Web-scraping-largest-chemical-producers.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Web Scraping using Python\n",
    "## Largest chemical producers worldwide\n",
    "_by Virginia Herrero_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The **overall** goal of this project is to scrap from the Wikipedia website the list of largest chemical producers by sales in the year 2021. Clean, explore, analyse and visualize the data obtained. \n",
    "\n",
    "**Section 01: Web scraping**\n",
    "* Obtain the list of largest chemical producers worldwide from Wikipedia.\n",
    "\n",
    "**Section 02: Data cleaning**\n",
    "* Clean the data scraped from Wikipedia.\n",
    "* Rename columns, change data types, convert currency.\n",
    "\n",
    "**Section 03: Data exploration and analysis**\n",
    "* Null values\n",
    "* Duplicates\n",
    "* Outliers\n",
    "\n",
    "**Section 04: Data visualization**\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Section 01: Web scraping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import all required libraries\n",
    "\n",
    "from bs4 import BeautifulSoup\n",
    "import requests\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Specify the url\n",
    "url = r\"https://en.wikipedia.org/wiki/List_of_largest_chemical_producers\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Send a GET request to the url\n",
    "page = requests.get(url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Parse the HTML content using BeautifulSoup\n",
    "soup = BeautifulSoup(page.text, \"html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Extract the table containing the data needed\n",
    "table = soup.find(\"table\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Extract the titles of the table\n",
    "titles = table.find_all(\"th\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Rank[4]',\n",
       " 'Company',\n",
       " 'Chemical sales in 2021USD millions[A]',\n",
       " 'Change from 2020in percent',\n",
       " 'Headquarters']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titles_table = [title.text.strip() for title in titles]\n",
    "titles_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>Rank[4]</th>\n",
       "      <th>Company</th>\n",
       "      <th>Chemical sales in 2021USD millions[A]</th>\n",
       "      <th>Change from 2020in percent</th>\n",
       "      <th>Headquarters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Rank[4], Company, Chemical sales in 2021USD millions[A], Change from 2020in percent, Headquarters]\n",
       "Index: []"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a DataFrame with the scraped titles\n",
    "df = pd.DataFrame(columns = titles_table)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fill the DataFrame with the scraped values\n",
    "column_data = table.find_all(\"tr\")\n",
    "\n",
    "for row in column_data[1:]:\n",
    "    row_data = row.find_all('td')\n",
    "    individual_row_data = [data.text.strip() for data in row_data]\n",
    "\n",
    "    length = len(df)\n",
    "    df.loc[length] = individual_row_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **DataFrame with all the data scraped from the Wikipedia website:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>Rank[4]</th>\n",
       "      <th>Company</th>\n",
       "      <th>Chemical sales in 2021USD millions[A]</th>\n",
       "      <th>Change from 2020in percent</th>\n",
       "      <th>Headquarters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>BASF</td>\n",
       "      <td>92,982</td>\n",
       "      <td>32.9%</td>\n",
       "      <td>Germany, Ludwigshafen am Rhein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Sinopec</td>\n",
       "      <td>65,848</td>\n",
       "      <td>31.9%</td>\n",
       "      <td>China, Beijing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Dow</td>\n",
       "      <td>54,968</td>\n",
       "      <td>42.6%</td>\n",
       "      <td>United States, Midland, Michigan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>SABIC</td>\n",
       "      <td>43,230</td>\n",
       "      <td>50.1%</td>\n",
       "      <td>Saudi Arabia, Riyadh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Formosa Plastics</td>\n",
       "      <td>43,173</td>\n",
       "      <td>47.8%</td>\n",
       "      <td>Taiwan, Taipei</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>Ineos</td>\n",
       "      <td>39,937</td>\n",
       "      <td>121%</td>\n",
       "      <td>United Kingdom, London</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>Petrochina</td>\n",
       "      <td>39,693</td>\n",
       "      <td>41.7%</td>\n",
       "      <td>China, Beijing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>LyondellBasell Industries</td>\n",
       "      <td>38,995</td>\n",
       "      <td>66.6%</td>\n",
       "      <td>United States, Houston, Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>LG Chem</td>\n",
       "      <td>37,257</td>\n",
       "      <td>41.8%</td>\n",
       "      <td>South Korea, Seoul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>36,858</td>\n",
       "      <td>59.6%</td>\n",
       "      <td>United States, Spring, Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>Mitsubishi Chemical Group</td>\n",
       "      <td>30,719</td>\n",
       "      <td>24.8%</td>\n",
       "      <td>Japan, Tokyo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>Hengli Petrochemical</td>\n",
       "      <td>27,961</td>\n",
       "      <td>31.9%</td>\n",
       "      <td>China, Suzhou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>Linde</td>\n",
       "      <td>27,926</td>\n",
       "      <td>14.5%</td>\n",
       "      <td>Ireland, Dublin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>Air Liquide</td>\n",
       "      <td>27,148</td>\n",
       "      <td>13.4%</td>\n",
       "      <td>France, Paris</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>Syngenta</td>\n",
       "      <td>24,900</td>\n",
       "      <td>20.9%</td>\n",
       "      <td>Switzerland, Basel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>Reliance Industries</td>\n",
       "      <td>22,583</td>\n",
       "      <td>65.6%</td>\n",
       "      <td>India, Mumbai</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>Wanhua</td>\n",
       "      <td>22,561</td>\n",
       "      <td>98.2%</td>\n",
       "      <td>China, Yantai</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>Braskem</td>\n",
       "      <td>19,575</td>\n",
       "      <td>80.4%</td>\n",
       "      <td>Brazil, São Paulo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>Sumitomo Chemical</td>\n",
       "      <td>19,176</td>\n",
       "      <td>24.7%</td>\n",
       "      <td>Japan, Tokyo and Osaka</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>Shin-Etsu Chemical</td>\n",
       "      <td>18,885</td>\n",
       "      <td>38.6%</td>\n",
       "      <td>Japan, Tokyo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>Covestro</td>\n",
       "      <td>18,813</td>\n",
       "      <td>48.5%</td>\n",
       "      <td>Germany, Leverkusen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>Toray Industries</td>\n",
       "      <td>17,856</td>\n",
       "      <td>20.9%</td>\n",
       "      <td>Japan, Tokyo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>Evonik Industries</td>\n",
       "      <td>17,692</td>\n",
       "      <td>22.6%</td>\n",
       "      <td>Germany, Essen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>Shell</td>\n",
       "      <td>16,993</td>\n",
       "      <td>45.0%</td>\n",
       "      <td>United Kingdom, London</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>DuPont</td>\n",
       "      <td>16,653</td>\n",
       "      <td>18.4%</td>\n",
       "      <td>United States, Wilmington, Delaware</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>Yara</td>\n",
       "      <td>16,617</td>\n",
       "      <td>43.4%</td>\n",
       "      <td>Norway, Oslo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>Rongsheng Petrochemical</td>\n",
       "      <td>16,001</td>\n",
       "      <td>59.6%</td>\n",
       "      <td>China, Hangzhou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>Lotte Chemical</td>\n",
       "      <td>15,827</td>\n",
       "      <td>48.2%</td>\n",
       "      <td>South Korea, Seoul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>Mitsui Chemicals</td>\n",
       "      <td>14,681</td>\n",
       "      <td>33.1%</td>\n",
       "      <td>Japan, Tokyo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>Indorama Ventures</td>\n",
       "      <td>14,626</td>\n",
       "      <td>41.2%</td>\n",
       "      <td>Thailand, Bangkok</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>31</td>\n",
       "      <td>Chevron Phillips Chemical</td>\n",
       "      <td>14,104</td>\n",
       "      <td>67.1%</td>\n",
       "      <td>United States, The Woodlands, Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>Umicore</td>\n",
       "      <td>13,567</td>\n",
       "      <td>34.4%</td>\n",
       "      <td>Belgium, Brussels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>Solvay</td>\n",
       "      <td>13,527</td>\n",
       "      <td>17.7%</td>\n",
       "      <td>Belgium, Brussels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>Bayer</td>\n",
       "      <td>12,743</td>\n",
       "      <td>9.7%</td>\n",
       "      <td>Germany, Leverkusen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>35</td>\n",
       "      <td>Mosaic</td>\n",
       "      <td>12,357</td>\n",
       "      <td>42.3%</td>\n",
       "      <td>United States, Plymouth, Minnesota</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>36</td>\n",
       "      <td>Nutrien</td>\n",
       "      <td>11,590</td>\n",
       "      <td>62.0%</td>\n",
       "      <td>Canada, Saskatoon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>Arkema</td>\n",
       "      <td>11,261</td>\n",
       "      <td>20.7%</td>\n",
       "      <td>France, Colombes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>38</td>\n",
       "      <td>Asahi Kasei</td>\n",
       "      <td>10,908</td>\n",
       "      <td>20.9%</td>\n",
       "      <td>Japan, Tokyo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>39</td>\n",
       "      <td>DSM</td>\n",
       "      <td>10,888</td>\n",
       "      <td>13.5%</td>\n",
       "      <td>Netherlands, Heerlen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>39</td>\n",
       "      <td>Hanwha Solutions</td>\n",
       "      <td>10,888</td>\n",
       "      <td>22.8%</td>\n",
       "      <td>South Korea, Seoul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>41</td>\n",
       "      <td>Eastman Chemical</td>\n",
       "      <td>10,476</td>\n",
       "      <td>23.6%</td>\n",
       "      <td>United States, Kingsport, Tennessee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>42</td>\n",
       "      <td>Johnson Matthey</td>\n",
       "      <td>10,412</td>\n",
       "      <td>2.48%</td>\n",
       "      <td>United Kingdom, London</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>43</td>\n",
       "      <td>Air Products</td>\n",
       "      <td>10,323</td>\n",
       "      <td>16.6%</td>\n",
       "      <td>United States, Allentown, Pennsylvania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>44</td>\n",
       "      <td>Eurochem</td>\n",
       "      <td>14,269</td>\n",
       "      <td>22.6%</td>\n",
       "      <td>Switzerland, Zug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>45</td>\n",
       "      <td>Borealis</td>\n",
       "      <td>10,164</td>\n",
       "      <td>26.0%</td>\n",
       "      <td>Austria, Vienna</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>46</td>\n",
       "      <td>PTT Global Chemical</td>\n",
       "      <td>16,521</td>\n",
       "      <td>51.7%</td>\n",
       "      <td>Thailand, Bangkok</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>47</td>\n",
       "      <td>Sasol</td>\n",
       "      <td>9,011</td>\n",
       "      <td>10.8%</td>\n",
       "      <td>South Africa, Johannesburg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>48</td>\n",
       "      <td>Tongkun Group</td>\n",
       "      <td>8,996</td>\n",
       "      <td>28.5%</td>\n",
       "      <td>China, Tongxiang</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>49</td>\n",
       "      <td>Lanxess</td>\n",
       "      <td>8,940</td>\n",
       "      <td>23.8%</td>\n",
       "      <td>Germany, Cologne</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>50</td>\n",
       "      <td>Hengyi Petrochemical</td>\n",
       "      <td>8,858</td>\n",
       "      <td>66.8%</td>\n",
       "      <td>China, Hangzhou</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Rank[4]                    Company Chemical sales in 2021USD millions[A]  \\\n",
       "0        1                       BASF                                92,982   \n",
       "1        2                    Sinopec                                65,848   \n",
       "2        3                        Dow                                54,968   \n",
       "3        4                      SABIC                                43,230   \n",
       "4        5           Formosa Plastics                                43,173   \n",
       "5        6                      Ineos                                39,937   \n",
       "6        7                 Petrochina                                39,693   \n",
       "7        8  LyondellBasell Industries                                38,995   \n",
       "8        9                    LG Chem                                37,257   \n",
       "9       10                 ExxonMobil                                36,858   \n",
       "10      11  Mitsubishi Chemical Group                                30,719   \n",
       "11      12       Hengli Petrochemical                                27,961   \n",
       "12      13                      Linde                                27,926   \n",
       "13      14                Air Liquide                                27,148   \n",
       "14      15                   Syngenta                                24,900   \n",
       "15      16        Reliance Industries                                22,583   \n",
       "16      17                     Wanhua                                22,561   \n",
       "17      18                    Braskem                                19,575   \n",
       "18      19          Sumitomo Chemical                                19,176   \n",
       "19      20         Shin-Etsu Chemical                                18,885   \n",
       "20      21                   Covestro                                18,813   \n",
       "21      22           Toray Industries                                17,856   \n",
       "22      23          Evonik Industries                                17,692   \n",
       "23      24                      Shell                                16,993   \n",
       "24      25                     DuPont                                16,653   \n",
       "25      26                       Yara                                16,617   \n",
       "26      27    Rongsheng Petrochemical                                16,001   \n",
       "27      28             Lotte Chemical                                15,827   \n",
       "28      29           Mitsui Chemicals                                14,681   \n",
       "29      30          Indorama Ventures                                14,626   \n",
       "30      31  Chevron Phillips Chemical                                14,104   \n",
       "31      32                    Umicore                                13,567   \n",
       "32      33                     Solvay                                13,527   \n",
       "33      34                      Bayer                                12,743   \n",
       "34      35                     Mosaic                                12,357   \n",
       "35      36                    Nutrien                                11,590   \n",
       "36      37                     Arkema                                11,261   \n",
       "37      38                Asahi Kasei                                10,908   \n",
       "38      39                        DSM                                10,888   \n",
       "39      39           Hanwha Solutions                                10,888   \n",
       "40      41           Eastman Chemical                                10,476   \n",
