orZRmEoXFxcHQ0NDhIWFwcrKCnPnzoWdnR2LYZVUo0YN9O3bF3379kVOTo7oOLI3b948vPvuuzh16hRmzJiB8PBwdmmqhAULFsDR0RFmZmbsWlIFzZo1w+7du2FkZCQ6CpWDxTCqFrbYqR4dHR0u1FWBlpYWFAoFhgwZgr59+0JPT090JI0SEBCAc+fO4c6dO+jduzdOnjyJTp06sRhWhuL+zocPH2bfenptjIyMsGbNGtExNI6HhwdMTU3h7+8PAAgNDYW7uzsCAgIEJ5O/mTNnio6gkVasWIF169ZJn79OnTphxYoVglPJF4ur1fN8Aad4pgkLO+Vj54h/5ptvvsFvv/2GSZMmoU6dOkhOToabm5voWLI3adIkjBo1CgMGDIBKpcLhw4cxbdo00bFkq6CgADo6OigoKEB+fj6OHTuGcePGoUaNGlxXqiauj1QsPj4e3377LY4fPw5bW1sMGTIEY8eOFR1L9vT09DB+/HjRMTTO6NGjcfz4cWnDZpcuXdi2WYZYDKNqYYud6mndujXCw8OhVCpx//59BAUFoWPHjqJjyVZoaCju3LmDyMhIuLq6olWrVhg6dCh69OghDRSnsh0+fBihoaGwsbGBr68vUlJSMG/ePNGxZO+vv/5CZmYmDAwMsGjRIty4cQNz585Fz549RUeTpczMTBgaGuLJkyelvv/WW2+91jyahvMmqic+Pl5tdqSzs7N0YofKZ2lpKTqCRqpbty4WLVokOobGKNnimiqPRR0SQV9fH82aNcOpU6dw6tQpdO7cmfe9lWBjY4N27drh7NmzAIo2IrZu3VpwKvkaMWIEQkJCMGrUKFhbW8Pc3BxdunRBYmIiDA0NRcejN1TxulGdOnXwv//9Dw0aNMDff/8tOJX8de7cGWvWrIG1tTV0dXWl623bthWYSv7WrFmDK1euSB0SgoKCcOnSJXYakhmuJlO1sMVO9Xh6emLTpk3Q1dWVFtenT58uOpastWrVCrNmzcKsWbMQFRUFNzc3ODo6so1CJdSsWRNaWlrQ0dFBZmYm6tevj6SkJNGxZG///v34/PPP8dtvv+HJkyfw8/ODm5sbFwXKMHfuXGzevBl2dnZQKBRSe0mgqH3u8ePHBaaTP86bqB49PT3ExMSgc+fOAIDz589zd2wlXbp0CT4+Prh79y7y8/OhVCqhr6+PCxcuiI4mS8uXL8fChQvL3O3Pe196mfj1RiJs27YNe/fuRb9+/QAUtRUbOXKk1Nqf1JXcCNagQQMMGTJEeu/JkyfcCFaG4meE8ePHq504MTY2xvbt20XF0jjFJ4UNDAwEJ9EMo0aNQnp6OlxcXODk5ISsrCzMmjVLdCzZu3HjBoCi54ZiCoWC36sViI6ORmhoqNRa0tbWFjY2NiyGyQyLYVQtbLFTdUqlEl988QWCgoIwZ84c0XE0xqNHjxAZGYmjR4+ibt26cHd3lx7UqHzt2rXD06dPMWLECNjZ2aFWrVo8iVgJxQ9qv/76K2xsbGBqaqpW4CF1mzdvhkqlwo4dO9C0aVPRcTQO501Uz5IlSzB//nxkZmZCpVKhbt26WLlypehYGmHp0qX4+uuv4eLigv379+PAgQO4f/++6FiyVXzicNKkSYKT0L8Bv95IhH379mHPnj2oVasWAMDR0RGjRo1iMawMz28EK6ZSqbgRrBypqalqcxGfx5mI5bt16xbmz5+P9PR0qFQqGBkZYeXKlTAzMxMdTdZGjBgBoKgzAr83Ky8oKEh0BI319OlTaVNERkaG2DBUKhbDqFrYYqfqtLW1oaWlhYyMDM4Nq6Rx48bh2bNnGDhwIHx9faVfKPn5+dx1VwlLliwBAIwZMwa9evVCZmYmzM3NxYbSAO3atcOkSZPw559/Yu7cucjMzOTQ2AooFApMnToV4eHhoqNoHM6bqJ42bdogLCwMmZmZAMD2OlXUvHlzKJVKaGtrw97eHjY2Npg7d67oWLLUrl07ALz3fRnS09ORlJTEe5Fy8Ovtn0lJScHatWuRnJyM77//HnFxcbh48aK0GEpl09bWLvVjetHmzZsBACdOnBCcRLMUFhZy/uE/sHjxYixYsADdunUDAJw7dw5eXl7YvXu34GTyVF7hFWDxtSJlzWFmO+fyTZ06Fba2tujatStUKhX++OMPuLq6io5Fz2ExjKqFLXaqp1atWhg6dCj+85//SDvvAHAGRRkePnwIANi9ezd+/vln6Tp33ZXv+vXr5b7HPs9lU6lUmDVrFlJTU2FiYgJ9fX2kpaVhxYoVoqPJ3vvvv48rV66gQ4cOoqNoFBsbG7Rt2xbnzp0DwHkTFeGD7T+nr6+PvLw8tGnTBn5+fmjUqBEKCwtFx5K94t7/JdWuXRvt2rWDk5MT6tWrJyCV/Dk4OGDjxo0oKCiAnZ0d6tevDwsLC7i7u4uOJmv379/H2rVrERcXh9zcXOk6733Lt2DBAtjZ2UntJFu0aIE5c+awGFYBOzs7jBgxQuq+cezYMdjb2wtOpXnu3buHH374AcuWLRMdRZYaNmzIhfR/ICsrSyqEAUDXrl2RlZUlMJG8lSy87t69G6NHjxaYRvOUXK/Mzc1FdHQ03n33XYGJNMOQIUNgaWmJq1evAgBcXV3RsGFDwanoeSyGUbWwxU71fPLJJ/jkk09Ex9AY3G1XPeW1CmOf5/IpFAp88cUXaiec6tWrx0XOSrh8+TLCw8PRtGlT6OvrS9d5Wqxi7777LurUqSO1R3z48CFbTpah+MH23r17uHr1KqytrQEAv/zyC9q3by8ymsbw8/ODSqWCl5cXAgMDkZSUhHXr1omOJXu9evWCtra2NBsmKioK2dnZaNCgAdzd3TnLqQwZGRkwNDTE3r17YWNjg1mzZpVaWKQiY8aMwa5du+Du7o5Zs2ZhxYoV2L59O4KDg1m0roS0tDQMGjQI3333HQBAR0eHp/srYeLEibC0tMT58+cBAL6+vnj//fcFp5Kv2NhY+Pn5ITk5GR999BHGjh0LHx8fXL58mS1Oy8G28/+MiYkJ1q9fL7XTDQsLg4mJieBU8lWy8Hrs2DEWYqvo+Z9lkydPxuTJkwWlkb87d+6gVatW0sb0t99+GwCQnJyM5ORkbkiXGRbDqNrYYqdqlEolgoOD2XuXXjl+jf0zPOFUPT/88IPoCBopKCgIAQEBaNCggdqCHYuIpSt+kB07diyCg4Ol9ojOzs6YOnWqyGgaw9jYGHl5efjzzz/Rr18/tGzZErq6uqJjyd6ZM2cQEhIivX7vvfdga2uLkJAQFnfKoVQqkZycjIMHD2L27Nmi48jeli1bABTtwu7evTuAou/ZmTNnws7ODi4uLiLjyV6tWrWQlpYmzXG6dOkS29OX48mTJ9LHxsbGMDY2VnuPLelL5+npiTFjxuDDDz/Eb7/9BhsbG9jY2GD16tWoWbOm6HiyFRgYKDqCRluxYgXWrVuHmTNnAgA6derE7iWVVHK2H1VPdnY2/vrrL9ExZCswMBA+Pj6lbkznhnT5YTGMqoUtdqqOM8PodcvPz8euXbsQExMDoGj+xKhRo1CjRg3ByeTt8uXLCAsLg7GxMU84VYGxsTFiYmLw4MED2NvbIzU1lXMBKmH79u04dOgQTx9WUUpKiloBR1dXFykpKQITaY7o6GgsXrwYzZo1g0qlwp9//glvb2/07t1bdDRZUyqVahslrly5Ip3m5Hydsk2fPh2TJ0+GhYUFOnTogISEBLRo0UJ0LNmaO3cuNm/eDF1dXRQWFqJ58+bYsWMHGjduzN+plbBgwQI4OTkhPj4eo0ePRlpaGvz9/UXHki07OzsoFArpxE7xgjFb0pcvLy8PdnZ2AIpO92/fvh1ubm6CU8kfi6v/TN26dTleg16bkhu9CgsLkZqaihkzZghMJG8+Pj4AuDFdUyhUPKtM1ZCYmIj69eujoKAAgYGByMjIwGeffYbmzZuLjiZrTk5OuHnzJmeG0WuxcOFCFBQUwMbGBkBRKwUtLS0sX75cbDCZS0xMLPV6yd2y9KKAgABcu3YN9+7dw+HDh/Ho0SO4uLhwqHMFHBwcsHXrVujocH9SVWzcuBEHDx5Um28ycOBATJs2TXAy+RswYAA2b94s3bPFx8fjiy++wKFDhwQnk7erV6/Cw8NDKkgYGBhg+fLlaN26NaKjozFo0CDBCelNcvnyZbRq1QqZmZnw9/dHRkYGHB0d8cEHH4iOJnsFBQW4d+8eVCoVWrZsyU1gFVCpVEhKSmJ75ioYMGAA1q5dKxURXV1dsWbNGuk122HRy1TRvS3bNJeuZDEnPj4ezZo1U3ufG13LV3JNREdHB/Xr1+fzajkyMzORkpIibfg6ePCgNPO1Z8+eaNCggcB09DwWw4heo5LtdUqytbV9zUk0099//602RJwPbeX79NNPERYWVuE1elFpJ5zYk718w4YNw4EDB2Bra4sDBw4AKHoI4YNG+Tw8PHDv3j306dNH7aTTxIkTBabSDNeuXZPmm3Tp0oXzTSrJ3t4e+/fvl16rVCoMHz5c7RqpUyqVCAoKwoQJE5CRkQEAPOVfSffu3cOSJUvw999/IyIiArGxsThx4gSmT58uOppGUSqViIyMxKeffio6iqwdOXLkhWu1a9eGmZkZ6tevLyCRZuD9WtU4ODiU+R7bYdHL9vvvvwMo+vmWkpIi/R6IjIxE/fr14eHhITKebJW1wbUYN7pWTKlUIiUlReqEAHANriyenp7o2LGjdGq4X79+sLKyQk5ODrS1tbF06VLBCakklnWpSlxcXODv71/mbATeRJfP1tYWOTk5ePjwId59913RcTTG8ePHsWrVKiQnJ8PIyAgPHz5Eq1atEBkZKTqarGlra6vtgkpISGArp0ooecLJ3t4e+fn5mDdvHk84VaBGjRpQKBRSi52srCzBiTRD06ZN0bRpU+Tn5yM/P190HI3Spk0bNGzYUHpAe/jwIR/QylG8SNyuXTs4Ojpi4MCBUCgUOHToENq3by84nbxpa2sjIiICEyZMYBGsijw9PeHm5gYvLy8AgLm5OVxdXVkMK0NmZiZ++uknPHr0CNbW1ujRowd++ukn/Pjjj3jvvfdYDKvAvn37cOnSJXTt2hVA0SJy27Zt8eeff2L69OlStwRSx3m5VcM2WNUzZswY7Nq1Cx07dlSb4VTclvPChQsC08mXpaUlAGDlypUIDg6WrltbW0sL7/QiFrv+Gc61rpqrV6+qFbwMDAzg6ekJoOhnH8kLi2FUJQsXLgTAo9jVdeLECaxatQr5+fk4ceIEbt68CX9/f34+K+Dv74+ff/4ZEydOxIEDB3D27FmebqoENzc3jB8/HiYmJlCpVHj48CGH7FbC0aNHpRNOADino5IGDhwILy8vPH36FHv27MH+/fsxYsQI0bFkz9nZWXQEjcQHtKr75ZdfpI8bNGiAP/74AwBgZGSkduqaSmdhYYGlS5di0KBBavMk2Q6rfNnZ2S8ssHNjTtnmzZuHunXr4sMPP8TevXuxefNmqFQqrF+/Hm3atBEdT/aUSiWioqKkdkQpKSmYP38+9uzZg3HjxrEYVobLly8jPDwcTZs25bxcemV27doFALh48aLgJJopOzsbCQkJUreShIQEZGdnC05FbyrOta4apVKpVuT38/OTPi7uKkHywWIYVUmjRo0AADt37sS8efPU3vvqq69euEbqAgICsG/fPqm1Qps2bfDnn38KTiV/Ojo6qFevHgoLC1FYWIhu3bqxqFMJ3bt3x5EjR3D37l0ARQOeS7Zho9LxhFP1TJ48GadPn4aBgQHu3buHWbNmoUePHqJjyV5qaiq2bNmCuLg4tYIEW+yUjw9oVefr6ys6gka7efMmgKINOsXYDqti9erVQ3x8vPQ79dChQ2jYsKHgVPL1559/YuPGjQCAESNGoGfPnoiOjkbNmjUFJ9MMSUlJanM56tevj6SkJLz11lucdVKOH374QXQE+hfZu3fvCxvmVq9eDVdXV0GJNIO7uzscHBzUNrp6e3uLjkVvqLfffpvdEKpAoVDg8ePH0j2umZkZAODRo0dqRTKSB94RUrX897//feHayZMnWQyrgI6Ozgu/UPiDsWJ16tTBs2fP0KVLF7i6usLIyAi1atUSHUsjXLt2DYmJiVAqlYiNjQUA7oqtQGknnEaOHCk6luwVb4goWQDjJomKubq6YuDAgYiOjoa3tzdCQkJgZGQkOpbs8QGt+jjDqXrYFqt6Fi9eDE9PT9y9exe9evXCO++8g6+++kp0LNkqWbDR1tbG22+/zUJYFVhaWmLq1KkYMGAAAODw4cOwtLREVlYWf2eUo7id2PPzmYlehSNHjqBmzZpS21dvb2/k5OQITiV/VlZW3Oj6D6WnpyMpKQnm5uaio8jW1q1bAQAmJiZwcHDgXOtKmjx5MqZNm4YFCxZIJ/lv3LiBVatWYfLkyYLT0fMUKpVKJToEaY6dO3di165danOIAODZs2ewsLDA6tWrBaaTPw8PD3Tv3h3fffcd1q1bh6CgIOTn53OYYgWysrKgp6eHwsJChIeHIyMjA59++ineeust0dFkbd68eUhISIC5ubnUkkihUGDRokWCk8nTwYMHYW1tjZo1a+L06dM4deoUAKBnz5484VQJtra2CAkJUbvGgewVs7OzQ3BwsNrnyt7eHvv37xecTN48PDxw7949PqBVw7hx46QZTgcOHAAADBkyBBEREWKDyVxKSgrWrl2L5ORkfP/994iLi8PFixfZDraSsrKyUFhYCENDQ9FRZK1NmzZSmzqVSoXc3Fzo6elxpk4VHD58GOfPnwdQ1N60f//+3HxYAc5nrprr16+X+z7b55YvJycHTk5OsLe3x2+//YbatWvz+bSSLly4IG10LcaNruVzcHDAxo0bUVBQADs7O9SvXx8WFhZwd3cXHU2WAgICyn2fLf7LdvLkSWzevBlxcXEAAFNTUzg6OqJ3796Ck9HzeDKMqmTo0KGwsrLC2rVrMXfuXOm6gYEBCxOV4OnpiU2bNkFXVxdffvklevXqxZ3YlbB+/XrMmzcPWlpa0hwnnjip2LVr1xAVFcUFgEqKiIjA0qVL0bNnTwwZMgSurq6ca1IJJTdJDB06VLr+7NkzdOzYUWAyzVB8CqBRo0aIjo5Go0aNkJ6eLjiV/DVt2hRNmzZFfn4+8vPzRcfRKJzhVD0LFiyAnZ2dNOe1RYsWmDNnDothZSjeWVwWFq5LV9yOk6pOqVRi8ODBOHToEPr37y86jkbhfOaqWblyZZnvsX1u2Z48eSJ9vGzZMsyYMQMWFhZwdnbGkydPuJ5UgbI2urIYVr6MjAwYGhpi7969sLGxwaxZs9SeWUkdi13VZ2VlBSsrK9ExqBJYDKMqqV27NmrXro3Zs2ejYcOG0NXVxblz53Dr1i3Y2NigTp06oiPKmr6+PubMmYM5c+aIjqJR2JazekxNTfH48WNp1h+Vb/369cjMzMTRo0cRFBSEhQsXwtraGkOGDIGlpaXoeLLFTRL/jJOTEzIyMjB//nz4+Pjg2bNn8PDwEB1L9vigVn2c4VQ9aWlpGDRoEL777jsARYVsLS0twank69mzZ6Ij0L+MtrY2WrZsiYcPH6Jp06ai42gUzmeuGrbNrR47OzsoFArppKtKpUJ0dDSio6OhUChw/Phx0RFljRtdq0epVCI5ORkHDx7E7NmzRcfRGBMnToS/v7+0xpueno4vv/ySMybpjcBiGFXLzJkzsX//fjx48ABeXl6wtrbG3LlzsWXLFtHRZGn58uVYuHAhpk2bVur7xbuMSV3xiZOEhIQXTpxYWFgITCZvxV9nz549w+DBg9GhQwfUqFFDep9fb2UzNDSEra0tbG1tkZaWhsOHD2PZsmVIT0/Hr7/+KjqeLBVvktDW1pZmThSbN28eZ8NUoG/fvgCKPo/FiyuBgYECE2mG1NRUbNmyBXFxcWrzTbgbu2KlzXBim+uK1apVC2lpadIi1KVLlziDqBzOzs5QKpUICgrChAkTRMehf4mnT59K977F7SYB3vtWhPOZqyc7Oxtbt25FUlISfHx8cP/+fdy7d0+6tyN1J06cEB1Bo3Gja/VMnz4dkydPRqdOndChQwckJCSgRYsWomPJXmpqqtphh7p16+Lvv/8WmIjo5WExjKpFS0sLOjo6OHLkCMaNGwcHBwcezy7HsGHDAACTJk0SnESz8MRJ9fDr7J9LT0/H0aNHERUVhfT0dLbbqYTi3tjFCgoKKpypQKULDAzk4nEFXF1dMXDgQERHR8Pb2xshISEwMjISHUtjBAYGqs1wSkhIEB1J9hYsWAAnJyfEx8dj9OjRSEtLg7+/v+hYsqatrY2IiAj+PKPXxsXFRXQEjbRhwwbo6enB3d1dms88Y8YM0bFkz93dHW3btsXFixcBAI0bN4aLiwuLYRUonlf6PK4nlS8tLY0bXath4MCBGDhwoPTaxMQE69atE5hIM2hra6udtE5MTOSpRHpjsBhG1aKjo4OIiAiEhoZi48aNAIoWPql0pqamCAwMRHx8PMzMzDB8+HBpTgyVTaFQ4J133oGXl9cL77GveNmKW/olJCSgUaNGqFmzJoCiYcUpKSkio8nas2fPcPToUURGRuLmzZuwtrbG9OnT0bVrV974lWPz5s3YtGkTcnNzpRObKpUKurq6GDlypOB0mkmlUomOIHtPnjzBiBEjsH37dlhaWsLS0hL29vaiY2mEWbNmISQkRG3Xv4uLC4KDgwWmkr+2bdtix44duHfvHlQqFVq2bKm2GEWls7CwwNKlSzFo0CC1kzpt27YVmIreVJaWlkhJScHVq1cBAB06dED9+vUFp5KvBw8eICUlBZ06dQIAaT5zTEwMMjIyUK9ePcEJ5S0+Ph7ffPMNIiMjARSNROA9XMWKvz8BIDc3F2fOnEHbtm1ZDKvAzJkzRUfQKFu2bIGjoyN8fHxKfZZftGiRgFSaY/bs2fjss8/QpUsXqFQqnD9/HkuXLhUdS/YyMjKwbt06xMTEACi6L5kxYwa7ScgMV+OpWnx9fbF7925MmzYNJiYmSEhIwKeffio6lmzNnz8fOjo66Ny5M06ePIm4uDj+8q2EuXPnYvPmzWr9xYuxr3jFXFxcsHv3bum1lpYWXFxcsH//foGp5Mva2hq9evXCZ599hp49e3KRs5KmTp2KqVOnYs2aNWonOKn6WHytWPGGkkaNGiE6OhqNGjVCenq64FTydufOHcTFxSEjIwNHjhyRrmdmZqq1miR1V65cQZMmTdCwYUPo6Ojg+vXrOHz4MIyNjeHs7MyNORW4efMmAKidolMoFGxpWoYxY8Zg165d6Nixo9rvguIZOxcuXBCYTv6ioqLw1VdfwdLSEiqVCj4+PnBzc8OAAQNER5OlFStW4Msvv3zheu3atbFixQqeOKmArq4ucnJypO/V+Ph46OrqCk4lf56enmqvnz59ypnqlcAZ1lXTqlUrAEC7du0EJ9FMVlZWCA4OxuXLl6FQKODh4cEuHJXg4eEBU1NT6b43NDQU7u7uCAgIEJyMSlKouHWF6JUbOnQowsPDARSdoBsxYgRCQkIEp9JsxYsCVLZhw4YhNDRU7dqnn36KsLAwQYnkLScnB3p6eqJjaJyKWiFy93/pnl/oLKZSqZCbm4sbN24ISKU5fvnlF3Tu3Fma0/Hs2TM4OzvD2tpadDTZOnbsGI4fP44TJ06ofZ4MDAwwaNAgzuIsg62tLbZu3Yq33noLf/zxB+bMmQNPT0/cvHkTd+/exbfffis6IhH9n08//RRbt26VToOlpqZiwoQJvPctg729fZmb5Eo+v1LpTp8+jY0bNyIuLg49evTAxYsX4evri65du4qOplHy8/MxZMgQHD58WHQUWbt06RJ8fHxw9+5d5OfnQ6lUQl9fn5skKhAfH49mzZqJjqExEhMTUadOHekk09mzZ3Hs2DEYGxtj7NixLPhXoLQ1uNKukVg8GUbVcv/+faxdu/aFwfU8qVO6ki0R2R6x6vz9/dVmABQWFmLevHlYs2aNwFTyZ2RkhOPHj+Ojjz4CULQQynYnZWMhrHpWrlxZ5nvc/V+24vkSVD3F8zhq166NoKAgAEVzsKhsH3/8MT7++GNcvHgRHTt2FB1HYyiVSun0V1RUFEaNGoX+/fujf//+0kxYKl90dDRu376t9szg7OwsMJFmSE9PR1JSEpRKpXSNG0zKp1Kp1NoivvXWW2xbV46MjIwy38vJyXmNSTRTjx498P777+Py5ctQqVRYuHAhT06Uw9HREV5eXli+fLl0rbCwEHfu3OHpzUpYunQpvv76a6nTy4EDB3D//n3RsWTPw8MDf/31F9q3b4/OnTujc+fOeO+990THkq3Zs2cjICAAtWvXxs2bN+Hi4oKpU6ciNjYW3t7eat+/9CI9PT3ExMSgc+fOAIDz589znUmGuCpP1eLu7o5Zs2ZhxYoV2L59O4KDg1FYWCg6lmzFxsaqzdIpnq3DlieV89dff2Hz5s2YOnUq8vLy4OLigvfff190LNnz9vaGq6srfHx8oFKp0KRJE6xatUp0LHrDFBciiEQLDAzEhAkTRMeQvaNHj8LU1BQ1a9bElClTcOvWLbi7u7OwU4bCwkIUFBRAR0cHZ86cgY+Pj/ReySIFlc7Lyws5OTk4d+4cRowYgcOHD6N9+/aiY8neN998g5CQEJiYmEiniLnBpGI9e/bE5MmTMXjwYABFBexevXoJTiVf7dq1w549e16Y8bp3714WXstx584dtGrVSuqO0LBhQwBAUlISkpKS+Lkrg52dHaZMmQIbGxt06NABNWrUgLa2NoyNjfH222+LjqcRmjdvDqVSCW1tbdjb28PGxoZt6iuwY8cO5OXl4erVq/j9998xdepUZGVl4ffffxcdTZZycnLQuHFjAEBYWBjs7e0xadIkFBYW8lmhEpYsWYL58+cjMzMTKpUKdevWLXfzMInBYhhVS25uLrp37w4AMDY2xsyZM2FnZ6d2eof+v+J5CVQ9K1asgKurKzZv3oxz587BysqKC56V0KxZM+zZswfPnj0DUNQKiyqWm5uLmjVrql1LTU3lTs9K+N///oe4uDjk5eVJ1zgMm14X7v6vnNOnT8PNzQ1Hjx6FsbExAgICMHbsWD7glmHw4MEYN24c6tWrBz09PWmn54MHD2BoaCg4nfxdvHgR4eHhGDp0KJydnTFx4kQ4OjqKjiV7Bw8exNGjR9mOqIrmz5+PI0eO4Pz58wCAUaNGoV+/foJTyZeHhwecnZ0RHh4uFXCuXbuG/Px8zjcpR2BgIHx8fEpd4GTRumwDBw6ElZUVNmzYgFWrVmHYsGHQ0tLClStXAAATJ04UnFDe9PX1kZeXhzZt2sDPzw+NGjXihvRKiImJwfnz5xETE4OMjAz06dNHupej8p09e1aaK6mlpSU4jWZo06YNwsLCkJmZCQB8VpApFsOoWnR1dVFYWIjmzZtjx44daNy4sbTgTvSylJxFNH78eHh5ecHCwgJdunTB9evXueuuDKGhoRg2bBi2bt1a6vt80Cjf8OHD4ePjgw8//BAAcPjwYaxdu5Z97CsQEBCAc+fO4c6dO+jduzdOnjyJTp06sRhGrw3nSFZOQUEBgKLWdQMGDJBmAlDpnJyc0L17dzx+/Bg9evSQvs4KCwvh6ekpOJ38FbeG0dfXx6NHj1CvXj08fvxYcCr5MzMzQ0ZGhlrLP6qctm3bwtDQEP/5z3+QnZ2NzMxMLkaVoUGDBti9ezfOnj2L27dvAwB69+4tbXql0hWfEGZ3hKqrUaOGVNR59uwZF9irwM/PDyqVCl5eXggMDERSUhLWrVsnOpbsjR8/Hm3btsXUqVNhZWXFTSYV6Nq1K1xcXNCwYUOkp6ejW7duAIDk5GTUqFFDcDr54hqcZmExjKrFw8MD2dnZWLRoEfz9/XH27Fm2X6OX7vnddnXq1EFcXBxWrlzJXXflyM7OBgAWqKtp9erV8PDwgKWlJZKTk/HkyRNs27ZNdCzZO3z4MEJDQ2FjYwNfX1+kpKRg3rx5omPRG6Zjx46lFr2KWxBTxfr27YsBAwZAT08PS5YsQWpq6gunYUld8eaIklq2bPn6g2igPn364OnTp5g8eTLs7OygUCgwfPhw0bFk74svvoCNjQ3MzMzUFp82bdokMJX87dmzBz///DPS09Nx7NgxPHr0CIsXL+Z9XAW6desmLXhS1Vy4cAGJiYlqbXO5Eax0J0+exMqVK2FtbY2QkBDo6+uLjqRRjI2NAQA1a9bk3M0qOHv2LC5cuIA//vgD27dvh5aWFj788EPMnj1bdDRZWrhwIaKiovD48WPs2rVLugdJSUnBnDlzBKeTL67BaRaFij1l6B/g0U8iehMdO3YM8+bNg4GBAX766Sc0b95cdCTZGz58OPbt2wc7Ozts374dBgYGGDhwIA4dOiQ6GhE958mTJ6hduza0tbWRlZWFZ8+eSTNPiF6VvLw85Obm8jRiJQwePBijRo2CmZmZ2skJS0tLgankb9iwYdi7dy9GjhyJAwcOAACGDh2K8PBwscHojTRv3jwkJCTA3Nwc2traAIpOqS9atEhwMnn67LPP4O3tDVNTU9FRNNL58+cREBCAhw8fSqf8AeD48eMCU2mGO3fu4Pfff0dMTAwuXryIpk2bYseOHaJjEZEgPBlG1XL16lV4eHhIVW9DQ0OsWLEC7dq1E5yM3iQ8alw95fX4VygUmDFjxmtMo3k8PDyQkJCAsLAw3L9/H1OnToWDgwPGjh0rOpqstWvXDk+fPsWIESNgZ2eHWrVqoWPHjqJjEdH/2bJlizSr6cyZMxg4cCAAoFatWti0aZM0E4DoZePJiarT09PD+PHjRcfQOLq6umotsEouGBO9bNeuXUNUVBTbNFfSzp07RUfQaAsXLoS7uzvatWvH9pJV8NFHH+Hdd99Fp06dMGbMGPj6+rJVIr0yqamp2LNnDxITE9XuQXx9fQWmouexGEbV4uHhgcWLF0uDJ2NiYuDu7s5dd/RS8ahx9dSqVeuFa1lZWdi/fz+ePHnCYlgFzMzMsHz5cigUCpiYmGDv3r28eSmHt7c3hgwZgiVLlgAAxowZg169eiEzMxPm5uZiwxGRJCoqSiqGfffdd1IxDAB+++03FsPolSjr5ASLYeXr3Lkz1qxZA2tra7VFO87LLV+XLl2wadMm5OTk4PTp09i5cyesra1Fx6I3lKmpKR4/foxGjRqJjkL/ArVr10bv3r1Fx9A4R48eZfGQXpvp06ejU6dO6N69u3TfS/LDYhhVi7a2tlQIA4oe2HR0+OVEL9fo0aMBgD2xq2jSpEnSx5mZmdi+fTuCg4MxaNAgtfeodBMmTFB7Xbt2baxYsUJMGA3QokUL+Pn54fHjxxgwYACGDBmC999/X3QsInpOyc7oz3dJZ9d0elV4cqJ6bty4AQC4dOmSdI3zcivm6uqKffv2wczMDD///DN69+6NESNGiI5Fb6i0tDQMHjwYHTp04Gw/euW6du2KVatW4ZNPPuEmiSp48OABlixZgr///hsRERGIjY3FiRMnMH36dNHRZO3atWsvdP765Zdf0LdvX0GJNEN2djbnpmsAVi+oSq5fvw6gaNedl5cXBg8eDIVCgaioKPawp5eO7f6q78mTJ9i6dSvCw8Nha2uLkJAQ1K1bV3QsjXD//n2sXbsWcXFxyM3Nla6zH3vpPv/8c3z++edITExEZGQkPDw8kJOTgyFDhmDw4MFo2bKl6IhEBKgVI54vTLBQQa8KT05UT1BQkOgIGklLSwsjR47EyJEjRUehf4GZM2eKjkD/IpcvXwZQVKQoxk0SFfP09ISbmxu8vLwAAObm5nB1dWUxrAKenp5YtWoVzMzMAAARERHYtm0bi2EV6NOnD3799Vee4pQ5hYpbQakKHBwcynyPv4jpZfvxxx9fuFay3d/FixcFpJK/VatW4ejRoxg5ciTGjh0LAwMD0ZE0ypgxYzBr1iysWLECmzZtQnBwMAoLC+Hi4iI6msa4ceMGPDw8cOvWLdy8eVN0HCIC0KZNG+jr60OlUiE3Nxd6enoAik6F5eXlSRueiF6GadOmAShqdR0bG8uTE5XEebnVc+zYMTx69Eia7zpixAikpqYCKDotVrItLBGRplEqlQgKCnqhgwlVzN7eHvv374eNjQ0OHDgAABg2bBhCQ0PFBpO5hIQEzJo1C6tXr8b58+dx4MABbN68GbVr1xYdTdY6duyI7Oxs1KhRQ+qeplAocOHCBcHJqCSeDKMq4S5Fep3Y7q96tm7dCl1dXWzcuFFtsUmlUvEXcSXk5uaie/fuAABjY2PMnDkTdnZ2LIZVoKCgACdPnkRkZCTOnj0LS0tLtjglkhEWpul14n1a9XBebvV8//33+Prrr6XXeXl52LdvH7Kzs+Hu7s5iGL0Sly5dgo+PD+7evYv8/HwolUro6+vzWYteOm1tbURERLAYVg316tVDfHy81AXh0KFDaNiwoeBU8mdiYoK1a9dixowZaNKkCX788UdpIx2VjRv2NQOLYVQtKSkpWLt2LZKTk/H9998jLi4OFy9eZE92eunY7q/qYmNjRUfQaLq6uigsLETz5s2xY8cONG7cmItS5Th9+jQiIiJw8uRJtG/fHoMHD4aPjw9q1aolOhoREQnSuHFjpKSkoFOnTmrXY2Ji2DKxHMVtdUrbTPLLL7+87jgaIz8/H02aNJFed+rUCfXq1UO9evWkAiPRy7Z06VJ8/fXXcHFxwf79+3HgwAHcv39fdCx6Q1lYWGDp0qUYNGgQ9PX1peucGVa+xYsXw9PTE3fv3kWvXr3wzjvvYPXq1aJjydbQoUPVXqenp0OpVEprveHh4SJiaZTjx48jJiYGAGBpacnWkjLENolULVOmTIGdnR02bdqEsLAwFBQUwNbWlj8Y6aViuz8S4cqVK2jVqhUyMjLg7++PjIwMTJkyBR9++KHoaLI0fvx4DB06FJ988gkL1UREBACYOnUqvvzyS7z33ntq12/duoWvv/6abRLLMGDAAHz//fd455131K7v378fGzduxLFjxwQlk7d+/frh6NGjpb738ccf8/NGr4SdnR2Cg4MxdOhQaR2kZCs2opeptJElHFVSeVlZWSgsLIShoSECAwN5yq4MiYmJ5b5vbGz8mpJoptWrV+Pq1atSUTEyMhLt2rXD3LlzBSejkngyjKolLS0NgwYNwnfffQcA0NHRgZaWluBU9KZhuz8SoUOHDgAAAwMD+Pr6Ck4jf3wAIyKi56WkpLxQCAOA9957r8KFln8zd3d3TJ48GZs3b0aLFi0AAJs3b0ZERAR27NghNpyMdejQAXv27MHIkSPVru/evVu6ryN62fT19ZGXl4c2bdrAz88PjRo1QmFhoehY9IbiyJJ/pmTXEhbDylZc7Lp06RJat24NQ0NDAEVjS+7cucNiWAV+/fVXhIaGSuvjtra2sLGxYTFMZlgMo2qpVasW0tLSpL67ly5d4iBFeunY7o9ep2nTppX7PnexExERVU5GRkaZ7+Xk5LzGJJqld+/e0NXVhaOjI9avX4+9e/fi6tWr2LFjB09fl8PDwwMzZsxAeHi41DLs+vXryMvLw/r16wWnozeVn58fVCoVvLy8EBgYiKSkJKxbt050LHpDcVTJy8MGaRVbsmQJQkJCpNe1atV64RqV7unTp3jrrbcAlH8/TOKwGEbVsmDBAjg5OSE+Ph6jR49GWloa/P39RcciIqq2S5cuoUmTJhg8eDA++OAD3iQTERFVU7t27Uo9qbN3717ON6lA9+7d4evrCwcHB3Ts2BHbtm1DzZo1RceStfr162P37t04c+YM4uLiABQVFrt37y44Gb3JjI2NkZqaCqD0OX9EL9OCBQukUSUA0KJFC8yZM4fFsGoo3tRPZSvuxlRMS0sLBQUFAhNphqlTp8LW1hZdu3aFSqXCH3/8wVNhMsSZYVRtBQUFuHfvHlQqFVq2bIkaNWqIjkREVG1KpRKnT59GZGQkbt26hd69e2PIkCEwNTUVHY2IiEijpKSkwNnZGTVq1JCKX9euXUN+fj4CAgLQsGFDwQnlqWPHjlAoFFCpVMjPz5da0bNFOJF8qFQqBAQEYMeOHVCpVFCpVNDW1sa4ceNYFKNXxt7eHvv371ebSzds2DCEhoaKDSZTxb9Pn6dSqZCbm4sbN24ISKU5nJ2dYWlpiTFjxgAAdu7ciXPnzmHDhg2Ck8lfcnIyrl69CqCojTPveeWHJ8OoSq5cuYImTZqgYcOG0NHRwfXr13H48GEYGxvD2dlZOgpKRKRptLW1YWVlBSsrK+Tl5SEiIgIODg5wdnbGuHHjRMcjIiLSGA0aNMDu3btx9uxZ3L59GwBP6lTGxYsXRUcgogoEBgbiwoUL2LdvH0xMTAAACQkJWLJkCWcR0SvDUSVVw9+n/4y3tzeWLVuGjRs3QqFQoHv37vDx8REdS/Y+//xzbNu2DR999NEL10g+eDKMqsTW1hZbt27FW2+9hT/++ANz5syBp6cnbt68ibt37+Lbb78VHZGIqNry8vIQHR2NiIgIJCYmwtraGsOHD0fjxo1FRyMiIiIiIsFsbGzw448/wsjISO16amoqJk2aJJ3aIXqZrl+/Dh8fH9y+fRumpqbSqBJzc3PR0Yj+9XJzc5GdnY3x48cjKChIGrmRmZmJKVOm4NChQ4ITUkk8GUZVolQqpdNfUVFRGDVqFPr374/+/ftj2LBhYsMREf0Dbm5uuH37NqysrODs7AwzMzPRkYiIiIiISEYKCgpeKIQBgJGREWfq0Ev38OFDNG3aFG3btsWOHTs4qoReqS1btsDR0RE+Pj6ltplctGiRgFTyt3v3bmzbtg3Jycmws7OTimGGhobsMiRDLIZRlRQWFqKgoAA6Ojo4c+aM2jFZpVIpMBkR0T8TFhYGfX193L9/H0FBQdJ1zukgIiIiIiIA5RYgWJygl23GjBkICQkBAMyZMwfr1q0TnIjeZK1atQIAtGvXTnASzfL555/j888/R1BQEBwcHETHoQqwGEZVMnjwYIwbNw716tWDnp4eOnfuDAB48OABDA0NBacjIqq+2NhY0RGIiIiIiEjGYmNjYWFh8cJ1lUqFvLw8AYnoTVZysk1CQoLAJPRvYG1tDaBoRA5VnYODAy5cuIDExES1AyM2NjbiQtELWAyjKnFyckL37t3x+PFj9OjRQzo2W1hYCE9PT8HpiIiIiIiIiIhejZs3b4qOQP8iJVvVlda2juhlmjZtWrnvb9q06TUl0Uzz5s1DQkICzM3Noa2tDaDo+5bFMHlRqEpuMyAiIiIiIiIiIiIiodq0aQN9fX2oVCrk5uZCT08PAFv506vRrVs3NGnSBIMHD8YHH3yA50sGlpaWgpJphoEDByIqKoqFa5njyTAiIiIiIiIiIiIiGeFJRHqdTp8+jdOnTyMyMhIRERHo3bs3hgwZAlNTU9HRNIKpqSkeP36MRo0aiY5C5eDJMCIiIiIiIiIiIiIiQl5eHiIiIuDn5wdnZ2eMGzdOdCTZc3BwQGxsLDp06IAaNWpI19leUl54MoyIiIiIiIiIiIiI6F8sLy8P0dHRiIiIQGJiIhwcHNCvXz/RsTTCzJkzRUegSuDJMCIiIiIiIiIiIiKifyk3Nzfcvn0bVlZWGDx4MMzMzERH0mgxMTGIjIzE4sWLRUehElgMIyIiIiIiIiIiIiL6lzI3N4e+vj4AQKFQSNdVKhUUCgUuXLggKprGuHHjBsLDw3H48GEYGxujf//+bDEpM2yTSERERERERERERET0LxUbGys6gka6d+8eIiMjERERgXr16mHQoEFQqVQICgoSHY1KwWIYERERERERERERERFRFQwcOBCdO3fG5s2b0bx5cwBAYGCg2FBUJi3RAYiIiIiIiIiIiIiIiDRJQEAAGjZsiPHjx2PRokU4c+YMOJVKvjgzjIiIiIiIiIiIiIiIqBqysrJw/PhxREZG4uzZsxg2bBj69euHnj17io5GJbAYRkRERERERERERERE9A+lp6fj0KFDiIqKwrZt20THoRJYDCMiIiIiIiIiIiIiIqI3FmeGERERERERERERERER0RuLxTAiIiIiIiIiIiIiIiJ6Y+mIDkBERERERPRvZm1tDV1dXejq6iI7OxutW7eGo6MjLCwsSv3zjo6O8PT0RLNmzV5zUiIiIiIiIs3EmWFEREREREQCWVtbY9OmTTAzMwMAHDlyBB4eHvjhhx/wwQcfSH+usLAQCoUCCoXipf7/lUoltLW1X+p/k4iIiIiISE54MoyIiIiIiEhGPvnkE1y5cgU//PADTE1Ncfv2bWRmZuLhw4f4+eefYWtri02bNuHp06dYtmwZDhw4IP1dOzs7LFiwAJaWlggJCcHOnTuhVCphaGiIJUuW4N1330VwcDDCwsJgYGCABw8e4KuvvsLx48cRERGBmjVrQqFQYPv27ahTp464TwIREREREdFLxGIYERERERGRzHzwwQc4ceIETE1NceXKFQQHB8PIyEjtz3Tu3BlZWVmIjY2Fubk5bt26hadPn6JLly6IiYnBwYMH8dNPP0FXVxe//vorPDw8sHv3bgDA5cuXERoaimbNmuHJkycIDAzEqVOnoKenh8zMTOjp6Yn4ZxMREREREb0SLIYRERERERHJTMlu9lZWVi8UworZ2NggJCQE7u7uCAkJgY2NDRQKBU6cOIHY2FiMGDFC+u89ffpU+nsWFhbSzLHatWujWbNmcHNzQ8+ePdGnTx8YGhq+wn8dERERERHR66UlOgARERERERGpu3r1KkxNTQEABgYGZf45GxsbREZGIjc3FxEREbC1tQVQVPyyt7dHaGgoQkNDERYWhujoaOnvlfxvamtrY8+ePRg3bhz++usv2NnZITY29tX8w4iIiIiIiARgMYyIiIiIiEhGjh07hl27dmHSpEkV/tmmTZuidevWWLZsGVq3bg1jY2MAgLW1NUJDQ/HXX38BAJRKJa5du1bqfyMzMxOpqamwtLTErFmzYGZmhtu3b7+8fxAREREREZFgbJNIREREREQk2KxZs6Crq4vs7Gy0atUK3333HT744AOcPHmywr9ra2sLNzc3+Pn5Sde6dOmC2bNnw8nJCUqlEvn5+RgwYADatWv3wt/PzMzEzJkzkZOTA5VKhffffx+ffPLJS/33ERERERERiaRQlWxGT0RERERERERERERERPQGYZtEIiIiIiIiIiIiIiIiemOxGEZERERERERERERERERvLBbDiIiIiIiIiIiIiIiI6I3FYhgRERERERERERERERG9sVgMIyIiIiIiIiIiIiIiojcWi2FERERERERERERERET0xmIxjIiIiIiIiIiIiIiIiN5YLIYRERERERERERERERHRG+v/AaR0plRyGVRTAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dnf_by_driver = data2021.groupby('driver').sum()['driver_dnf']\n",
    "driver_race_entered = data2021.groupby('driver').count()['driver_dnf']\n",
    "driver_dnf_ratio = (dnf_by_driver*100/driver_race_entered).sort_values(ascending=False)\n",
    "plt.figure(figsize=(30,10))\n",
    "bars = plt.bar(x=driver_dnf_ratio.index,height=driver_dnf_ratio,align='center',width=0.5)\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('Drivers')\n",
    "plt.ylabel('2021 Driver DNF ratio')\n",
    "plt.title('2021 DNFs ratio due to Driver error')\n",
    "for bar in bars.patches:\n",
    "    yval = bar.get_height()\n",
    "    plt.text(bar.get_x()-0.1,yval+0.15,f'{round(yval,1)}',fontdict=font)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dnf_by_constructor = data2021.groupby('constructor').sum()['constructor_dnf']\n",
    "constructor_race_entered = data2021.groupby('constructor').count()['constructor_dnf']\n",
    "constructor_dnf_ratio = (dnf_by_constructor*100/constructor_race_entered).sort_values(ascending=False)\n",