       "41      42            Johnson Matthey                                10,412   \n",
       "42      43               Air Products                                10,323   \n",
       "43      44                   Eurochem                                14,269   \n",
       "44      45                   Borealis                                10,164   \n",
       "45      46        PTT Global Chemical                                16,521   \n",
       "46      47                      Sasol                                 9,011   \n",
       "47      48              Tongkun Group                                 8,996   \n",
       "48      49                    Lanxess                                 8,940   \n",
       "49      50       Hengyi Petrochemical                                 8,858   \n",
       "\n",
       "   Change from 2020in percent                            Headquarters  \n",
       "0                       32.9%          Germany, Ludwigshafen am Rhein  \n",
       "1                       31.9%                          China, Beijing  \n",
       "2                       42.6%        United States, Midland, Michigan  \n",
       "3                       50.1%                    Saudi Arabia, Riyadh  \n",
       "4                       47.8%                          Taiwan, Taipei  \n",
       "5                        121%                  United Kingdom, London  \n",
       "6                       41.7%                          China, Beijing  \n",
       "7                       66.6%           United States, Houston, Texas  \n",
       "8                       41.8%                      South Korea, Seoul  \n",
       "9                       59.6%            United States, Spring, Texas  \n",
       "10                      24.8%                            Japan, Tokyo  \n",
       "11                      31.9%                           China, Suzhou  \n",
       "12                      14.5%                         Ireland, Dublin  \n",
       "13                      13.4%                           France, Paris  \n",
       "14                      20.9%                      Switzerland, Basel  \n",
       "15                      65.6%                           India, Mumbai  \n",
       "16                      98.2%                           China, Yantai  \n",
       "17                      80.4%                       Brazil, São Paulo  \n",
       "18                      24.7%                  Japan, Tokyo and Osaka  \n",
       "19                      38.6%                            Japan, Tokyo  \n",
       "20                      48.5%                     Germany, Leverkusen  \n",
       "21                      20.9%                            Japan, Tokyo  \n",
       "22                      22.6%                          Germany, Essen  \n",
       "23                      45.0%                  United Kingdom, London  \n",
       "24                      18.4%     United States, Wilmington, Delaware  \n",
       "25                      43.4%                            Norway, Oslo  \n",
       "26                      59.6%                         China, Hangzhou  \n",
       "27                      48.2%                      South Korea, Seoul  \n",
       "28                      33.1%                            Japan, Tokyo  \n",
       "29                      41.2%                       Thailand, Bangkok  \n",
       "30                      67.1%     United States, The Woodlands, Texas  \n",
       "31                      34.4%                       Belgium, Brussels  \n",
       "32                      17.7%                       Belgium, Brussels  \n",
       "33                       9.7%                     Germany, Leverkusen  \n",
       "34                      42.3%      United States, Plymouth, Minnesota  \n",
       "35                      62.0%                       Canada, Saskatoon  \n",
       "36                      20.7%                        France, Colombes  \n",
       "37                      20.9%                            Japan, Tokyo  \n",
       "38                      13.5%                    Netherlands, Heerlen  \n",
       "39                      22.8%                      South Korea, Seoul  \n",
       "40                      23.6%     United States, Kingsport, Tennessee  \n",
       "41                      2.48%                  United Kingdom, London  \n",
       "42                      16.6%  United States, Allentown, Pennsylvania  \n",
       "43                      22.6%                        Switzerland, Zug  \n",
       "44                      26.0%                         Austria, Vienna  \n",
       "45                      51.7%                       Thailand, Bangkok  \n",
       "46                      10.8%              South Africa, Johannesburg  \n",
       "47                      28.5%                        China, Tongxiang  \n",
       "48                      23.8%                        Germany, Cologne  \n",
       "49                      66.8%                         China, Hangzhou  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Section 02: Data cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* View dataset info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 50 entries, 0 to 49\n",
      "Data columns (total 5 columns):\n",
      " #   Column                                 Non-Null Count  Dtype \n",
      "---  ------                                 --------------  ----- \n",
      " 0   Rank[4]                                50 non-null     object\n",
      " 1   Company                                50 non-null     object\n",
      " 2   Chemical sales in 2021USD millions[A]  50 non-null     object\n",
      " 3   Change from 2020in percent             50 non-null     object\n",
      " 4   Headquarters                           50 non-null     object\n",
      "dtypes: object(5)\n",
      "memory usage: 2.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\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>Rank[4]</th>\n",
       "      <th>Company</th>\n",
       "      <th>Chemical sales in 2021USD millions[A]</th>\n",
       "      <th>Change from 2020in percent</th>\n",
       "      <th>Headquarters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>BASF</td>\n",
       "      <td>92,982</td>\n",
       "      <td>32.9%</td>\n",
       "      <td>Germany, Ludwigshafen am Rhein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Sinopec</td>\n",
       "      <td>65,848</td>\n",
       "      <td>31.9%</td>\n",
       "      <td>China, Beijing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Dow</td>\n",
       "      <td>54,968</td>\n",
       "      <td>42.6%</td>\n",
       "      <td>United States, Midland, Michigan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>SABIC</td>\n",
       "      <td>43,230</td>\n",
       "      <td>50.1%</td>\n",
       "      <td>Saudi Arabia, Riyadh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Formosa Plastics</td>\n",
       "      <td>43,173</td>\n",
       "      <td>47.8%</td>\n",
       "      <td>Taiwan, Taipei</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Rank[4]           Company Chemical sales in 2021USD millions[A]  \\\n",
       "0       1              BASF                                92,982   \n",
       "1       2           Sinopec                                65,848   \n",
       "2       3               Dow                                54,968   \n",
       "3       4             SABIC                                43,230   \n",
       "4       5  Formosa Plastics                                43,173   \n",
       "\n",
       "  Change from 2020in percent                      Headquarters  \n",
       "0                      32.9%    Germany, Ludwigshafen am Rhein  \n",
       "1                      31.9%                    China, Beijing  \n",
       "2                      42.6%  United States, Midland, Michigan  \n",
       "3                      50.1%              Saudi Arabia, Riyadh  \n",
       "4                      47.8%                    Taiwan, Taipei  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>Rank[4]</th>\n",
       "      <th>Company</th>\n",
       "      <th>Chemical sales in 2021USD millions[A]</th>\n",
       "      <th>Change from 2020in percent</th>\n",
       "      <th>Headquarters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>46</td>\n",
       "      <td>PTT Global Chemical</td>\n",
       "      <td>16,521</td>\n",
       "      <td>51.7%</td>\n",
       "      <td>Thailand, Bangkok</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>47</td>\n",
       "      <td>Sasol</td>\n",
       "      <td>9,011</td>\n",
       "      <td>10.8%</td>\n",
       "      <td>South Africa, Johannesburg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>48</td>\n",
       "      <td>Tongkun Group</td>\n",
       "      <td>8,996</td>\n",
       "      <td>28.5%</td>\n",
       "      <td>China, Tongxiang</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>49</td>\n",
       "      <td>Lanxess</td>\n",
       "      <td>8,940</td>\n",
       "      <td>23.8%</td>\n",
       "      <td>Germany, Cologne</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>50</td>\n",
       "      <td>Hengyi Petrochemical</td>\n",
       "      <td>8,858</td>\n",
       "      <td>66.8%</td>\n",
       "      <td>China, Hangzhou</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Rank[4]               Company Chemical sales in 2021USD millions[A]  \\\n",
       "45      46   PTT Global Chemical                                16,521   \n",
       "46      47                 Sasol                                 9,011   \n",
       "47      48         Tongkun Group                                 8,996   \n",
       "48      49               Lanxess                                 8,940   \n",
       "49      50  Hengyi Petrochemical                                 8,858   \n",
       "\n",
       "   Change from 2020in percent                Headquarters  \n",
       "45                      51.7%           Thailand, Bangkok  \n",
       "46                      10.8%  South Africa, Johannesburg  \n",
       "47                      28.5%            China, Tongxiang  \n",
       "48                      23.8%            Germany, Cologne  \n",
       "49                      66.8%             China, Hangzhou  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Clean up column names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .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>Rank</th>\n",
       "      <th>Company</th>\n",
       "      <th>Sales in 2021 in USD millions</th>\n",
       "      <th>Growth in 2021 in %</th>\n",
       "      <th>Headquarters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>BASF</td>\n",
       "      <td>92,982</td>\n",
       "      <td>32.9%</td>\n",
       "      <td>Germany, Ludwigshafen am Rhein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Sinopec</td>\n",
       "      <td>65,848</td>\n",
       "      <td>31.9%</td>\n",
       "      <td>China, Beijing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Dow</td>\n",
       "      <td>54,968</td>\n",
       "      <td>42.6%</td>\n",
       "      <td>United States, Midland, Michigan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>SABIC</td>\n",
       "      <td>43,230</td>\n",
       "      <td>50.1%</td>\n",
       "      <td>Saudi Arabia, Riyadh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Formosa Plastics</td>\n",
       "      <td>43,173</td>\n",
       "      <td>47.8%</td>\n",
       "      <td>Taiwan, Taipei</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>Ineos</td>\n",
       "      <td>39,937</td>\n",
       "      <td>121%</td>\n",
       "      <td>United Kingdom, London</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>Petrochina</td>\n",
       "      <td>39,693</td>\n",
       "      <td>41.7%</td>\n",
       "      <td>China, Beijing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>LyondellBasell Industries</td>\n",
       "      <td>38,995</td>\n",
       "      <td>66.6%</td>\n",
       "      <td>United States, Houston, Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>LG Chem</td>\n",
       "      <td>37,257</td>\n",
       "      <td>41.8%</td>\n",
       "      <td>South Korea, Seoul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>36,858</td>\n",
       "      <td>59.6%</td>\n",
       "      <td>United States, Spring, Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>Mitsubishi Chemical Group</td>\n",
       "      <td>30,719</td>\n",
       "      <td>24.8%</td>\n",
       "      <td>Japan, Tokyo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>Hengli Petrochemical</td>\n",
       "      <td>27,961</td>\n",
       "      <td>31.9%</td>\n",
       "      <td>China, Suzhou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>Linde</td>\n",
       "      <td>27,926</td>\n",
       "      <td>14.5%</td>\n",
       "      <td>Ireland, Dublin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>Air Liquide</td>\n",
       "      <td>27,148</td>\n",
       "      <td>13.4%</td>\n",
       "      <td>France, Paris</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>Syngenta</td>\n",
       "      <td>24,900</td>\n",
       "      <td>20.9%</td>\n",
       "      <td>Switzerland, Basel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>Reliance Industries</td>\n",
       "      <td>22,583</td>\n",
       "      <td>65.6%</td>\n",
       "      <td>India, Mumbai</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>Wanhua</td>\n",
       "      <td>22,561</td>\n",
       "      <td>98.2%</td>\n",
       "      <td>China, Yantai</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>Braskem</td>\n",
       "      <td>19,575</td>\n",
       "      <td>80.4%</td>\n",
       "      <td>Brazil, São Paulo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>Sumitomo Chemical</td>\n",
       "      <td>19,176</td>\n",
       "      <td>24.7%</td>\n",
       "      <td>Japan, Tokyo and Osaka</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>Shin-Etsu Chemical</td>\n",
       "      <td>18,885</td>\n",
       "      <td>38.6%</td>\n",
       "      <td>Japan, Tokyo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>Covestro</td>\n",
       "      <td>18,813</td>\n",
       "      <td>48.5%</td>\n",
       "      <td>Germany, Leverkusen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>Toray Industries</td>\n",
       "      <td>17,856</td>\n",
       "      <td>20.9%</td>\n",
       "      <td>Japan, Tokyo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>Evonik Industries</td>\n",
       "      <td>17,692</td>\n",
       "      <td>22.6%</td>\n",
       "      <td>Germany, Essen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>Shell</td>\n",
       "      <td>16,993</td>\n",
       "      <td>45.0%</td>\n",
       "      <td>United Kingdom, London</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>DuPont</td>\n",
       "      <td>16,653</td>\n",
       "      <td>18.4%</td>\n",
       "      <td>United States, Wilmington, Delaware</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>Yara</td>\n",
       "      <td>16,617</td>\n",
       "      <td>43.4%</td>\n",
       "      <td>Norway, Oslo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>Rongsheng Petrochemical</td>\n",
       "      <td>16,001</td>\n",
       "      <td>59.6%</td>\n",
       "      <td>China, Hangzhou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>Lotte Chemical</td>\n",
       "      <td>15,827</td>\n",
       "      <td>48.2%</td>\n",
       "      <td>South Korea, Seoul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>Mitsui Chemicals</td>\n",
       "      <td>14,681</td>\n",
       "      <td>33.1%</td>\n",
       "      <td>Japan, Tokyo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>Indorama Ventures</td>\n",
       "      <td>14,626</td>\n",
       "      <td>41.2%</td>\n",
       "      <td>Thailand, Bangkok</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>31</td>\n",
       "      <td>Chevron Phillips Chemical</td>\n",
       "      <td>14,104</td>\n",
       "      <td>67.1%</td>\n",
       "      <td>United States, The Woodlands, Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>Umicore</td>\n",
       "      <td>13,567</td>\n",
       "      <td>34.4%</td>\n",
       "      <td>Belgium, Brussels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>Solvay</td>\n",
       "      <td>13,527</td>\n",
       "      <td>17.7%</td>\n",
       "      <td>Belgium, Brussels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>Bayer</td>\n",
       "      <td>12,743</td>\n",
       "      <td>9.7%</td>\n",
       "      <td>Germany, Leverkusen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>35</td>\n",
       "      <td>Mosaic</td>\n",
       "      <td>12,357</td>\n",
       "      <td>42.3%</td>\n",
       "      <td>United States, Plymouth, Minnesota</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>36</td>\n",
       "      <td>Nutrien</td>\n",
       "      <td>11,590</td>\n",
       "      <td>62.0%</td>\n",
       "      <td>Canada, Saskatoon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>Arkema</td>\n",
       "      <td>11,261</td>\n",
       "      <td>20.7%</td>\n",
       "      <td>France, Colombes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>38</td>\n",
       "      <td>Asahi Kasei</td>\n",
       "      <td>10,908</td>\n",
       "      <td>20.9%</td>\n",
       "      <td>Japan, Tokyo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>39</td>\n",
       "      <td>DSM</td>\n",
       "      <td>10,888</td>\n",
       "      <td>13.5%</td>\n",
       "      <td>Netherlands, Heerlen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>39</td>\n",
       "      <td>Hanwha Solutions</td>\n",
       "      <td>10,888</td>\n",
       "      <td>22.8%</td>\n",
       "      <td>South Korea, Seoul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>41</td>\n",
       "      <td>Eastman Chemical</td>\n",
       "      <td>10,476</td>\n",
       "      <td>23.6%</td>\n",
       "      <td>United States, Kingsport, Tennessee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>42</td>\n",
       "      <td>Johnson Matthey</td>\n",
       "      <td>10,412</td>\n",
       "      <td>2.48%</td>\n",
       "      <td>United Kingdom, London</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>43</td>\n",
       "      <td>Air Products</td>\n",
       "      <td>10,323</td>\n",
       "      <td>16.6%</td>\n",
       "      <td>United States, Allentown, Pennsylvania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>44</td>\n",
       "      <td>Eurochem</td>\n",
       "      <td>14,269</td>\n",
       "      <td>22.6%</td>\n",
       "      <td>Switzerland, Zug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>45</td>\n",
       "      <td>Borealis</td>\n",
       "      <td>10,164</td>\n",
       "      <td>26.0%</td>\n",
       "      <td>Austria, Vienna</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>46</td>\n",
       "      <td>PTT Global Chemical</td>\n",
       "      <td>16,521</td>\n",
       "      <td>51.7%</td>\n",
       "      <td>Thailand, Bangkok</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>47</td>\n",
       "      <td>Sasol</td>\n",
       "      <td>9,011</td>\n",
       "      <td>10.8%</td>\n",
       "      <td>South Africa, Johannesburg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>48</td>\n",
       "      <td>Tongkun Group</td>\n",
       "      <td>8,996</td>\n",
       "      <td>28.5%</td>\n",
       "      <td>China, Tongxiang</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>49</td>\n",
       "      <td>Lanxess</td>\n",
       "      <td>8,940</td>\n",
       "      <td>23.8%</td>\n",
       "      <td>Germany, Cologne</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>50</td>\n",
       "      <td>Hengyi Petrochemical</td>\n",
       "      <td>8,858</td>\n",
       "      <td>66.8%</td>\n",
       "      <td>China, Hangzhou</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Rank                    Company Sales in 2021 in USD millions  \\\n",
       "0     1                       BASF                        92,982   \n",
       "1     2                    Sinopec                        65,848   \n",
       "2     3                        Dow                        54,968   \n",
       "3     4                      SABIC                        43,230   \n",
       "4     5           Formosa Plastics                        43,173   \n",
       "5     6                      Ineos                        39,937   \n",
       "6     7                 Petrochina                        39,693   \n",
       "7     8  LyondellBasell Industries                        38,995   \n",
       "8     9                    LG Chem                        37,257   \n",
       "9    10                 ExxonMobil                        36,858   \n",
       "10   11  Mitsubishi Chemical Group                        30,719   \n",
       "11   12       Hengli Petrochemical                        27,961   \n",
       "12   13                      Linde                        27,926   \n",
       "13   14                Air Liquide                        27,148   \n",
       "14   15                   Syngenta                        24,900   \n",
       "15   16        Reliance Industries                        22,583   \n",
       "16   17                     Wanhua                        22,561   \n",
       "17   18                    Braskem                        19,575   \n",
       "18   19          Sumitomo Chemical                        19,176   \n",
       "19   20         Shin-Etsu Chemical                        18,885   \n",
       "20   21                   Covestro                        18,813   \n",
       "21   22           Toray Industries                        17,856   \n",
       "22   23          Evonik Industries                        17,692   \n",
       "23   24                      Shell                        16,993   \n",
       "24   25                     DuPont                        16,653   \n",
       "25   26                       Yara                        16,617   \n",
       "26   27    Rongsheng Petrochemical                        16,001   \n",
       "27   28             Lotte Chemical                        15,827   \n",
       "28   29           Mitsui Chemicals                        14,681   \n",
       "29   30          Indorama Ventures                        14,626   \n",
       "30   31  Chevron Phillips Chemical                        14,104   \n",
       "31   32                    Umicore                        13,567   \n",
       "32   33                     Solvay                        13,527   \n",
       "33   34                      Bayer                        12,743   \n",
       "34   35                     Mosaic                        12,357   \n",
       "35   36                    Nutrien                        11,590   \n",
       "36   37                     Arkema                        11,261   \n",
       "37   38                Asahi Kasei                        10,908   \n",
       "38   39                        DSM                        10,888   \n",
       "39   39           Hanwha Solutions                        10,888   \n",
       "40   41           Eastman Chemical                        10,476   \n",
       "41   42            Johnson Matthey                        10,412   \n",
       "42   43               Air Products                        10,323   \n",
       "43   44                   Eurochem                        14,269   \n",
       "44   45                   Borealis                        10,164   \n",
       "45   46        PTT Global Chemical                        16,521   \n",
       "46   47                      Sasol                         9,011   \n",
       "47   48              Tongkun Group                         8,996   \n",
       "48   49                    Lanxess                         8,940   \n",
       "49   50       Hengyi Petrochemical                         8,858   \n",
       "\n",
       "   Growth in 2021 in %                            Headquarters  \n",
       "0                32.9%          Germany, Ludwigshafen am Rhein  \n",
       "1                31.9%                          China, Beijing  \n",
       "2                42.6%        United States, Midland, Michigan  \n",
       "3                50.1%                    Saudi Arabia, Riyadh  \n",
       "4                47.8%                          Taiwan, Taipei  \n",
       "5                 121%                  United Kingdom, London  \n",
       "6                41.7%                          China, Beijing  \n",
       "7                66.6%           United States, Houston, Texas  \n",
       "8                41.8%                      South Korea, Seoul  \n",
       "9                59.6%            United States, Spring, Texas  \n",
       "10               24.8%                            Japan, Tokyo  \n",
       "11               31.9%                           China, Suzhou  \n",
       "12               14.5%                         Ireland, Dublin  \n",
       "13               13.4%                           France, Paris  \n",
       "14               20.9%                      Switzerland, Basel  \n",
       "15               65.6%                           India, Mumbai  \n",
       "16               98.2%                           China, Yantai  \n",
       "17               80.4%                       Brazil, São Paulo  \n",
       "18               24.7%                  Japan, Tokyo and Osaka  \n",
       "19               38.6%                            Japan, Tokyo  \n",
       "20               48.5%                     Germany, Leverkusen  \n",
       "21               20.9%                            Japan, Tokyo  \n",
       "22               22.6%                          Germany, Essen  \n",
       "23               45.0%                  United Kingdom, London  \n",
       "24               18.4%     United States, Wilmington, Delaware  \n",
       "25               43.4%                            Norway, Oslo  \n",
       "26               59.6%                         China, Hangzhou  \n",
       "27               48.2%                      South Korea, Seoul  \n",
       "28               33.1%                            Japan, Tokyo  \n",
       "29               41.2%                       Thailand, Bangkok  \n",
       "30               67.1%     United States, The Woodlands, Texas  \n",
       "31               34.4%                       Belgium, Brussels  \n",
       "32               17.7%                       Belgium, Brussels  \n",
       "33                9.7%                     Germany, Leverkusen  \n",
       "34               42.3%      United States, Plymouth, Minnesota  \n",
       "35               62.0%                       Canada, Saskatoon  \n",
       "36               20.7%                        France, Colombes  \n",
       "37               20.9%                            Japan, Tokyo  \n",
       "38               13.5%                    Netherlands, Heerlen  \n",
       "39               22.8%                      South Korea, Seoul  \n",
       "40               23.6%     United States, Kingsport, Tennessee  \n",
       "41               2.48%                  United Kingdom, London  \n",
       "42               16.6%  United States, Allentown, Pennsylvania  \n",
       "43               22.6%                        Switzerland, Zug  \n",
       "44               26.0%                         Austria, Vienna  \n",
       "45               51.7%                       Thailand, Bangkok  \n",
       "46               10.8%              South Africa, Johannesburg  \n",
       "47               28.5%                        China, Tongxiang  \n",
       "48               23.8%                        Germany, Cologne  \n",
       "49               66.8%                         China, Hangzhou  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.rename(columns = {\"Rank[4]\":\"Rank\", \n",
    "                          \"Company\":\"Company\", \n",
    "                          \"Chemical sales in 2021USD millions[A]\":\"Sales in 2021 in USD millions\", \n",
    "                          \"Change from 2020in percent\":\"Growth in 2021 in %\", \n",
    "                          \"Headquarters\":\"Headquarters\"})\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Clean up numerical values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert_currency(val):\n",
    "    \"\"\"\n",
    "    Removes comma from string parameter and returns it as an integer\n",
    "    \n",
    "    Parameter\n",
    "    ----------\n",
    "    val : str\n",
    "        string value of sales in 2021 in USD millions\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    new_val : int\n",
    "        integer value of sales in 2021 in USD millions\n",
    "    \"\"\"\n",
    "    new_val = val.replace(',','')\n",
    "    return int(new_val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Sales in 2021 in USD millions\"] = df[\"Sales in 2021 in USD millions\"].apply(convert_currency)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert_percent(val):\n",
    "    \"\"\"\n",
    "    Removes percentage sign from string parameter and returns it as a float round to two decimal places\n",
    "    \n",
    "    Parameter\n",
    "    ----------\n",
    "    val : str\n",
    "        string value of growth in 2021 in %\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    new_val : int\n",
    "        float round to two decimal places value of growth in 2021 in %\n",
    "    \"\"\"\n",
    "    new_val = val.replace('%', '')\n",
    "    return round(float(new_val), 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 50 entries, 0 to 49\n",
      "Data columns (total 5 columns):\n",
      " #   Column                         Non-Null Count  Dtype  \n",
      "---  ------                         --------------  -----  \n",
      " 0   Rank                           50 non-null     object \n",
      " 1   Company                        50 non-null     object \n",
      " 2   Sales in 2021 in USD millions  50 non-null     int64  \n",
      " 3   Growth in 2021 in %            50 non-null     float64\n",
      " 4   Headquarters                   50 non-null     object \n",
      "dtypes: float64(1), int64(1), object(3)\n",
      "memory usage: 2.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df[\"Growth in 2021 in %\"] = df[\"Growth in 2021 in %\"].apply(convert_percent)\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Change Data Types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Rank\"] = df[\"Rank\"].astype(\"int\")\n",
    "df[\"Sales in 2021 in USD millions\"] = df[\"Sales in 2021 in USD millions\"].astype(\"int\")\n",
    "df[\"Growth in 2021 in %\"] = df[\"Growth in 2021 in %\"].astype(\"float\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Replacing data that was transfered with errors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Growth in 2021 in %\"] = df[\"Growth in 2021 in %\"].replace(18.4, -18.4)\n",
    "df[\"Growth in 2021 in %\"] = df[\"Growth in 2021 in %\"].replace(2.48, -2.48)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Check everything is correct"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 50 entries, 0 to 49\n",
      "Data columns (total 5 columns):\n",
      " #   Column                         Non-Null Count  Dtype  \n",
      "---  ------                         --------------  -----  \n",
      " 0   Rank                           50 non-null     int64  \n",
      " 1   Company                        50 non-null     object \n",
      " 2   Sales in 2021 in USD millions  50 non-null     int64  \n",
      " 3   Growth in 2021 in %            50 non-null     float64\n",
      " 4   Headquarters                   50 non-null     object \n",
      "dtypes: float64(1), int64(2), object(2)\n",
      "memory usage: 2.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **The clean dataset:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>Rank</th>\n",
       "      <th>Company</th>\n",
       "      <th>Sales in 2021 in USD millions</th>\n",
       "      <th>Growth in 2021 in %</th>\n",
       "      <th>Headquarters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>BASF</td>\n",
       "      <td>92982</td>\n",
       "      <td>32.90</td>\n",
       "      <td>Germany, Ludwigshafen am Rhein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Sinopec</td>\n",
       "      <td>65848</td>\n",
       "      <td>31.90</td>\n",
       "      <td>China, Beijing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Dow</td>\n",
       "      <td>54968</td>\n",
       "      <td>42.60</td>\n",
       "      <td>United States, Midland, Michigan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>SABIC</td>\n",
       "      <td>43230</td>\n",
       "      <td>50.10</td>\n",
       "      <td>Saudi Arabia, Riyadh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Formosa Plastics</td>\n",
       "      <td>43173</td>\n",
       "      <td>47.80</td>\n",