    "plt.figure(figsize=(30,10))\n",
    "bars = plt.bar(x=constructor_dnf_ratio.index,height=constructor_dnf_ratio,align='center',width=0.8)\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('F1 Teams')\n",
    "plt.ylabel('F1 Temas DNF ratio for 2021')\n",
    "plt.title('2021 DNFs ratio due to F1 Team error')\n",
    "for bar in bars.patches:\n",
    "    yval = bar.get_height()\n",
    "    plt.text(bar.get_x()+0.21,yval+1,f'{round(yval,2)}',fontdict=font)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Check Points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "driver_home_points_finish = data2021.loc[(data2021['position']<11)&(data2021['driver_home']==1)].groupby('driver').count()['position']\n",
    "total_home_races = data2021[data2021['driver_home']==1].groupby('driver').sum()['driver_home']\n",
    "driver_home_point_finish_ratio = (driver_home_points_finish*100/total_home_races).sort_values(ascending=False).fillna(0)\n",
    "plt.figure(figsize=(30,10))\n",
    "bars = plt.bar(x=driver_home_point_finish_ratio.index,height=driver_home_point_finish_ratio,align='center',width=0.8)\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('Drivers')\n",
    "plt.ylabel('percentage')\n",
    "plt.title('2021 Drivers points finish percentage at home race')\n",
    "for bar in bars.patches:\n",
    "    yval = bar.get_height()\n",
    "    plt.text(bar.get_x(),yval+1,f'{round(yval,2)}',fontdict=font)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "constructor_home_points_finish = data2021.loc[(data2021['position']<11)&(data2021['constructor_home']==1)].groupby('constructor').count()['position']\n",
    "total_home_races = data2021[data2021['constructor_home']==1].groupby('constructor').sum()['constructor_home']\n",
    "constructor_home_point_finish_ratio = (constructor_home_points_finish*100/total_home_races).sort_values(ascending=False).fillna(0)\n",
    "plt.figure(figsize=(30,10))\n",
    "bars = plt.bar(x=constructor_home_point_finish_ratio.index,height=constructor_home_point_finish_ratio,align='center',width=0.8)\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('F1 Teams')\n",
    "plt.ylabel('percentage')\n",
    "plt.title('2021 F1 Teams points finish percentage at home race')\n",
    "for bar in bars.patches:\n",
    "    yval = bar.get_height()\n",
    "    plt.text(bar.get_x()+0.2,yval+1,f'{round(yval,2)}',fontdict=font)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "end = time.time()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0:00:26.173770'"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import datetime\n",
    "str(datetime.timedelta(seconds=(end - start)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "26.1737699508667 seconds\n"
     ]
    }
   ],
   "source": [
    "print(str(end - start)+\" seconds\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}