       "      <td>Taiwan, Taipei</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>Ineos</td>\n",
       "      <td>39937</td>\n",
       "      <td>121.00</td>\n",
       "      <td>United Kingdom, London</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>Petrochina</td>\n",
       "      <td>39693</td>\n",
       "      <td>41.70</td>\n",
       "      <td>China, Beijing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>LyondellBasell Industries</td>\n",
       "      <td>38995</td>\n",
       "      <td>66.60</td>\n",
       "      <td>United States, Houston, Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>LG Chem</td>\n",
       "      <td>37257</td>\n",
       "      <td>41.80</td>\n",
       "      <td>South Korea, Seoul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>36858</td>\n",
       "      <td>59.60</td>\n",
       "      <td>United States, Spring, Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>Mitsubishi Chemical Group</td>\n",
       "      <td>30719</td>\n",
       "      <td>24.80</td>\n",
       "      <td>Japan, Tokyo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>Hengli Petrochemical</td>\n",
       "      <td>27961</td>\n",
       "      <td>31.90</td>\n",
       "      <td>China, Suzhou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>Linde</td>\n",
       "      <td>27926</td>\n",
       "      <td>14.50</td>\n",
       "      <td>Ireland, Dublin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>Air Liquide</td>\n",
       "      <td>27148</td>\n",
       "      <td>13.40</td>\n",
       "      <td>France, Paris</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>Syngenta</td>\n",
       "      <td>24900</td>\n",
       "      <td>20.90</td>\n",
       "      <td>Switzerland, Basel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>Reliance Industries</td>\n",
       "      <td>22583</td>\n",
       "      <td>65.60</td>\n",
       "      <td>India, Mumbai</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>Wanhua</td>\n",
       "      <td>22561</td>\n",
       "      <td>98.20</td>\n",
       "      <td>China, Yantai</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>Braskem</td>\n",
       "      <td>19575</td>\n",
       "      <td>80.40</td>\n",
       "      <td>Brazil, São Paulo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>Sumitomo Chemical</td>\n",
       "      <td>19176</td>\n",
       "      <td>24.70</td>\n",
       "      <td>Japan, Tokyo and Osaka</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>Shin-Etsu Chemical</td>\n",
       "      <td>18885</td>\n",
       "      <td>38.60</td>\n",
       "      <td>Japan, Tokyo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>Covestro</td>\n",
       "      <td>18813</td>\n",
       "      <td>48.50</td>\n",
       "      <td>Germany, Leverkusen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>Toray Industries</td>\n",
       "      <td>17856</td>\n",
       "      <td>20.90</td>\n",
       "      <td>Japan, Tokyo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>Evonik Industries</td>\n",
       "      <td>17692</td>\n",
       "      <td>22.60</td>\n",
       "      <td>Germany, Essen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>Shell</td>\n",
       "      <td>16993</td>\n",
       "      <td>45.00</td>\n",
       "      <td>United Kingdom, London</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>DuPont</td>\n",
       "      <td>16653</td>\n",
       "      <td>-18.40</td>\n",
       "      <td>United States, Wilmington, Delaware</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>Yara</td>\n",
       "      <td>16617</td>\n",
       "      <td>43.40</td>\n",
       "      <td>Norway, Oslo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>Rongsheng Petrochemical</td>\n",
       "      <td>16001</td>\n",
       "      <td>59.60</td>\n",
       "      <td>China, Hangzhou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>Lotte Chemical</td>\n",
       "      <td>15827</td>\n",
       "      <td>48.20</td>\n",
       "      <td>South Korea, Seoul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>Mitsui Chemicals</td>\n",
       "      <td>14681</td>\n",
       "      <td>33.10</td>\n",
       "      <td>Japan, Tokyo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>Indorama Ventures</td>\n",
       "      <td>14626</td>\n",
       "      <td>41.20</td>\n",
       "      <td>Thailand, Bangkok</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>31</td>\n",
       "      <td>Chevron Phillips Chemical</td>\n",
       "      <td>14104</td>\n",
       "      <td>67.10</td>\n",
       "      <td>United States, The Woodlands, Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>Umicore</td>\n",
       "      <td>13567</td>\n",
       "      <td>34.40</td>\n",
       "      <td>Belgium, Brussels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>Solvay</td>\n",
       "      <td>13527</td>\n",
       "      <td>17.70</td>\n",
       "      <td>Belgium, Brussels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>Bayer</td>\n",
       "      <td>12743</td>\n",
       "      <td>9.70</td>\n",
       "      <td>Germany, Leverkusen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>35</td>\n",
       "      <td>Mosaic</td>\n",
       "      <td>12357</td>\n",
       "      <td>42.30</td>\n",
       "      <td>United States, Plymouth, Minnesota</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>36</td>\n",
       "      <td>Nutrien</td>\n",
       "      <td>11590</td>\n",
       "      <td>62.00</td>\n",
       "      <td>Canada, Saskatoon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>Arkema</td>\n",
       "      <td>11261</td>\n",
       "      <td>20.70</td>\n",
       "      <td>France, Colombes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>38</td>\n",
       "      <td>Asahi Kasei</td>\n",
       "      <td>10908</td>\n",
       "      <td>20.90</td>\n",
       "      <td>Japan, Tokyo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>39</td>\n",
       "      <td>DSM</td>\n",
       "      <td>10888</td>\n",
       "      <td>13.50</td>\n",
       "      <td>Netherlands, Heerlen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>39</td>\n",
       "      <td>Hanwha Solutions</td>\n",
       "      <td>10888</td>\n",
       "      <td>22.80</td>\n",
       "      <td>South Korea, Seoul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>41</td>\n",
       "      <td>Eastman Chemical</td>\n",
       "      <td>10476</td>\n",
       "      <td>23.60</td>\n",
       "      <td>United States, Kingsport, Tennessee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>42</td>\n",
       "      <td>Johnson Matthey</td>\n",
       "      <td>10412</td>\n",
       "      <td>-2.48</td>\n",
       "      <td>United Kingdom, London</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>43</td>\n",
       "      <td>Air Products</td>\n",
       "      <td>10323</td>\n",
       "      <td>16.60</td>\n",
       "      <td>United States, Allentown, Pennsylvania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>44</td>\n",
       "      <td>Eurochem</td>\n",
       "      <td>14269</td>\n",
       "      <td>22.60</td>\n",
       "      <td>Switzerland, Zug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>45</td>\n",
       "      <td>Borealis</td>\n",
       "      <td>10164</td>\n",
       "      <td>26.00</td>\n",
       "      <td>Austria, Vienna</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>46</td>\n",
       "      <td>PTT Global Chemical</td>\n",
       "      <td>16521</td>\n",
       "      <td>51.70</td>\n",
       "      <td>Thailand, Bangkok</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>47</td>\n",
       "      <td>Sasol</td>\n",
       "      <td>9011</td>\n",
       "      <td>10.80</td>\n",
       "      <td>South Africa, Johannesburg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>48</td>\n",
       "      <td>Tongkun Group</td>\n",
       "      <td>8996</td>\n",
       "      <td>28.50</td>\n",
       "      <td>China, Tongxiang</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>49</td>\n",
       "      <td>Lanxess</td>\n",
       "      <td>8940</td>\n",
       "      <td>23.80</td>\n",
       "      <td>Germany, Cologne</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>50</td>\n",
       "      <td>Hengyi Petrochemical</td>\n",
       "      <td>8858</td>\n",
       "      <td>66.80</td>\n",
       "      <td>China, Hangzhou</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Rank                    Company  Sales in 2021 in USD millions  \\\n",
       "0      1                       BASF                          92982   \n",
       "1      2                    Sinopec                          65848   \n",
       "2      3                        Dow                          54968   \n",
       "3      4                      SABIC                          43230   \n",
       "4      5           Formosa Plastics                          43173   \n",
       "5      6                      Ineos                          39937   \n",
       "6      7                 Petrochina                          39693   \n",
       "7      8  LyondellBasell Industries                          38995   \n",
       "8      9                    LG Chem                          37257   \n",
       "9     10                 ExxonMobil                          36858   \n",
       "10    11  Mitsubishi Chemical Group                          30719   \n",
       "11    12       Hengli Petrochemical                          27961   \n",
       "12    13                      Linde                          27926   \n",
       "13    14                Air Liquide                          27148   \n",
       "14    15                   Syngenta                          24900   \n",
       "15    16        Reliance Industries                          22583   \n",
       "16    17                     Wanhua                          22561   \n",
       "17    18                    Braskem                          19575   \n",
       "18    19          Sumitomo Chemical                          19176   \n",
       "19    20         Shin-Etsu Chemical                          18885   \n",
       "20    21                   Covestro                          18813   \n",
       "21    22           Toray Industries                          17856   \n",
       "22    23          Evonik Industries                          17692   \n",
       "23    24                      Shell                          16993   \n",
       "24    25                     DuPont                          16653   \n",
       "25    26                       Yara                          16617   \n",
       "26    27    Rongsheng Petrochemical                          16001   \n",
       "27    28             Lotte Chemical                          15827   \n",
       "28    29           Mitsui Chemicals                          14681   \n",
       "29    30          Indorama Ventures                          14626   \n",
       "30    31  Chevron Phillips Chemical                          14104   \n",
       "31    32                    Umicore                          13567   \n",
       "32    33                     Solvay                          13527   \n",
       "33    34                      Bayer                          12743   \n",
       "34    35                     Mosaic                          12357   \n",
       "35    36                    Nutrien                          11590   \n",
       "36    37                     Arkema                          11261   \n",
       "37    38                Asahi Kasei                          10908   \n",
       "38    39                        DSM                          10888   \n",
       "39    39           Hanwha Solutions                          10888   \n",
       "40    41           Eastman Chemical                          10476   \n",
       "41    42            Johnson Matthey                          10412   \n",
       "42    43               Air Products                          10323   \n",
       "43    44                   Eurochem                          14269   \n",
       "44    45                   Borealis                          10164   \n",
       "45    46        PTT Global Chemical                          16521   \n",
       "46    47                      Sasol                           9011   \n",
       "47    48              Tongkun Group                           8996   \n",
       "48    49                    Lanxess                           8940   \n",
       "49    50       Hengyi Petrochemical                           8858   \n",
       "\n",
       "    Growth in 2021 in %                            Headquarters  \n",
       "0                 32.90          Germany, Ludwigshafen am Rhein  \n",
       "1                 31.90                          China, Beijing  \n",
       "2                 42.60        United States, Midland, Michigan  \n",
       "3                 50.10                    Saudi Arabia, Riyadh  \n",
       "4                 47.80                          Taiwan, Taipei  \n",
       "5                121.00                  United Kingdom, London  \n",
       "6                 41.70                          China, Beijing  \n",
       "7                 66.60           United States, Houston, Texas  \n",
       "8                 41.80                      South Korea, Seoul  \n",
       "9                 59.60            United States, Spring, Texas  \n",
       "10                24.80                            Japan, Tokyo  \n",
       "11                31.90                           China, Suzhou  \n",
       "12                14.50                         Ireland, Dublin  \n",
       "13                13.40                           France, Paris  \n",
       "14                20.90                      Switzerland, Basel  \n",
       "15                65.60                           India, Mumbai  \n",
       "16                98.20                           China, Yantai  \n",
       "17                80.40                       Brazil, São Paulo  \n",
       "18                24.70                  Japan, Tokyo and Osaka  \n",
       "19                38.60                            Japan, Tokyo  \n",
       "20                48.50                     Germany, Leverkusen  \n",
       "21                20.90                            Japan, Tokyo  \n",
       "22                22.60                          Germany, Essen  \n",
       "23                45.00                  United Kingdom, London  \n",
       "24               -18.40     United States, Wilmington, Delaware  \n",
       "25                43.40                            Norway, Oslo  \n",
       "26                59.60                         China, Hangzhou  \n",
       "27                48.20                      South Korea, Seoul  \n",
       "28                33.10                            Japan, Tokyo  \n",
       "29                41.20                       Thailand, Bangkok  \n",
       "30                67.10     United States, The Woodlands, Texas  \n",
       "31                34.40                       Belgium, Brussels  \n",
       "32                17.70                       Belgium, Brussels  \n",
       "33                 9.70                     Germany, Leverkusen  \n",
       "34                42.30      United States, Plymouth, Minnesota  \n",
       "35                62.00                       Canada, Saskatoon  \n",
       "36                20.70                        France, Colombes  \n",
       "37                20.90                            Japan, Tokyo  \n",
       "38                13.50                    Netherlands, Heerlen  \n",
       "39                22.80                      South Korea, Seoul  \n",
       "40                23.60     United States, Kingsport, Tennessee  \n",
       "41                -2.48                  United Kingdom, London  \n",
       "42                16.60  United States, Allentown, Pennsylvania  \n",
       "43                22.60                        Switzerland, Zug  \n",
       "44                26.00                         Austria, Vienna  \n",
       "45                51.70                       Thailand, Bangkok  \n",
       "46                10.80              South Africa, Johannesburg  \n",
       "47                28.50                        China, Tongxiang  \n",
       "48                23.80                        Germany, Cologne  \n",
       "49                66.80                         China, Hangzhou  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Section 03: Data Exploration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Null values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank                             0\n",
       "Company                          0\n",
       "Sales in 2021 in USD millions    0\n",
       "Growth in 2021 in %              0\n",
       "Headquarters                     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum().sort_values(ascending = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Duplicates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.int64(0)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.duplicated().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1400 with 16 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "outliers = df.drop(columns =[\"Company\", \"Rank\"]).select_dtypes(include = np.number)\n",
    "outliers.plot(subplots=True, layout=(4,4), kind = \"box\", figsize = (12,14), patch_artist = True)\n",
    "plt.subplots_adjust(wspace = 0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* New features: Headquarters column transformation to obtain a Country column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>Rank</th>\n",
       "      <th>Company</th>\n",
       "      <th>Sales in 2021 in USD millions</th>\n",
       "      <th>Growth in 2021 in %</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>BASF</td>\n",
       "      <td>92982</td>\n",
       "      <td>32.90</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Sinopec</td>\n",
       "      <td>65848</td>\n",
       "      <td>31.90</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Dow</td>\n",
       "      <td>54968</td>\n",
       "      <td>42.60</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>SABIC</td>\n",
       "      <td>43230</td>\n",
       "      <td>50.10</td>\n",
       "      <td>Saudi Arabia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Formosa Plastics</td>\n",
       "      <td>43173</td>\n",
       "      <td>47.80</td>\n",
       "      <td>Taiwan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>Ineos</td>\n",
       "      <td>39937</td>\n",
       "      <td>121.00</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>Petrochina</td>\n",
       "      <td>39693</td>\n",
       "      <td>41.70</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>LyondellBasell Industries</td>\n",
       "      <td>38995</td>\n",
       "      <td>66.60</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>LG Chem</td>\n",
       "      <td>37257</td>\n",
       "      <td>41.80</td>\n",
       "      <td>South Korea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>36858</td>\n",
       "      <td>59.60</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>Mitsubishi Chemical Group</td>\n",
       "      <td>30719</td>\n",
       "      <td>24.80</td>\n",
       "      <td>Japan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>Hengli Petrochemical</td>\n",
       "      <td>27961</td>\n",
       "      <td>31.90</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>Linde</td>\n",
       "      <td>27926</td>\n",
       "      <td>14.50</td>\n",
       "      <td>Ireland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>Air Liquide</td>\n",
       "      <td>27148</td>\n",
       "      <td>13.40</td>\n",
       "      <td>France</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>Syngenta</td>\n",
       "      <td>24900</td>\n",
       "      <td>20.90</td>\n",
       "      <td>Switzerland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>Reliance Industries</td>\n",
       "      <td>22583</td>\n",
       "      <td>65.60</td>\n",
       "      <td>India</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>Wanhua</td>\n",
       "      <td>22561</td>\n",
       "      <td>98.20</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>Braskem</td>\n",
       "      <td>19575</td>\n",
       "      <td>80.40</td>\n",
       "      <td>Brazil</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>Sumitomo Chemical</td>\n",
       "      <td>19176</td>\n",
       "      <td>24.70</td>\n",
       "      <td>Japan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>Shin-Etsu Chemical</td>\n",
       "      <td>18885</td>\n",
       "      <td>38.60</td>\n",
       "      <td>Japan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>Covestro</td>\n",
       "      <td>18813</td>\n",
       "      <td>48.50</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>Toray Industries</td>\n",
       "      <td>17856</td>\n",
       "      <td>20.90</td>\n",
       "      <td>Japan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>Evonik Industries</td>\n",
       "      <td>17692</td>\n",
       "      <td>22.60</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>Shell</td>\n",
       "      <td>16993</td>\n",
       "      <td>45.00</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>DuPont</td>\n",
       "      <td>16653</td>\n",
       "      <td>-18.40</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>Yara</td>\n",
       "      <td>16617</td>\n",
       "      <td>43.40</td>\n",
       "      <td>Norway</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>Rongsheng Petrochemical</td>\n",
       "      <td>16001</td>\n",
       "      <td>59.60</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>Lotte Chemical</td>\n",
       "      <td>15827</td>\n",
       "      <td>48.20</td>\n",
       "      <td>South Korea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>Mitsui Chemicals</td>\n",
       "      <td>14681</td>\n",
       "      <td>33.10</td>\n",
       "      <td>Japan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>Indorama Ventures</td>\n",
       "      <td>14626</td>\n",
       "      <td>41.20</td>\n",
       "      <td>Thailand</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>31</td>\n",
       "      <td>Chevron Phillips Chemical</td>\n",
       "      <td>14104</td>\n",
       "      <td>67.10</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>Umicore</td>\n",
       "      <td>13567</td>\n",
       "      <td>34.40</td>\n",
       "      <td>Belgium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>Solvay</td>\n",
       "      <td>13527</td>\n",
       "      <td>17.70</td>\n",
       "      <td>Belgium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>Bayer</td>\n",
       "      <td>12743</td>\n",
       "      <td>9.70</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>35</td>\n",
       "      <td>Mosaic</td>\n",
       "      <td>12357</td>\n",
       "      <td>42.30</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>36</td>\n",
       "      <td>Nutrien</td>\n",
       "      <td>11590</td>\n",
       "      <td>62.00</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>Arkema</td>\n",
       "      <td>11261</td>\n",
       "      <td>20.70</td>\n",
       "      <td>France</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>38</td>\n",
       "      <td>Asahi Kasei</td>\n",
       "      <td>10908</td>\n",
       "      <td>20.90</td>\n",
       "      <td>Japan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>39</td>\n",
       "      <td>DSM</td>\n",
       "      <td>10888</td>\n",
       "      <td>13.50</td>\n",
       "      <td>Netherlands</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>39</td>\n",
       "      <td>Hanwha Solutions</td>\n",
       "      <td>10888</td>\n",
       "      <td>22.80</td>\n",
       "      <td>South Korea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>41</td>\n",
       "      <td>Eastman Chemical</td>\n",
       "      <td>10476</td>\n",
       "      <td>23.60</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>42</td>\n",
       "      <td>Johnson Matthey</td>\n",
       "      <td>10412</td>\n",
       "      <td>-2.48</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>43</td>\n",
       "      <td>Air Products</td>\n",
       "      <td>10323</td>\n",
       "      <td>16.60</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>44</td>\n",
       "      <td>Eurochem</td>\n",
       "      <td>14269</td>\n",
       "      <td>22.60</td>\n",
       "      <td>Switzerland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>45</td>\n",
       "      <td>Borealis</td>\n",
       "      <td>10164</td>\n",
       "      <td>26.00</td>\n",
       "      <td>Austria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>46</td>\n",
       "      <td>PTT Global Chemical</td>\n",
       "      <td>16521</td>\n",
       "      <td>51.70</td>\n",
       "      <td>Thailand</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>47</td>\n",
       "      <td>Sasol</td>\n",
       "      <td>9011</td>\n",
       "      <td>10.80</td>\n",
       "      <td>South Africa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>48</td>\n",
       "      <td>Tongkun Group</td>\n",
       "      <td>8996</td>\n",
       "      <td>28.50</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>49</td>\n",
       "      <td>Lanxess</td>\n",
       "      <td>8940</td>\n",
       "      <td>23.80</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>50</td>\n",
       "      <td>Hengyi Petrochemical</td>\n",
       "      <td>8858</td>\n",
       "      <td>66.80</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Rank                    Company  Sales in 2021 in USD millions  \\\n",
       "0      1                       BASF                          92982   \n",
       "1      2                    Sinopec                          65848   \n",
       "2      3                        Dow                          54968   \n",
       "3      4                      SABIC                          43230   \n",
       "4      5           Formosa Plastics                          43173   \n",
       "5      6                      Ineos                          39937   \n",
       "6      7                 Petrochina                          39693   \n",
       "7      8  LyondellBasell Industries                          38995   \n",
       "8      9                    LG Chem                          37257   \n",
       "9     10                 ExxonMobil                          36858   \n",
       "10    11  Mitsubishi Chemical Group                          30719   \n",
       "11    12       Hengli Petrochemical                          27961   \n",
       "12    13                      Linde                          27926   \n",
       "13    14                Air Liquide                          27148   \n",
       "14    15                   Syngenta                          24900   \n",
       "15    16        Reliance Industries                          22583   \n",
       "16    17                     Wanhua                          22561   \n",
       "17    18                    Braskem                          19575   \n",
       "18    19          Sumitomo Chemical                          19176   \n",
       "19    20         Shin-Etsu Chemical                          18885   \n",
       "20    21                   Covestro                          18813   \n",
       "21    22           Toray Industries                          17856   \n",
       "22    23          Evonik Industries                          17692   \n",
       "23    24                      Shell                          16993   \n",
       "24    25                     DuPont                          16653   \n",
       "25    26                       Yara                          16617   \n",
       "26    27    Rongsheng Petrochemical                          16001   \n",
       "27    28             Lotte Chemical                          15827   \n",
       "28    29           Mitsui Chemicals                          14681   \n",
       "29    30          Indorama Ventures                          14626   \n",
       "30    31  Chevron Phillips Chemical                          14104   \n",
       "31    32                    Umicore                          13567   \n",
       "32    33                     Solvay                          13527   \n",
       "33    34                      Bayer                          12743   \n",
       "34    35                     Mosaic                          12357   \n",
       "35    36                    Nutrien                          11590   \n",
       "36    37                     Arkema                          11261   \n",
       "37    38                Asahi Kasei                          10908   \n",
       "38    39                        DSM                          10888   \n",
       "39    39           Hanwha Solutions                          10888   \n",
       "40    41           Eastman Chemical                          10476   \n",
       "41    42            Johnson Matthey                          10412   \n",
       "42    43               Air Products                          10323   \n",
       "43    44                   Eurochem                          14269   \n",
       "44    45                   Borealis                          10164   \n",
       "45    46        PTT Global Chemical                          16521   \n",
       "46    47                      Sasol                           9011   \n",
       "47    48              Tongkun Group                           8996   \n",
       "48    49                    Lanxess                           8940   \n",
       "49    50       Hengyi Petrochemical                           8858   \n",
       "\n",
       "    Growth in 2021 in %         Country  \n",
       "0                 32.90         Germany  \n",
       "1                 31.90           China  \n",
       "2                 42.60   United States  \n",
       "3                 50.10    Saudi Arabia  \n",
       "4                 47.80          Taiwan  \n",
       "5                121.00  United Kingdom  \n",
       "6                 41.70           China  \n",
       "7                 66.60   United States  \n",
       "8                 41.80     South Korea  \n",
       "9                 59.60   United States  \n",
       "10                24.80           Japan  \n",
       "11                31.90           China  \n",
       "12                14.50         Ireland  \n",
       "13                13.40          France  \n",
       "14                20.90     Switzerland  \n",
       "15                65.60           India  \n",
       "16                98.20           China  \n",
       "17                80.40          Brazil  \n",
       "18                24.70           Japan  \n",
       "19                38.60           Japan  \n",
       "20                48.50         Germany  \n",
       "21                20.90           Japan  \n",
       "22                22.60         Germany  \n",
       "23                45.00  United Kingdom  \n",
       "24               -18.40   United States  \n",
       "25                43.40          Norway  \n",
       "26                59.60           China  \n",
       "27                48.20     South Korea  \n",
       "28                33.10           Japan  \n",
       "29                41.20        Thailand  \n",
       "30                67.10   United States  \n",
       "31                34.40         Belgium  \n",
       "32                17.70         Belgium  \n",
       "33                 9.70         Germany  \n",
       "34                42.30   United States  \n",
       "35                62.00          Canada  \n",
       "36                20.70          France  \n",
       "37                20.90           Japan  \n",
       "38                13.50     Netherlands  \n",
       "39                22.80     South Korea  \n",
       "40                23.60   United States  \n",
       "41                -2.48  United Kingdom  \n",
       "42                16.60   United States  \n",
       "43                22.60     Switzerland  \n",
       "44                26.00         Austria  \n",
       "45                51.70        Thailand  \n",
       "46                10.80    South Africa  \n",
       "47                28.50           China  \n",
       "48                23.80         Germany  \n",
       "49                66.80           China  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "headquarters = df[\"Headquarters\"].str.split(\", \", expand = True)\n",
    "headquarters.columns = [\"Country\", \"City\", \"None\"]\n",
    "df = pd.concat([df, headquarters], axis = 1)\n",
    "df = df.drop(columns = [\"Headquarters\", \"City\", \"None\"])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Section 04: Data Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Sales distribution by company"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Sales distribution by company in 2021')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sales_distribution_graph = plt.figure(figsize=(18, 5))\n",
    "sns.barplot(data = df, x = \"Company\", y = \"Sales in 2021 in USD millions\")\n",
    "plt.grid(color = \"b\", linestyle = \"-\", linewidth = 0.1)\n",
    "plt.xlabel(\"Company\")\n",
    "plt.ylabel(\"Sales in USD millions\")\n",
    "plt.xticks(rotation = 90)\n",
    "plt.yticks(np.arange(0,100000,5000))\n",
    "plt.title(\"Sales distribution by company in 2021\", size = 14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Top 5 best selling chemical companies in 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Top 5 best selling chemical companies in 2021')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_5_best_selling_companies_graph = plt.figure(figsize=(18, 5))\n",
    "sns.barplot(data = df.iloc[0:5], x = \"Company\", y = \"Sales in 2021 in USD millions\")\n",
    "plt.grid(color = \"b\", linestyle = \"-\", linewidth = 0.1)\n",
    "plt.xlabel(\"Company\")\n",
    "plt.ylabel(\"Sales in USD millions\")\n",
    "plt.yticks(np.arange(0,100000,5000))\n",
    "plt.title(\"Top 5 best selling chemical companies in 2021\", size = 14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Growth distribution by company"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>Country</th>\n",
       "      <th>Growth in 2021 in %</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Company</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Ineos</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>121.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wanhua</th>\n",
       "      <td>China</td>\n",
       "      <td>98.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Braskem</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>80.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chevron Phillips Chemical</th>\n",
       "      <td>United States</td>\n",
       "      <td>67.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hengyi Petrochemical</th>\n",
       "      <td>China</td>\n",
       "      <td>66.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LyondellBasell Industries</th>\n",
       "      <td>United States</td>\n",
       "      <td>66.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reliance Industries</th>\n",
       "      <td>India</td>\n",
       "      <td>65.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nutrien</th>\n",
       "      <td>Canada</td>\n",
       "      <td>62.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ExxonMobil</th>\n",
       "      <td>United States</td>\n",
       "      <td>59.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rongsheng Petrochemical</th>\n",
       "      <td>China</td>\n",
       "      <td>59.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTT Global Chemical</th>\n",
       "      <td>Thailand</td>\n",
       "      <td>51.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SABIC</th>\n",
       "      <td>Saudi Arabia</td>\n",
       "      <td>50.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Covestro</th>\n",
       "      <td>Germany</td>\n",
       "      <td>48.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lotte Chemical</th>\n",
       "      <td>South Korea</td>\n",
       "      <td>48.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Formosa Plastics</th>\n",
       "      <td>Taiwan</td>\n",
       "      <td>47.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shell</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>45.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yara</th>\n",
       "      <td>Norway</td>\n",
       "      <td>43.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dow</th>\n",
       "      <td>United States</td>\n",
       "      <td>42.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mosaic</th>\n",
       "      <td>United States</td>\n",
       "      <td>42.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LG Chem</th>\n",
       "      <td>South Korea</td>\n",
       "      <td>41.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Petrochina</th>\n",
       "      <td>China</td>\n",
       "      <td>41.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indorama Ventures</th>\n",
       "      <td>Thailand</td>\n",
       "      <td>41.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shin-Etsu Chemical</th>\n",
       "      <td>Japan</td>\n",
       "      <td>38.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Umicore</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>34.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mitsui Chemicals</th>\n",
       "      <td>Japan</td>\n",
       "      <td>33.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BASF</th>\n",
       "      <td>Germany</td>\n",
       "      <td>32.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hengli Petrochemical</th>\n",
       "      <td>China</td>\n",
       "      <td>31.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sinopec</th>\n",
       "      <td>China</td>\n",
       "      <td>31.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tongkun Group</th>\n",
       "      <td>China</td>\n",
       "      <td>28.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Borealis</th>\n",
       "      <td>Austria</td>\n",
       "      <td>26.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mitsubishi Chemical Group</th>\n",
       "      <td>Japan</td>\n",
       "      <td>24.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sumitomo Chemical</th>\n",
       "      <td>Japan</td>\n",
       "      <td>24.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lanxess</th>\n",
       "      <td>Germany</td>\n",
       "      <td>23.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eastman Chemical</th>\n",
       "      <td>United States</td>\n",
       "      <td>23.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hanwha Solutions</th>\n",
       "      <td>South Korea</td>\n",
       "      <td>22.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Evonik Industries</th>\n",
       "      <td>Germany</td>\n",
       "      <td>22.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eurochem</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>22.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Toray Industries</th>\n",
       "      <td>Japan</td>\n",
       "      <td>20.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Asahi Kasei</th>\n",
       "      <td>Japan</td>\n",
       "      <td>20.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Syngenta</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>20.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arkema</th>\n",
       "      <td>France</td>\n",
       "      <td>20.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Solvay</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>17.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Air Products</th>\n",
       "      <td>United States</td>\n",
       "      <td>16.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Linde</th>\n",
       "      <td>Ireland</td>\n",
       "      <td>14.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DSM</th>\n",
       "      <td>Netherlands</td>\n",
       "      <td>13.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Air Liquide</th>\n",
       "      <td>France</td>\n",
       "      <td>13.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sasol</th>\n",
       "      <td>South Africa</td>\n",
       "      <td>10.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bayer</th>\n",
       "      <td>Germany</td>\n",
       "      <td>9.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Johnson Matthey</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>-2.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DuPont</th>\n",
       "      <td>United States</td>\n",
       "      <td>-18.40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  Country  Growth in 2021 in %\n",
       "Company                                                       \n",
       "Ineos                      United Kingdom               121.00\n",
       "Wanhua                              China                98.20\n",
       "Braskem                            Brazil                80.40\n",
       "Chevron Phillips Chemical   United States                67.10\n",
       "Hengyi Petrochemical                China                66.80\n",
       "LyondellBasell Industries   United States                66.60\n",
       "Reliance Industries                 India                65.60\n",
       "Nutrien                            Canada                62.00\n",
       "ExxonMobil                  United States                59.60\n",
       "Rongsheng Petrochemical             China                59.60\n",
       "PTT Global Chemical              Thailand                51.70\n",
       "SABIC                        Saudi Arabia                50.10\n",
       "Covestro                          Germany                48.50\n",
       "Lotte Chemical                South Korea                48.20\n",
       "Formosa Plastics                   Taiwan                47.80\n",
       "Shell                      United Kingdom                45.00\n",
       "Yara                               Norway                43.40\n",
       "Dow                         United States                42.60\n",
       "Mosaic                      United States                42.30\n",
       "LG Chem                       South Korea                41.80\n",
       "Petrochina                          China                41.70\n",
       "Indorama Ventures                Thailand                41.20\n",
       "Shin-Etsu Chemical                  Japan                38.60\n",
       "Umicore                           Belgium                34.40\n",
       "Mitsui Chemicals                    Japan                33.10\n",
       "BASF                              Germany                32.90\n",
       "Hengli Petrochemical                China                31.90\n",
       "Sinopec                             China                31.90\n",
       "Tongkun Group                       China                28.50\n",
       "Borealis                          Austria                26.00\n",
       "Mitsubishi Chemical Group           Japan                24.80\n",
       "Sumitomo Chemical                   Japan                24.70\n",
       "Lanxess                           Germany                23.80\n",
       "Eastman Chemical            United States                23.60\n",
       "Hanwha Solutions              South Korea                22.80\n",
       "Evonik Industries                 Germany                22.60\n",
       "Eurochem                      Switzerland                22.60\n",
       "Toray Industries                    Japan                20.90\n",
       "Asahi Kasei                         Japan                20.90\n",
       "Syngenta                      Switzerland                20.90\n",
       "Arkema                             France                20.70\n",
       "Solvay                            Belgium                17.70\n",
       "Air Products                United States                16.60\n",
       "Linde                             Ireland                14.50\n",
       "DSM                           Netherlands                13.50\n",
       "Air Liquide                        France                13.40\n",
       "Sasol                        South Africa                10.80\n",
       "Bayer                             Germany                 9.70\n",
       "Johnson Matthey            United Kingdom                -2.48\n",
       "DuPont                      United States               -18.40"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "growth_df = pd.pivot_table(df, values = [\"Growth in 2021 in %\", \"Country\"], index = \"Company\", aggfunc = \"sum\")\n",
    "growth_df = growth_df.reindex(growth_df[\"Growth in 2021 in %\"].sort_values(ascending = False).index)\n",
    "growth_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Growth distribution by company in 2021')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "growth_graph = plt.figure(figsize = (15, 5))\n",
    "sns.barplot(data = growth_df, x = \"Company\", y = \"Growth in 2021 in %\", color = \"orange\")\n",
    "plt.grid(color = \"orange\", linestyle = \"-\", linewidth = 0.1)\n",
    "plt.xlabel(\"Company\")\n",
    "plt.ylabel(\"Growth in %\")\n",
    "plt.xticks(rotation = 90)\n",
    "plt.title(\"Growth distribution by company in 2021\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Top 5 fastest growing chemical companies in 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Top 5 fastest growing chemical companies in 2021')"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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fJNkkze71/SLl1tv03O09EXd3+2eRJP33v/+1mY6Pj1f//v3THK+6ZMmS1r+z4lx4/vnn1b17d02fPl3z5s3T008/nelrvpCQEM2ePVsuLi7y9/dXvnz5rNuRkeM2PZl977nb8ZviTtfU8fHxGjt2rDp06JBquVuTlGm1cbdr9YzGmZevyUms4b5Wq1YtxcbGKl++fAoMDEyzTqVKlbR582b17NnTWrZ582ZVrlzZOl2gQAG1adNGbdq00aBBg1SxYkUdOHBAtWrVyu5NAHKVkJAQRUVF6cKFC3r11Vet5U2aNNHPP/+s7du3a8CAATp8+LDOnTund9991/qf/1ufKJqVihYtqlOnTlmn4+LibP7ruWvXLlksFk2dOtXaU+Gbb77JlliA3MBkMsnJyUnXrl1Lt87mzZvVrl07Pfvss5JuXiD//vvvNp99JpNJjRo1UqNGjTRq1CiVKlVKS5cu1bBhwyRJDz30kL7//nsFBwerc+fO+uabb5Q/f/4MffYi7ylcuLDCwsL00UcfaciQIam+WF68eDHD//SsVauWlixZosDAQOsX3du5urqqQ4cOWrRokY4dO6YKFSrc9bqtUqVKOnnypE6ePGn97Dp06JAuXrxoc27Yq3Tp0tn+pM47uX28wq1btyooKMiaGMiXL59CQ0MVGhqq0aNHy9vbW+vWrUvzi3jXrl3VpUsXLV++PNU4a4ZhKC4uzmactfQ8/PDDSk5O1pkzZ9S4ceN72Lo7q169uv773//q999/T7PXWkbeE3HvatWqpUOHDt3TOGcVKlTQF198oYSEBOtTPXfs2JGqXqtWreTm5qbZs2dr1apV2rBhQ6bXlVayUMrYcevi4pLhp/6mfB+91ebNm1W+fHk5OzurWrVqslgsWr9+vUJDQzO9HdLNfX/kyJF72vd34+HhocDAQEVERKR6gImUt6/JuRUU97XQ0FA1aNBA7du315o1a3T8+HFt2bJFb7zxhvVL/quvvqrw8HDNnj1bR48e1bRp0/T9999bB5gMDw/XZ599pt9++01//vmnvvjiCxUoUEClSpVy5KYBDhESEqJNmzZp7969Nt3RmzZtqrlz5yoxMVEhISEqWbKkXFxc9MEHH+jPP//UihUrNH78+GyJ6bHHHtPChQu1ceNGHThwQD179rT572G5cuWUlJRkjWXhwoWaM2dOtsQCOEJCQoJiY2MVGxur6Ohovfjii9YePekJCgqy9kiLjo5W//79bZ58uG3bNk2YMEE7d+7UX3/9pe+//15nz55VpUqVbNopVqyY1q1bp8OHD+uZZ57RjRs3MvTZi7zpo48+UnJysurVq6clS5bo6NGjio6O1syZM9WgQYMMtzNo0CCdP39ezzzzjHbs2KE//vhDq1ev1nPPPWfzRbZbt2768ccf9fnnn9s8tCA9oaGhqlatmrp166bdu3dr+/bt6tGjh5o2bZrq1q370V9//aVhw4bpyJEj+vLLL/XBBx/opZdeknTzlreZM2dq7969OnHihBYsWCCLxaIKFSqk2Vbnzp319NNP65lnnrG+V5w4cUIrV65UaGiozYMj7qR8+fLq1q2bevTooe+//14xMTHavn27Jk6cqB9//DHLtr1p06Zq0qSJOnbsqLVr1yomJsb68BTp7u+JyBojRozQli1bNHjwYO3du1dHjx7V8uXL7zgY/u26du0qi8Wifv36KTo6WqtXr7Y+AfTWW52dnZ3Vq1cvjRw5UkFBQZl6j7mbjBy3gYGBio+PV0REhP7999873uo4fPhwRUREaPz48fr99981f/58ffjhh9bvo4GBgerZs6d69+6tZcuWKSYmRlFRUZlKSo0aNUoLFizQ2LFjdfDgQUVHR+urr77Sm2++eW874zZjxozR1KlTNXPmTB09elS7d+/WBx98IClvX5OTWMN9zWQy6aefflKTJk303HPPqXz58urSpYtOnDhhvWe8ffv2ev/99zVlyhRVqVJFc+fO1bx58xQcHCzp5m0rn3zyiRo1aqTq1avrl19+0Q8//GDztDUgrwgJCdG1a9dUrlw56zkk3bxgvXz5sipUqCA/Pz8VLfp/7d1/TNX1Hsfx1zdrTkVEmwo6lJ1NkMMBwUDTpoBizB/I2Qh/gCI0bQ1sZTRd40eUa4ktJZridMLZKQVEAxMn5VCPTi1YpHNJWrQS3dQ2paVr/uBw/+jes86lLtwjwWk9H/99v5/Peb8/3zPGOXufz4/Rstlsqqmpkdls1qZNm7ode95XXn/9dcXGxmrRokVauHChrFar2z4sU6ZM0ZYtW1RcXCyLxaI9e/bonXfe+UvGAgyEhoYGBQQEKCAgQNOnT1dzc7Nqampcn2N/JD8/X1OnTlViYqLi4uLk7+8vq9Xqavf19dXJkye1YMECBQcHKz8/X++9957mz5/fLZa/v7+OHTumCxcuKD09XU6ns8fPXvwzmUwmtbS0KD4+Xrm5ubJYLJo3b54aGxtVVlbW6zjjxo3T6dOn1dnZqWeffVbh4eF65ZVX5Ofn57aH2pw5czRq1ChdunRJaWlpPcY1DEMHDx7UyJEjNXv2bCUkJMhkMqm6utqj5/U2GRkZ+vXXXzVt2jTl5OTo5Zdf1gsvvCDpt++7H3/8sebMmaPQ0FDt2LFDlZWVCgsL+8NYhmFo79692rJli+rq6hQbG6uIiAgVFRUpOTlZiYmJvR5XRUWFMjIylJubq5CQEFmtVjU3N7stDewLBw4cUExMjJYvXy6z2az169e7CrE9/U9E34iIiJDD4dDly5c1a9YsRUVFqbCwUOPGjet1DF9fXx06dEjnzp1TZGSk8vLyVFhYKMl9SaMk1xLDrKysPn0Oqee/25kzZ+rFF1/U0qVLNXr0aG3evPlPY02dOlX79u1TVVWVLBaLCgsL9dZbbykzM9PVp6ysTM8995yys7M1efJkrVmzRnfv3u31eBMTE1VfX6/PPvtMMTExevrpp7V169Y+nyyyatUqlZSUaPv27QoLC9OiRYtcJ/z+k7+TG13/706jAAAAAACvERcXp8jISJWUlAz0UIA+t2fPHmVlZennn3922+fr1KlTmjt3rtrb2/lhBwOKPdYAAAAAAIBXsNvtMplMGj9+vM6fP68NGzZoyZIlrqLavXv39NNPP6moqEipqakU1TDgWAoKAAAAAAC8wvXr17VixQqFhoZq3bp1Sk1N1c6dO13tlZWVmjhxojo6Ov7nEkygv7AUFAAAAAAAAPAAM9YAAAAAAAAAD1BYAwAAAAAAADxAYQ0AAAAAAADwAIU1AAAAAAAAwAMU1gAAAAAAAAAPUFgDAAAAAAAAPEBhDQAAwAtdv35dL730kkwmkwYPHqzAwEAlJSWpsbFxoIcGAACAf3t8oAcAAAAAdz/88IOeeeYZ+fn56d1331V4eLgePHigTz/9VDk5Ofrmm28GeogAAAAQM9YAAAC8TnZ2tgzDUFNTk1JSUhQcHKywsDC9+uqr+vzzzyVJV65cUXJysnx8fOTr66slS5boxo0brhhFRUWKjIxUeXm5JkyYIB8fH2VnZ6uzs1ObN2+Wv7+/xowZo7ffftstt2EYKisr0/z58zVkyBCZTCbt37/frc+GDRsUHBysoUOHymQyqaCgQA8ePOiW+8MPP1RQUJBGjBihZcuW6ZdffpEk2e12Pfnkk7p3755bXKvVqpUrV/bpewkAAPBXorAGAADgRW7duqWGhgbl5ORo2LBh3dr9/PzkdDqVnJysW7duyeFw6OjRo/r++++1dOlSt75tbW06cuSIGhoaVFlZqd27d2vhwoW6evWqHA6HiouLlZ+fry+++MLtdQUFBUpJSdH58+eVnp6uZcuWqbW11dU+fPhw2Ww2Xbx4Ue+//7527dqlrVu3dstdV1en+vp61dfXy+FwaNOmTZKk1NRUdXZ26pNPPnH1v3nzpg4fPqznn3/+kd9DAACA/kJhDQAAwIt899136urq0uTJk/+0T2Njoy5cuKC9e/fqqaee0vTp02W32+VwONTc3Ozq53Q6VV5eLrPZrKSkJMXHx+vSpUsqKSlRSEiIsrKyFBISouPHj7vFT01N1erVqxUcHKyNGzcqOjpaH3zwgas9Pz9fM2fOVFBQkJKSkvTaa69p3759bjGcTqdsNpssFotmzZqllStXuvaHGzJkiNLS0lRRUeHq/9FHH2nChAmKi4t7lLcPAACgX7HHGgAAgBfp6urqsU9ra6sCAwMVGBjoumc2m+Xn56fW1lbFxMRIkoKCgjR8+HBXn7Fjx2rQoEF67LHH3O7dvHnTLf6MGTO6XZ87d851XV1drdLSUrW1tenOnTt6+PChfH193V7z37kDAgLc8qxZs0YxMTG6du2axo8fL5vNpszMTBmG0ePzAwAAeAtmrAEAAHiRSZMmyTCMPjmg4IknnnC7NgzjD+85nc5exzx79qzS09O1YMEC1dfX66uvvlJeXp7u37/fY+7f54mKitKUKVNkt9v15Zdf6uuvv1ZmZmavxwEAAOANKKwBAAB4kVGjRikxMVHbtm3T3bt3u7V3dHQoNDRU7e3tam9vd92/ePGiOjo6ZDabH3kM/zkg4ffXoaGhkqQzZ85o4sSJysvLU3R0tCZNmqQff/zRozyrV6+WzWZTRUWFEhIS3GbgAQAA/B1QWAMAAPAy27ZtU2dnp6ZNm6YDBw7o22+/VWtrq0pLSzVjxgwlJCQoPDxc6enpamlpUVNTkzIyMhQbG6vo6OhHzl9TU6Py8nJdvnxZb7zxhpqamrR27VpJv82ou3LliqqqqtTW1qbS0lLV1tZ6lCctLU1Xr17Vrl27OLQAAAD8LVFYAwAA8DImk0ktLS2Kj49Xbm6uLBaL5s2bp8bGRpWVlckwDB08eFAjR47U7NmzlZCQIJPJpOrq6j7J/+abb6qqqkoRERGy2+2qrKx0zYRbvHix1q1bp7Vr1yoyMlJnzpxRQUGBR3lGjBihlJQU+fj4yGq19snYAQAA+pPR1ZsdcgEAAPCPYBiGamtr+63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      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_5_fastest_growing_companies_graph = plt.figure(figsize = (15, 5))\n",
    "sns.barplot(data = growth_df.iloc[0:5], x = \"Company\", y = \"Growth in 2021 in %\", palette = \"light:orange_r\", hue = \"Country\")\n",
    "plt.grid(color = \"orange\", linestyle = \"-\", linewidth = 0.1)\n",
    "plt.xlabel(\"Company\")\n",
    "plt.ylabel(\"Growth in %\")\n",
    "plt.title(\"Top 5 fastest growing chemical companies in 2021\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Distribution of the most successful chemical companies by country"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>Company</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>United States</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>China</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Korea</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United Kingdom</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Switzerland</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Belgium</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thailand</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Austria</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Netherlands</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ireland</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Norway</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Taiwan</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Company\n",
       "Country                \n",
       "United States         8\n",
       "China                 7\n",
       "Japan                 6\n",
       "Germany               5\n",
       "South Korea           3\n",
       "United Kingdom        3\n",
       "Switzerland           2\n",
       "Belgium               2\n",
       "Thailand              2\n",
       "France                2\n",
       "Austria               1\n",
       "Brazil                1\n",
       "Canada                1\n",
       "Netherlands           1\n",
       "Ireland               1\n",
       "India                 1\n",
       "Norway                1\n",
       "South Africa          1\n",
       "Saudi Arabia          1\n",
       "Taiwan                1"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "countries_df = df.groupby(\"Country\")[[\"Company\"]].count().sort_values(by = \"Company\", ascending = False)\n",
    "countries_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Distribution of the most sucessful chemical companies by country')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "companies_worldwide_graph = plt.figure(figsize = (10, 5))\n",
    "sns.barplot(data = countries_df, y = \"Country\", x = \"Company\", color = \"c\")\n",
    "plt.grid(color = \"c\", linestyle = \"-\", linewidth = 0.1)\n",
    "plt.xlabel(\"Number of companies\")\n",
    "plt.ylabel(\"Company\")\n",
    "plt.title(\"Distribution of the most sucessful chemical companies by country\", size = 12)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Analysis of German companies"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Top best selling German chemical companies in 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>Rank</th>\n",
       "      <th>Company</th>\n",
       "      <th>Sales in 2021 in USD millions</th>\n",
       "      <th>Growth in 2021 in %</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>BASF</td>\n",
       "      <td>92982</td>\n",
       "      <td>32.9</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>Covestro</td>\n",
       "      <td>18813</td>\n",
       "      <td>48.5</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>Evonik Industries</td>\n",
       "      <td>17692</td>\n",
       "      <td>22.6</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>Bayer</td>\n",
       "      <td>12743</td>\n",
       "      <td>9.7</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>49</td>\n",
       "      <td>Lanxess</td>\n",
       "      <td>8940</td>\n",
       "      <td>23.8</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Rank            Company  Sales in 2021 in USD millions  \\\n",
       "0      1               BASF                          92982   \n",
       "20    21           Covestro                          18813   \n",
       "22    23  Evonik Industries                          17692   \n",
       "33    34              Bayer                          12743   \n",
       "48    49            Lanxess                           8940   \n",
       "\n",
       "    Growth in 2021 in %  Country  \n",
       "0                  32.9  Germany  \n",
       "20                 48.5  Germany  \n",
       "22                 22.6  Germany  \n",
       "33                  9.7  Germany  \n",
       "48                 23.8  Germany  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "germany = df[df[\"Country\"] == \"Germany\"]\n",
    "germany"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Top best selling German chemical companies in 2021')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "german_companies_by_sale_graph = plt.figure(figsize = (10, 5))\n",
    "sns.barplot(data = germany, x = \"Company\", y = \"Sales in 2021 in USD millions\", color = \"deeppink\")\n",
    "plt.grid(color = \"deeppink\", linestyle = \"-\", linewidth = 0.1)\n",
    "plt.xlabel(\"Company\")\n",
    "plt.ylabel(\"Sales in USD millions\")\n",
    "plt.title(\"Top best selling German chemical companies in 2021\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Top fastest growing German chemical companies in 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "germany_growth_df = germany.sort_values(by = \"Growth in 2021 in %\", ascending = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "german_companies_by_growth_graph = plt.figure(figsize = (10, 5))\n",
    "ax = sns.barplot(data = germany_growth_df, x = \"Company\", y = \"Growth in 2021 in %\", palette = \"RdPu_r\", hue = \"Company\")\n",
    "plt.grid(color = \"deeppink\", linestyle = \"-\", linewidth = 0.1)\n",
    "plt.xlabel(\"Company\")\n",
    "plt.ylabel(\"Growth in %\")\n",
    "plt.title(\"Top fastest growing German chemical companies in 2021\")\n",
    "for i in ax.containers:\n",
    "    ax.bar_label(i,)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusions:\n",
    "\n",
    "### Top 5 best-selling chemical companies in the world in 2021\n",
    "The best performing chemical producing companies in 2021 were:\n",
    "* BASF\n",
    "* Sinopec\n",
    "* Dow\n",
    "* SABIC\n",
    "* Formosa Plastics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>Rank</th>\n",
       "      <th>Company</th>\n",
       "      <th>Sales in 2021 in USD millions</th>\n",
       "      <th>Growth in 2021 in %</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>BASF</td>\n",
       "      <td>92982</td>\n",
       "      <td>32.9</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Sinopec</td>\n",
       "      <td>65848</td>\n",
       "      <td>31.9</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Dow</td>\n",
       "      <td>54968</td>\n",
       "      <td>42.6</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>SABIC</td>\n",
       "      <td>43230</td>\n",
       "      <td>50.1</td>\n",
       "      <td>Saudi Arabia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Formosa Plastics</td>\n",
       "      <td>43173</td>\n",
       "      <td>47.8</td>\n",
       "      <td>Taiwan</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Rank           Company  Sales in 2021 in USD millions  Growth in 2021 in %  \\\n",
       "0     1              BASF                          92982                 32.9   \n",
       "1     2           Sinopec                          65848                 31.9   \n",
       "2     3               Dow                          54968                 42.6   \n",
       "3     4             SABIC                          43230                 50.1   \n",
       "4     5  Formosa Plastics                          43173                 47.8   \n",
       "\n",
       "         Country  \n",
       "0        Germany  \n",
       "1          China  \n",
       "2  United States  \n",
       "3   Saudi Arabia  \n",
       "4         Taiwan  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Top 5 best-selling chemical companies in 2021')"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 1800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_5_best_selling_companies_graph = plt.figure(figsize=(18, 5))\n",
    "sns.barplot(data = df.iloc[0:5], x = \"Company\", y = \"Sales in 2021 in USD millions\")\n",
    "plt.grid(color = \"b\", linestyle = \"-\", linewidth = 0.1)\n",
    "plt.xlabel(\"Company\")\n",
    "plt.ylabel(\"Sales in USD millions\")\n",
    "plt.yticks(np.arange(0,100000,5000))\n",
    "plt.title(\"Top 5 best-selling chemical companies in 2021\", size = 14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Top 5 fastest growing chemical companies in the world in 2021\n",
    "The chemical producing companies that grew the most in the year 2021 were:\n",
    "* Ineos\n",
    "* Wanhua\n",
    "* Braskern\n",
    "* Chevron Phillips Chemical\n",
    "* Hengyi Petrochemical"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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>Country</th>\n",
       "      <th>Growth in 2021 in %</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Company</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Ineos</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>121.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wanhua</th>\n",
       "      <td>China</td>\n",
       "      <td>98.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Braskem</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>80.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chevron Phillips Chemical</th>\n",
       "      <td>United States</td>\n",
       "      <td>67.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hengyi Petrochemical</th>\n",
       "      <td>China</td>\n",
       "      <td>66.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  Country  Growth in 2021 in %\n",
       "Company                                                       \n",
       "Ineos                      United Kingdom                121.0\n",
       "Wanhua                              China                 98.2\n",
       "Braskem                            Brazil                 80.4\n",
       "Chevron Phillips Chemical   United States                 67.1\n",
       "Hengyi Petrochemical                China                 66.8"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "growth_df.iloc[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Top 5 fastest growing chemical companies in 2021')"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_5_fastest_growing_companies_graph = plt.figure(figsize = (15, 5))\n",
    "sns.barplot(data = growth_df.iloc[0:5], x = \"Company\", y = \"Growth in 2021 in %\", palette = \"light:orange_r\", hue = \"Country\")\n",
    "plt.grid(color = \"orange\", linestyle = \"-\", linewidth = 0.1)\n",
    "plt.xlabel(\"Company\")\n",
    "plt.ylabel(\"Growth in %\")\n",
    "plt.title(\"Top 5 fastest growing chemical companies in 2021\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Global distribution of top-performing chemical companies in 2021\n",
    "The United States is the country with the most chemical companies on the list of the world's 50 largest chemical producers, followed by China, Japan and Germany."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Distribution of the most sucessful chemical companies by country')"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2xYMHD6BUKgEAO3bsgEqlQs+ePXH//n3px9raGk5OTjh69KhGx3lzwh1tbW3Uq1cPoihi8ODB0nozMzNUq1ZNLVea5sXMzAxPnz7F4cOH85+EHOjr60NXVxdRUVHZLg8siO3bt6NWrVrZRvUASJfMb9u2DS4uLqhevbparlu2bAkAUq41ef+ZmZnhn3/+yfGSWLlt374d5cqVw6hRo7Jte/t2gV69eqFs2bLSctaVDVmviYcPH+LXX39Fz5498eTJEylHDx48gJeXF+Li4rJdKjh48GC14zRs2DDbay/rNZnX+1SlUmHXrl3o1KmT2v36b5+LQqGAltar/xXLzMzEgwcPpEuvz58/n2v/udHktZPfvx89evSAqamptNywYUMAQL9+/dTmF2jYsCHS09Oz5bRChQpq8ZiYmMDHxwcXLlzAnTt3CpSHgQMHqs058PbvPifbtm2Dqakp2rRpo/aeqVu3LoyMjLK9Z/bu3YuMjIxc+8uNJufbs2dP6OnpYfPmzVK7gwcP4v79++jXr1+e/WvyHsnvZ1F+vOtzoCB9AK8+t//77z+1z4nNmzdDX18f3bp1K3C89OFhcUpE7yU1NVWtEHxbr1690KRJE/j5+cHKygpffPEFtm7dmq9CtWLFivma/MjJyUltWRAEODo6FvljQW7duoUKFSpky0fW5aC3bt1SW1+5cuVsfZQtW/adBc6tW7fg5OQk/c/cu45TWN6ON6swyIo3Li4OoijCyckJlpaWaj+xsbHSpDr5PY6pqSn09PRQrly5bOvfzJWmeRkxYgScnZ3Rrl07VKpUCYMGDdL4Xt+cKBQKzJ49G/v374eVlRWaNWuGOXPmSP8jml/x8fGoWbNmnm3i4uLw119/Zcuzs7MzgP+fwEiT99/48eNhZGSEBg0awMnJCSNHjlS77FdO8fHxqFatmkaTqr3r9Xjjxg2IoohJkyZly1PW7NVvvyZzeu0BgK2tbbb1eb1P7927B6VS+c7fo0qlwoIFC+Dk5ASFQoFy5crB0tISf/zxB1JSUvLcNyeavHby+/cjPzkBkC0vjo6O2b5YyHqdZv1Nzm8e3vW7z0lcXBxSUlJQvnz5bK+H1NRU6bXQvHlzdOvWDcHBwShXrhw6d+6MdevWZbuXOzeanK+ZmRk6deok3dcNvCrEKlasKH3BlBtN3iP5/SzKj4Lk/m1Vq1bNtq5NmzawsbGRCnaVSoWffvoJnTt3zvP/Mejjw3tOiajA/vnnH6SkpMDR0THXNvr6+vjtt99w9OhR7Nu3DwcOHMDPP/+Mli1b4tChQ9DW1n7ncfJzn6im3v6fhyyZmZkaxVQYcjuO+NZEKyXFu+JVqVQQBAH79+/Psa2RkVGBj1OYuSpfvjwuXryIgwcPYv/+/di/fz/WrVsHHx+fHCdP0sSYMWPQqVMn7Nq1CwcPHsSkSZMQGhqKX3/9Nds9VG/LzMzM9/FUKhXc3Nwwf/78HLdnFQ6avP9cXFxw7do17N27FwcOHMD27duxfPlyTJ48GcHBwXnGIQhCjr+DgpxTfmnyegSAwMBAeHl55dj27b9dufWZ0/rCeJ+GhIRg0qRJGDRoEKZPnw5zc3NoaWlhzJgxJeYxKPnJCVCwvOQ3DwU5tkqlQvny5dVGK9+UdT++IAiIiIjAqVOn8L///Q8HDx7EoEGDEBYWhlOnTmn8d+xdfHx8sG3bNpw8eRJubm7Ys2cPRowYke1Lg6KU1+dgbgrj957TZ7q2tjb69OmDVatWYfny5YiOjsZ///33zpFk+viwOCWiAtu4cSMA5Po/flm0tLTQqlUrtGrVCvPnz0dISAgmTpyIo0ePonXr1rl+QBZUXFyc2rIoirhx44ba81jLli2Lx48fZ9v31q1bsLe3l5bzE1uVKlVw5MgRPHnyRO2b3qtXr0rbC0OVKlXwxx9/QKVSqf2PzPse531/D1kTcVStWlUaKZBTfvKiq6uLTp06oVOnTlCpVBgxYgRWrlyJSZMm5TjyoQkHBweMGzcO48aNQ1xcHDw8PBAWFibNZp3Tay49PR1JSUnZ+vnzzz/feaxLly6hVatW74z1Xe8/ADA0NESvXr3Qq1cvpKenw9vbGzNnzkRQUFCej0gpW7ZsjpdSFnRkxsHBAadPn0ZGRsZ7Pwok632so6MjnadcLC0tYWJi8s7fY0REBFq0aIE1a9aorX/8+HG2KwU0oclrp6j+fuQmawT7zdfp9evXAUCaLKyw85ATBwcHHDlyBE2aNNHoC89PPvkEn3zyCWbOnIkff/wRffv2xZYtW975nF9NzhcA2rZtC0tLS2zevBkNGzbEs2fP0L9/f43O413vEU0/i7JGPd/+u/S+V98U9LPEx8cHYWFh+N///of9+/fD0tLynf9/QR8fXtZLRAXy66+/Yvr06ahatSr69u2ba7u3Hy0AAB4eHgAgXSaV9YyznIrFgtiwYYPafbARERFISkpCu3btpHUODg44deqU9EgH4NU9Rm8/8iQ/sbVv3x6ZmZlYunSp2voFCxZAEAS147+P9u3b486dO/j555+ldS9fvsSSJUtgZGQkPfYjvwwNDd/rd+Dt7Q1tbW0EBwdn+xZdFEU8ePCgwH1rQtO8vB2HlpaW9MVFQV6Tz549w4sXL9TWOTg4wNjYWO1SQAcHB/z2229q7X744YdsoxTdunXDpUuXsHPnzmzHysprz5498e+//2LVqlXZ2jx//hxPnz4FoNn77+186OrqwtXVFaIovvOeOwcHB1y9ehX37t2T1l26dKnAlwV369YN9+/fz/YeAvI/Ile+fHl4enpi5cqV2b4AAKAWc2HT0tJCly5d8L///Q9nz57Ntj3rXLS1tbOd17Zt2wr82AxNXjtF9fcjN//9959aPEqlEhs2bICHhwesra0BFH4ectKzZ09kZmZi+vTp2ba9fPlSeq8/evQoWyxvv2fyosn5Aq+eCd67d29s3boV4eHhcHNzU/sCNTeavEc0/SwyMTFBuXLlsv1dWr58+TvjyEtBP0vc3d3h7u6O1atXY/v27fjiiy+K/LnpVPLwN05E77R//35cvXoVL1++xN27d/Hrr7/i8OHDqFKlCvbs2ZPnyMq0adPw22+/oUOHDqhSpQqSk5OxfPlyVKpUCZ9++imAV/+Da2ZmhhUrVsDY2BiGhoZo2LBhjvelaMLc3ByffvopBg4ciLt372LhwoVwdHRUe9yNn58fIiIi0LZtW/Ts2RPx8fHYtGlTtinv8xNbp06d0KJFC0ycOBEJCQmoVasWDh06hN27d2PMmDHZ+i6ooUOHYuXKlfD19cW5c+dgZ2eHiIgIREdHY+HChQW+P6du3bo4cuQI5s+fjwoVKqBq1arS5CeacHBwwIwZMxAUFISEhAR06dIFxsbGuHnzJnbu3ImhQ4ciMDCwQLFpQtO8+Pn54eHDh2jZsiUqVaqEW7duYcmSJfDw8JDuyfLw8IC2tjZmz56NlJQUKBQKtGzZEuXLl8923OvXr6NVq1bo2bMnXF1dUaZMGezcuRN3797FF198IbXz8/PDl19+iW7duqFNmza4dOkSDh48mG1k6Ouvv0ZERAR69OiBQYMGoW7dunj48CH27NmDFStWoFatWujfvz+2bt2KL7/8EkePHkWTJk2QmZmJq1evYuvWrTh48CDq1aun0fvvs88+g7W1NZo0aQIrKyvExsZi6dKl6NChwztfS4MGDcL8+fPh5eWFwYMHIzk5GStWrECNGjXyNUFKFh8fH2zYsAEBAQE4c+YMmjZtiqdPn+LIkSMYMWJEno/YyMmyZcvw6aefws3NDUOGDIG9vT3u3r2L33//Hf/88897PU/0XUJCQnDo0CE0b95cetxPUlIStm3bhhMnTsDMzAwdO3bEtGnTMHDgQDRu3BiXL1/G5s2b1a7eyA9NXjtF9fcjN87Ozhg8eDBiYmJgZWWFtWvX4u7du1i3bp3UprDzkJPmzZtj2LBhCA0NxcWLF/HZZ59BR0cHcXFx2LZtGxYtWoTu3btj/fr1WL58Obp27QoHBwc8efIEq1atgomJCdq3b18o55vFx8cHixcvxtGjR9UeyZUXTd4j+fks8vPzw6xZs+Dn54d69erht99+k0Z6C+p9Pkt8fHykzwle0ltKyTElMBF9mLIer5D1o6urK1pbW4tt2rQRFy1apPbIkixvP0omMjJS7Ny5s1ihQgVRV1dXrFChgti7d2/x+vXravvt3r1bdHV1FcuUKaM2dXzz5s1zfcxFbo+S+emnn8SgoCCxfPnyor6+vtihQwfx1q1b2fYPCwsTK1asKCoUCrFJkybi2bNnc3w0Rm6x5fS4jCdPnohjx44VK1SoIOro6IhOTk7i3Llz1R5PIYqvpukfOXJktphye8TN2+7evSsOHDhQLFeunKirqyu6ubnlON1+fh4lc/XqVbFZs2aivr6+CECKI+t3+vbjSLJeHzdv3lRbv337dvHTTz8VDQ0NRUNDQ7F69eriyJEjxWvXruV5/NyOM2DAANHQ0DBb+5xeG5rkJSIiQvzss8/E8uXLi7q6umLlypXFYcOGiUlJSWrtVq1aJdrb24va2tp5Plbm/v374siRI8Xq1auLhoaGoqmpqdiwYUNx69atau0yMzPF8ePHi+XKlRMNDAxELy8v8caNGzn+zh88eCD6+/uLFStWFHV1dcVKlSqJAwYMEO/fvy+1SU9PF2fPni3WqFFDVCgUYtmyZcW6deuKwcHBYkpKiiiKmr3/Vq5cKTZr1ky0sLAQFQqF6ODgIH799ddSH6KY+6NkRFEUN23aJNrb24u6urqih4eHePDgwQI/SkYURfHZs2fixIkTxapVq4o6OjqitbW12L17dzE+Pl4Uxf9//EVOj+7J6Rjx8fGij4+PaG1tLero6IgVK1YUO3bsKEZEREhtcntsVn5ekzkd+9atW6KPj49oaWkpKhQK0d7eXhw5cqT0GJQXL16I48aNE21sbER9fX2xSZMm4u+//57t75Cmj5IRRc1eO5q8T3LLc26vhZxymPX35+DBg6K7u7uoUCjE6tWrZ9tX0zzkduyc8pPTa1AURfGHH34Q69atK+rr64vGxsaim5ub+M0334j//fefKIqvHl/Su3dvsXLlyqJCoRDLly8vduzYUTx79myuOc/v+b6pRo0aopaWlvjPP/+8s/8s73qPiKLmn0XPnj0TBw8eLJqamorGxsZiz549xeTk5FwfJaPJ50B+P0velJSUJGpra4vOzs4a54M+LoIoltCZN4iIiIjog2VnZ4eaNWti7969xR1KiVW7dm2Ym5sjMjKyuEMpEe7fvw8bGxtMnjwZkyZNKu5wqBjwnlMiIiIiIpmdPXsWFy9ehI+PT3GHUmKEh4cjMzNTo8mh6OPEe06JiIiIiGTy559/4ty5cwgLC4ONjQ169epV3CEVu19//RVXrlzBzJkz0aVLF7WZjal04cgpEREREZFMIiIiMHDgQGRkZOCnn37Kc1LB0mLatGkICAiAh4cHlixZUtzhUDHiPadERERERERU7DhySkRERERERMWOxSkREREREREVO06IREVCpVLhv//+g7GxMQRBKO5wiIiIiIiomIiiiCdPnqBChQrQ0sp9fJTFKRWJ//77D7a2tsUdBhERERERlRC3b99GpUqVct3O4pSKhLGxMYBXL0ATE5Nijubj9zAjAwBgrqNTzJGUDsy3vJhv+THn8mK+5cV8y4v5ll9JzLlSqYStra1UI+SGxSkViaxLeeseOgQtA4Nijubjp3qdby1Ovi0L5ltezLf8mHN5Md/yYr7lxXzLTyUIiPX2hkkJKk6zvOt2P06IRERERERERMWOxekb7OzssHDhwiLpWxAE7Nq1q0j6JiIiIiIi+tB98MWpp6cnxowZk219eHg4zMzM8tVXTEwMhg4dKi3LWVDeu3cPw4cPR+XKlaFQKGBtbQ0vLy9ER0e/dzxFWXQTEREREREVBt5z+gZLS8tiO3a3bt2Qnp6O9evXw97eHnfv3kVkZCQePHhQbDERERERERHJ5YMfOdWUr68vunTpgnnz5sHGxgYWFhYYOXIkMl7PZgWojzDa2dkBALp27QpBEKRlANi9ezfq1KkDPT092NvbIzg4GC9fvpS2x8XFoVmzZtDT04OrqysOHz6cZ2yPHz/G8ePHMXv2bLRo0QJVqlRBgwYNEBQUhM8//zzPeOLj49G5c2dYWVnByMgI9evXx5EjR6S+PT09cevWLYwdOxaCIKjdhHzixAk0bdoU+vr6sLW1xejRo/H06VNp+/Lly+Hk5AQ9PT1YWVmhe/fuGuebiIiIiIgoP0rVyOnRo0dhY2ODo0eP4saNG+jVqxc8PDwwZMiQbG1jYmJQvnx5rFu3Dm3btoW2tjYA4Pjx4/Dx8cHixYvRtGlTxMfHS5cCT5kyBSqVCt7e3rCyssLp06eRkpKS42XHbzIyMoKRkRF27dqFTz75BAqFQuN4UlNT0b59e8ycORMKhQIbNmxAp06dcO3aNVSuXBk7duxArVq1MHToULXzjI+PR9u2bTFjxgysXbsW9+7dg7+/P/z9/bFu3TqcPXsWo0ePxsaNG9G4cWM8fPgQx48fz/Uc0tLSkJaWJi0rlUoAr2doe8esXPT+VMyxrJhveTHf8mPO5cV8y4v5lhfzLT+VIODRGwNwJYFSw3hKzcgpAJQtWxZLly5F9erV0bFjR3To0AGRkZE5ts26xNfMzAzW1tbScnBwMCZMmIABAwbA3t4ebdq0wfTp07Fy5UoAwJEjR3D16lVs2LABtWrVQrNmzRASEpJnXGXKlEF4eDjWr18PMzMzNGnSBN9++y3++OOPd8ZTq1YtDBs2DDVr1oSTkxOmT58OBwcH7NmzBwBgbm4ObW1tGBsbw9raGtbW1gCA0NBQ9O3bF2PGjIGTkxMaN26MxYsXY8OGDXjx4gUSExNhaGiIjh07okqVKqhduzZGjx6d6zmEhobC1NRU+rG1tX3n74OIiIiIiChLqRo5rVGjhjTiCAA2Nja4fPlyvvq4dOkSoqOjMXPmTGldZmYmXrx4gWfPniE2Nha2traoUKGCtL1Ro0bv7Ldbt27o0KEDjh8/jlOnTmH//v2YM2cOVq9eDV9f31z3S01NxdSpU7Fv3z4kJSXh5cuXeP78ORITE995Hn/88Qc2b94srRNFESqVCjdv3kSbNm1QpUoV2Nvbo23btmjbti26du0Kg1yeWRoUFISAgABpOetBu1qiyOdayYi5lhfzLS/mW37MubyYb3kx3/JivuVVVkcH5iXoOadlNIzlgy9OTUxMkJKSkm3948ePYWpqqrZO562kCIIAlUqVr+OlpqYiODgY3t7e2bbp6enlq6+c9m/Tpg3atGmDSZMmwc/PD1OmTMmzOA0MDMThw4cxb948ODo6Ql9fH927d0d6evo7z2PYsGE5joZWrlwZurq6OH/+PKKionDo0CFMnjwZU6dORUxMTI6zICsUihwvRyYiIiIiItLEB1+cVqtWDYcOHcq2/vz583B2dn6vvnV0dJCZmam2rk6dOrh27RocHR1z3MfFxQW3b99GUlISbGxsAACnTp0q0PFdXV3VHh2TUzzR0dHw9fVF165dAbwqOhMSEtTa6Orq5ngeV65cyfU8gFeXG7du3RqtW7fGlClTYGZmhl9//TXHwpyIiIiIiOh9fPD3nA4fPhzXr1/H6NGj8ccff+DatWuYP38+fvrpJ4wbN+69+razs0NkZCTu3LmDR48eAQAmT56MDRs2IDg4GH/99RdiY2OxZcsWfPfddwCA1q1bw9nZGQMGDMClS5dw/PhxTJw4Mc/jPHjwAC1btsSmTZvwxx9/4ObNm9i2bRvmzJmDzp075xmPk5MTduzYgYsXL+LSpUvo06dPttFgOzs7/Pbbb/j3339x//59AMD48eNx8uRJ+Pv74+LFi4iLi8Pu3bvh7+8PANi7dy8WL16Mixcv4tatW9iwYQNUKhWqVav2XjklIiIiIiLKyQdfnNrb2+O3337D1atX0bp1azRs2BBbt27Ftm3b0LZt2/fqOywsDIcPH4atrS1q164NAPDy8sLevXtx6NAh1K9fH5988gkWLFiAKlWqAAC0tLSwc+dOPH/+HA0aNICfn5/a/ak5MTIyQsOGDbFgwQI0a9YMNWvWxKRJkzBkyBAsXbo0z3jmz5+PsmXLonHjxujUqRO8vLxQp04dtf6nTZuGhIQEODg4SBMpubu749ixY7h+/TqaNm2K2rVrY/LkydK9smZmZtixYwdatmwJFxcXrFixAj/99BNq1KjxXjklIiIiIiLKiSCKvDuZCp9SqYSpqSnKr1kDrVwmUaLCkzVNOycbkAfzLS/mW37MubyYb3kx3/JivuWnEgTEenuXqAmRsmqDlJQUmJiY5Nrugx85JSIiIiIiog/fBz8hEpVscd275/ntCBWOh68fbFySviH7mDHf8mK+5cecy4v5lhfzLS/mW35ZOf8QceSUiIiIiIiIih2LUyIiIiIiIip2LE6JiIiIiIio2PGeUypSThERnK1XBpwJT17Mt7yYb/kx5/JivuXFfMsra+ZYIk1w5JSIiIiIiIiKHYtTIiIiIiIiKnYsTj9wgiBg165duW6PioqCIAh4/PixbDERERERERHlF4vTEu7OnTsYNWoU7O3toVAoYGtri06dOiEyMlKj/Rs3boykpCSYmpoWcaREREREREQFxwmRSrCEhAQ0adIEZmZmmDt3Ltzc3JCRkYGDBw9i5MiRuHr16jv70NXVhbW1tQzREhERERERFRxHTkuwESNGQBAEnDlzBt26dYOzszNq1KiBgIAAnDp1Smp3//59dO3aFQYGBnBycsKePXukbW9f1hseHg4zMzMcPHgQLi4uMDIyQtu2bZGUlCTtExMTgzZt2qBcuXIwNTVF8+bNcf78ednOm4iIiIiISh+OnJZQDx8+xIEDBzBz5kwYGhpm225mZib9Ozg4GHPmzMHcuXOxZMkS9O3bF7du3YK5uXmOfT979gzz5s3Dxo0boaWlhX79+iEwMBCbN28GADx58gQDBgzAkiVLIIoiwsLC0L59e8TFxcHY2DjHPtPS0pCWliYtK5VKAK+na389ZTsVHRVzLCvmW17Mt/yYc3kx3/JivuWlEgQ8ysgo7jBKlZKYb6WGMXHktIS6ceMGRFFE9erV39nW19cXvXv3hqOjI0JCQpCamoozZ87k2j4jIwMrVqxAvXr1UKdOHfj7+6vdw9qyZUv069cP1atXh4uLC3744Qc8e/YMx44dy7XP0NBQmJqaSj+2trb5O2EiIiIiIirVOHJaQon5eDC0u7u79G9DQ0OYmJggOTk51/YGBgZwcHCQlm1sbNTa3717F9999x2ioqKQnJyMzMxMPHv2DImJibn2GRQUhICAAGlZqVTC1tYWWqLIh1zLiLmWF/MtL+Zbfsy5vJhveTHf8imrowNzHZ3iDqPUKUk5L6NhLCxOSygnJycIgqDRpEc6b/2yBUGASqXKV/s3i+EBAwbgwYMHWLRoEapUqQKFQoFGjRohPT091z4VCgUUCsU7YyUiIiIiIsoJL+stoczNzeHl5YVly5bh6dOn2bYX5XNLo6OjMXr0aLRv3x41atSAQqHA/fv3i+x4RERERERELE5LsGXLliEzMxMNGjTA9u3bERcXh9jYWCxevBiNGjUqsuM6OTlh48aNiI2NxenTp9G3b1/o6+sX2fGIiIiIiIhYnJZg9vb2OH/+PFq0aIFx48ahZs2aaNOmDSIjI/H9998X2XHXrFmDR48eoU6dOujfvz9Gjx6N8uXLF9nxiIiIiIiIBDE/M+8QaUipVMLU1BTl16yBloFBcYfz0cuaFp+TO8iD+ZYX8y0/5lxezLe8mG95qQQBsd7eJWpyno/dw9ePbSlJOc+qDVJSUmBiYpJrO06IREUqrnv3PF+AVDhK4h+hjxnzLS/mW37MubyYb3kx3/J6WAKfuUklFy/rJSIiIiIiomLH4pSIiIiIiIiKHYtTIiIiIiIiKna855SKlFNEBCdEkgEnd5AX8y0v5lt+zLm8mG95ZU3QQ0QlD0dOiYiIiIiIqNixOCUiIiIiIqJix+KUiIiIiIiIih2L0xLM19cXXbp0Ke4wiIiIiIiIihyLUyIiIiIiIip2LE4/EAcOHMCnn34KMzMzWFhYoGPHjoiPj5e2JyQkQBAEbNmyBY0bN4aenh5q1qyJY8eOSW0yMzMxePBgVK1aFfr6+qhWrRoWLVqkdpys0dp58+bBxsYGFhYWGDlyJDIyMmQ7VyIiIiIiKn34KJkPxNOnTxEQEAB3d3ekpqZi8uTJ6Nq1Ky5evAgtrf//juHrr7/GwoUL4erqivnz56NTp064efMmLCwsoFKpUKlSJWzbtg0WFhY4efIkhg4dChsbG/Ts2VPq4+jRo7CxscHRo0dx48YN9OrVCx4eHhgyZEiu8aWlpSEtLU1aViqVAF5Pj/96inwqOirmWFbMt7yYb/kx5/JivuWlEgQ84pfusmGu5VcSc67UMCYWpx+Ibt26qS2vXbsWlpaWuHLlCmrWrCmt9/f3l9p+//33OHDgANasWYNvvvkGOjo6CA4OltpWrVoVv//+O7Zu3apWnJYtWxZLly6FtrY2qlevjg4dOiAyMjLP4jQ0NFStbyIiIiIiovxgcfqBiIuLw+TJk3H69Gncv38fKpUKAJCYmKhWnDZq1Ej6d5kyZVCvXj3ExsZK65YtW4a1a9ciMTERz58/R3p6Ojw8PNSOVaNGDWhra0vLNjY2uHz5cp7xBQUFISAgQFpWKpWwtbWFlijyoeIyYq7lxXzLi/mWH3MuL+ZbPmV1dGCuo1PcYZQqzLf8SlLOy2gYC4vTD0SnTp1QpUoVrFq1ChUqVIBKpULNmjWRnp6ucR9btmxBYGAgwsLC0KhRIxgbG2Pu3Lk4ffq0Wjudt148giBIxXBuFAoFFAqF5idERERERET0Bk6I9AF48OABrl27hu+++w6tWrWCi4sLHj16lGPbU6dOSf9++fIlzp07BxcXFwBAdHQ0GjdujBEjRqB27dpwdHRUm1SJiIiIiIiouHDk9ANQtmxZWFhY4IcffoCNjQ0SExMxYcKEHNsuW7YMTk5OcHFxwYIFC/Do0SMMGjQIAODk5IQNGzbg4MGDqFq1KjZu3IiYmBhUrVpVztMhIiIiIiLKhiOnJZhKpUKZMmWgpaWFLVu24Ny5c6hZsybGjh2LuXPn5rjPrFmzMGvWLNSqVQsnTpzAnj17UK5cOQDAsGHD4O3tjV69eqFhw4Z48OABRowYIecpERERERER5UgQRd59X1K1bdsWjo6OWLp06TvbJiQkoGrVqrhw4UK2CY6Kg1KphKmpKcqvWQMtA4PiDuejl/UYAk6mIQ/mW17Mt/yYc3kx3/JSCQJivb1L1GQxH7OHrx8hwnzLpyTmPKs2SElJgYmJSa7tOHJaAj169Ah79+5FVFQUWrduXdzhEBERERERFTnec1oCDRo0CDExMRg3bhw6d+5c3OG8l7ju3fP8doQKR0n8huxjxnzLi/mWH3MuL+ZbXln5JqKSh8VpCbRz585872NnZwdeoU1ERERERB8qXtZLRERERERExY4jp1SknCIiOCGSDDiZhryYb3kx3/JjzuWVNUEPEVFpx5FTIiIiIiIiKnYsTomIiIiIiKjYsTglIiIiIiKiYsfi9D3duXMHX331FRwdHaGnpwcrKys0adIE33//PZ49e1bc4REREREREX0QOCHSe/j777/RpEkTmJmZISQkBG5ublAoFLh8+TJ++OEHVKxYEZ9//nm++01PT4eurm4RRExERERERFQyceT0PYwYMQJlypTB2bNn0bNnT7i4uMDe3h6dO3fGvn370KlTJwDA48eP4efnB0tLS5iYmKBly5a4dOmS1M/UqVPh4eGB1atXo2rVqtDT0wMACIKAlStXomPHjjAwMICLiwt+//133LhxA56enjA0NETjxo0RHx8v9RUfH4/OnTvDysoKRkZGqF+/Po4cOaIWt52dHUJCQjBo0CAYGxujcuXK+OGHH6TtLVu2hL+/v9o+9+7dg66uLiIjIws9j0RERERERBw5LaAHDx7g0KFDCAkJgaGhYY5thNdT8ffo0QP6+vrYv38/TE1NsXLlSrRq1QrXr1+Hubk5AODGjRvYvn07duzYAW1tbamP6dOnY/78+Zg/fz7Gjx+PPn36wN7eHkFBQahcuTIGDRoEf39/7N+/HwCQmpqK9u3bY+bMmVAoFNiwYQM6deqEa9euoXLlylK/YWFhmD59Or799ltERERg+PDhaN68OapVqwY/Pz/4+/sjLCwMCoUCALBp0yZUrFgRLVu2zPFc09LSkJaWJi0rlUoArx9H8DoPVHRUzLGsmG95Md/yY87lpRIEPMrIKO4wSg3mWl7Mt/xKYs6VGsbEkdMCunHjBkRRRLVq1dTWlytXDkZGRjAyMsL48eNx4sQJnDlzBtu2bUO9evXg5OSEefPmwczMDBEREdJ+6enp2LBhA2rXrg13d3dp/cCBA9GzZ084Oztj/PjxSEhIQN++feHl5QUXFxd89dVXiIqKktrXqlULw4YNQ82aNeHk5ITp06fDwcEBe/bsUYuzffv2GDFiBBwdHTF+/HiUK1cOR48eBQB4v37W2u7du6X24eHh8PX1lQrut4WGhsLU1FT6sbW1LVhiiYiIiIioVOLIaSE7c+YMVCoV+vbti7S0NFy6dAmpqamwsLBQa/f8+XO1y3GrVKkCS0vLbP29WahaWVkBANzc3NTWvXjxAkqlEiYmJkhNTcXUqVOxb98+JCUl4eXLl3j+/DkSExNz7VcQBFhbWyM5ORkAoKenh/79+2Pt2rXo2bMnzp8/jz///DNbgfumoKAgBAQESMtKpRK2trbQEkU+xF1GzLW8mG95Md/yY87lU1ZHB+Y6OsUdRqnCfMuL+ZZfScp5GQ1jYXFaQI6OjhAEAdeuXVNbb29vDwDQ19cH8OoyWxsbG7XRzSxmZmbSv3O7NFjnjV9k1qhlTutUKhUAIDAwEIcPH8a8efPg6OgIfX19dO/eHenp6bn2m9VPVh8A4OfnBw8PD/zzzz9Yt24dWrZsiSpVquQYIwAoFArpEmAiIiIiIqL8YnFaQBYWFmjTpg2WLl2KUaNG5Vpc1qlTB3fu3EGZMmVgZ2dX5HFFR0fD19cXXbt2BfCqOE5ISMh3P25ubqhXrx5WrVqFH3/8EUuXLi3kSImIiIiIiP4f7zl9D8uXL8fLly9Rr149/Pzzz4iNjcW1a9ewadMmXL16Fdra2mjdujUaNWqELl264NChQ0hISMDJkycxceJEnD17ttBjcnJywo4dO3Dx4kVcunQJffr0URsRzQ8/Pz/MmjULoihKxS4REREREVFRYHH6HhwcHHDhwgW0bt0aQUFBqFWrFurVq4clS5YgMDAQ06dPhyAI+OWXX9CsWTMMHDgQzs7O+OKLL3Dr1i3pHtLCNH/+fJQtWxaNGzdGp06d4OXlhTp16hSor969e6NMmTLo3bu39HgbIiIiIiKioiCIImc7oJwlJCTAwcEBMTEx+S5wlUolTE1NUX7NGmgZGBRRhJQl67EPnLxEHsy3vJhv+THn8lIJAmK9vUvU5CUfs4evH2nBfMuD+ZZfScx5Vm2QkpICExOTXNvxnlPKJiMjAw8ePMB3332HTz75pMAjr0RERERERJpicUrZREdHo0WLFnB2dlZ7FmtBxHXvnue3I1Q4SuI3ZB8z5ltezLf8mHN5PdTw4fRERB87FqeUjaenJ3i1NxERERERyYkTIhEREREREVGxY3FKRERERERExY6X9VKRcoqI4Gy9MuDMmvJivuWVNZMpERERfdw4ckpERERERETFjsWpDKKioiAIAh4/flzcoRAREREREZVIpaY4vXfvHoYPH47KlStDoVDA2toaXl5eiI6OLtTjeHp6YsyYMYXSlyAI2LVrl7SckZGB3r17o2LFivjzzz8L5RhEREREREQlQam557Rbt25IT0/H+vXrYW9vj7t37yIyMhIPHjwo7tA08uzZM3Tr1g1xcXE4ceIEqlatmu8+MjMzIQgCtLRKzXcSRERERET0gSgVVcrjx49x/PhxzJ49Gy1atECVKlXQoEEDBAUF4fPPP5faJSYmonPnzjAyMoKJiQl69uyJu3fvStt9fX3RpUsXtb7HjBkDT09PafuxY8ewaNEiCIIAQRCQkJAgtT137hzq1asHAwMDNG7cGNeuXdM4/jZt2uC///5TK0wfPXoEHx8flC1bFgYGBmjXrh3i4uKk/cLDw2FmZoY9e/bA1dUVCoUCiYmJSEtLQ2BgICpWrAhDQ0M0bNgQUVFR0n4PHjyQRmgNDAzg5uaGn376ScNsExERERER5V+pGDk1MjKCkZERdu3ahU8++QQKhSJbG5VKJRWmx44dw8uXLzFy5Ej06tVLrXDLy6JFi3D9+nXUrFkT06ZNAwBYWlpKBerEiRMRFhYGS0tLfPnllxg0aNA7Lyu+c+cOmjdvLsVlZmYmbfP19UVcXBz27NkDExMTjB8/Hu3bt8eVK1ego6MD4NWI6+zZs7F69WpYWFigfPny8Pf3x5UrV7BlyxZUqFABO3fuRNu2bXH58mU4OTnhxYsXqFu3LsaPHw8TExPs27cP/fv3h4ODAxo0aJBjnGlpaUhLS5OWlUrlq7wKAvB6ZlMqOirmWFbMt7xUgoBHGRnFHUapwnzLi/mWF/MtL+ZbfiUx50oNYyoVxWmZMmUQHh6OIUOGYMWKFahTpw6aN2+OL774Au7u7gCAyMhIXL58GTdv3oStrS0AYMOGDahRowZiYmJQv379dx7H1NQUurq6MDAwgLW1dbbtM2fORPPmzQEAEyZMQIcOHfDixQvo6enl2udXX30Fe3t7HD58GAZvPJIlqyiNjo5G48aNAQCbN2+Gra0tdu3ahR49egB4dZ/q8uXLUatWLQCvRofXrVuHxMREVKhQAQAQGBiIAwcOYN26dQgJCUHFihURGBgoHWvUqFE4ePAgtm7dmmtxGhoaiuDg4HfmiIiIiIiIKCelojgFXt1z2qFDBxw/fhynTp3C/v37MWfOHKxevRq+vr6IjY2Fra2tVJgCgKurK8zMzBAbG6tRcfouWYUwANjY2AAAkpOTUbly5Vz36dixI3bt2oWVK1di7Nix0vrY2FiUKVMGDRs2lNZZWFigWrVqiI2Nldbp6uqqHffy5cvIzMyEs7Oz2nHS0tJgYWEB4NW9qSEhIdi6dSv+/fdfpKenIy0tTa04fltQUBACAgKkZaVSCVtbW2iJIp8FKSPmWl7Mt3zK6ujA/PUVISQf5lxezLe8mG95Md/yK0k5L6NhLKWmOAUAPT09tGnTBm3atMGkSZPg5+eHKVOmwNfXV6P9tbS0IL71P6MZ+Rg213njlyK8vixQpVLluU///v3x+eefY9CgQRBFUa0A1IS+vr50LABITU2FtrY2zp07B21tbbW2RkZGAIC5c+di0aJFWLhwIdzc3GBoaIgxY8YgPT091+MoFIocL5cmIiIiIiLSRKkqTt/m6uoqParFxcUFt2/fxu3bt6XR0ytXruDx48dwdXUF8Or+0bcf4XLx4kW1olNXVxeZmZmFGueAAQOgpaWFgQMHQqVSITAwEC4uLnj58iVOnz4tXdb74MEDXLt2TYo3J7Vr10ZmZiaSk5PRtGnTHNtER0ejc+fO6NevH4BXBfT169fz7JeIiIiIiOh9lIrZeh88eICWLVti06ZN+OOPP3Dz5k1s27YNc+bMQefOnQEArVu3hpubG/r27Yvz58/jzJkz8PHxQfPmzVGvXj0AQMuWLXH27Fls2LABcXFxmDJlSrZi1c7ODqdPn0ZCQgLu37//zpFRTfXv3x/r16/HhAkTMHfuXDg5OaFz584YMmQITpw4gUuXLqFfv36oWLGidE45cXZ2Rt++feHj44MdO3bg5s2bOHPmDEJDQ7Fv3z4AgJOTEw4fPoyTJ08iNjYWw4YNU5u1mIiIiIiIqLCVipFTIyMjNGzYEAsWLEB8fDwyMjJga2uLIUOG4NtvvwXw6jLb3bt3Y9SoUWjWrBm0tLTQtm1bLFmyROrHy8sLkyZNwjfffIMXL15g0KBB8PHxweXLl6U2gYGBGDBgAFxdXfH8+XPcvHmz0M6jb9++0NLSQv/+/aFSqbBu3Tp89dVX6NixI9LT09GsWTP88ssvaiO5OVm3bh1mzJiBcePG4d9//0W5cuXwySefoGPHjgCA7777Dn///Te8vLxgYGCAoUOHokuXLkhJSSm0cyEiIiIiInqTIL59EyVRIVAqlTA1NUX5NWuglcdESlQ4sh5twgl65MF8y0slCIj19i5REzt87B6+nk+BOZcH8y0v5ltezLf8SmLOs2qDlJQUmJiY5NquVFzWS0RERERERCVbqbisl4pPXPfueX47QoWjJH5D9jFjvuX1sAQ+TJyIiIgKH0dOiYiIiIiIqNixOCUiIiIiIqJix+KUiIiIiIiIih3vOaUi5RQRwdl6ZcDZY+XFfMsra7ZeIiIi+rhx5JSIiIiIiIiKHYtTIiIiIiIiKnYfTXFqZ2eHhQsXFknfgiBg165d79WHp6cnxowZUyjx5CUqKgqCIODx48dFfiwiIiIiIqLCUqzFaW4FW3h4OMzMzPLVV0xMDIYOHSotF0ZBqSlfX1906dJFbV1ERAT09PQQFhYGANixYwemT58uSzxEREREREQfmo9mQiRLS8viDkGyevVqjBw5EitWrMDAgQMBAObm5sUcFRERERERUcn1QVzWmzUyOW/ePNjY2MDCwgIjR45ERkaG1ObNy3rt7OwAAF27doUgCNIyAOzevRt16tSBnp4e7O3tERwcjJcvX0rb4+Li0KxZM+jp6cHV1RWHDx/OV6xz5szBqFGjsGXLFqkwBbKPEtvZ2SEkJASDBg2CsbExKleujB9++EGtr5MnT8LDwwN6enqoV68edu3aBUEQcPHiRanNL7/8AmdnZ+jr66NFixZISEjIFtP27dtRo0YNKBQK2NnZSaO5b8YyY8YM+Pj4wMjICFWqVMGePXtw7949dO7cGUZGRnB3d8fZs2fzlQsiIiIiIiJNfTAjp0ePHoWNjQ2OHj2KGzduoFevXvDw8MCQIUOytY2JiUH58uWxbt06tG3bFtra2gCA48ePw8fHB4sXL0bTpk0RHx8vXQo8ZcoUqFQqeHt7w8rKCqdPn0ZKSkq+7hMdP348li9fjr1796JVq1bvbB8WFobp06fj22+/RUREBIYPH47mzZujWrVqUCqV6NSpE9q3b48ff/wRt27dyhbL7du34e3tjZEjR2Lo0KE4e/Ysxo0bp9bm3Llz6NmzJ6ZOnYpevXrh5MmTGDFiBCwsLODr6yu1W7BgAUJCQjBp0iQsWLAA/fv3R+PGjTFo0CDMnTsX48ePh4+PD/766y8Irx+j8aa0tDSkpaVJy0qlEsDrR27k0J4Kl4o5lhXzLS+VIODRG19GUtFjvuXFfMuL+ZYX8y2/kphzpYYxfRAjpwBQtmxZLF26FNWrV0fHjh3RoUMHREZG5tg26xJfMzMzWFtbS8vBwcGYMGECBgwYAHt7e7Rp0wbTp0/HypUrAQBHjhzB1atXsWHDBtSqVQvNmjVDSEiIRvHt378fc+bMwe7duzUqTAGgffv2GDFiBBwdHTF+/HiUK1cOR48eBQD8+OOPEAQBq1atgqurK9q1a4evv/5abf/vv/8eDg4OCAsLQ7Vq1dC3b1+1ghMA5s+fj1atWmHSpElwdnaGr68v/P39MXfu3GyxDBs2DE5OTpg8eTKUSiXq16+PHj16wNnZGePHj0dsbCzu3r2b47mEhobC1NRU+rG1tdUoB0RERERERMAHNHJao0YNaQQUAGxsbHD58uV89XHp0iVER0dj5syZ0rrMzEy8ePECz549Q2xsLGxtbVGhQgVpe6NGjTTq293dHffv38eUKVPQoEEDGBkZabRPFkEQYG1tjeTkZADAtWvX4O7uDj09PalNgwYN1PaPjY1Fw4YN1da9HW9sbCw6d+6stq5JkyZYuHAhMjMzpZy+GYuVlRUAwM3NLdu65ORkWFtbZzuXoKAgBAQESMtKpRK2trbQEkVoiWJuKaBCxlzLi/mWT1kdHZjr6BR3GKUOcy4v5ltezLe8mG/5laScl9EwlmItTk1MTJCSkpJt/ePHj2Fqaqq2TuetExIEASqVKl/HS01NRXBwMLy9vbNte7MILIiKFSsiIiICLVq0QNu2bbF//34YGxvnuU9hnFNheTOWrMt2c1qXW3wKhQIKhaIIIyQiIiIioo9ZsV7WW61aNZw/fz7b+vPnz8PZ2fm9+tbR0UFmZqbaujp16uDatWtwdHTM9qOlpQUXFxfcvn0bSUlJ0j6nTp3S+JhVqlTBsWPHcOfOHbRt2xZPnjwpcPzVqlXD5cuX1e7jjImJUWvj4uKCM2fOqK17O14XFxdER0errYuOjoazs7PaSDQREREREVFxKtbidPjw4bh+/TpGjx6NP/74A9euXcP8+fPx008/ZZvYJ7/s7OwQGRmJO3fu4NGjRwCAyZMnY8OGDQgODsZff/2F2NhYbNmyBd999x0AoHXr1nB2dsaAAQNw6dIlHD9+HBMnTszXcW1tbREVFYXk5GR4eXlJEwPlV58+faBSqTB06FDExsbi4MGDmDdvHoD/H8X88ssvERcXh6+//hrXrl3Djz/+iPDwcLV+xo0bh8jISEyfPh3Xr1/H+vXrsXTpUgQGBhYoLiIiIiIioqJQrMWpvb09fvvtN1y9ehWtW7dGw4YNsXXrVmzbtg1t27Z9r77DwsJw+PBh2Nraonbt2gAALy8v7N27F4cOHUL9+vXxySefYMGCBahSpQoAQEtLCzt37sTz58/RoEED+Pn5qd2fqqlKlSohKioK9+/fL3CBamJigv/973+4ePEiPDw8MHHiREyePBnA/1+CXLlyZWzfvh27du1CrVq1sGLFimwTONWpUwdbt27Fli1bULNmTUyePBnTpk3LNnESERERERFRcRJEkTN6fCg2b96MgQMHIiUlBfr6+sUdTp6USiVMTU1Rfs0aaBkYFHc4H72sR5twgh55MN/yUgkCYr29S9TEDh+7h6+n/GfO5cF8y4v5lhfzLb+SmPOs2iAlJQUmJia5tvtgZustjTZs2AB7e3tUrFgRly5dwvjx49GzZ88SX5i+Ka579zxfgFQ4SuIfoY8Z8y2vhyXweW1ERERU+FiclmB37tzB5MmTcefOHdjY2KBHjx4FusyYiIiIiIiopGNxWoJ98803+Oabb4o7DCIiIiIioiJXrBMiEREREREREQEcOaUi5hQRwQmRZMAJeuSVNUEPERERERUejpwSERERERFRsWNxSkRERERERMWOxWkh8PX1RZcuXT7qY4eHh8PMzKzIj0NERERERKVTqS1O7927h+HDh6Ny5cpQKBSwtraGl5cXoqOj893XokWLEB4eLi17enpizJgxhRcsERERERHRR67UTojUrVs3pKenY/369bC3t8fdu3cRGRmJBw8e5LsvU1PTIogwb5mZmRBeT4JDRERERET0oSuVI6ePHz/G8ePHMXv2bLRo0QJVqlRBgwYNEBQUhM8//xyBgYHo2LGj1H7hwoUQBAEHDhyQ1jk6OmL16tUA1C+t9fX1xbFjx7Bo0SIIggBBEJCQkABfX19p+c2fqKgoAEBaWhoCAwNRsWJFGBoaomHDhtI24P8vq92zZw9cXV2hUCiQmJiY7dwOHDiATz/9FGZmZrCwsEDHjh0RHx8vbU9ISIAgCNixYwdatGgBAwMD1KpVC7///rtaP+Hh4ahcuTIMDAzQtWvXAhXtREREREREmiqVI6dGRkYwMjLCrl278Mknn0ChUKhtb968OVavXo3MzExoa2vj2LFjKFeuHKKiotC2bVv8+++/iI+Ph6enZ7a+Fy1ahOvXr6NmzZqYNm0aAMDS0hKLFi3CrFmzpHazZs3CTz/9hOrVqwMA/P39ceXKFWzZsgUVKlTAzp070bZtW1y+fBlOTk4AgGfPnmH27NlYvXo1LCwsUL58+WzHf/r0KQICAuDu7o7U1FRMnjwZXbt2xcWLF6Gl9f/fRUycOBHz5s2Dk5MTJk6ciN69e+PGjRsoU6YMTp8+jcGDByM0NBRdunTBgQMHMGXKlDxzmpaWhrS0NGlZqVQCeP2IE47wFjkVcywrlSDgUUZGcYdRajDX8mPO5cV8y4v5lhfzLb+SmHOlhjGVyuK0TJkyCA8Px5AhQ7BixQrUqVMHzZs3xxdffAF3d3c0bdoUT548wYULF1C3bl389ttv+Prrr7Fr1y4AQFRUFCpWrAhHR8dsfZuamkJXVxcGBgawtrZWW591+e+OHTuwcuVKHDlyBNbW1khMTMS6deuQmJiIChUqAAACAwNx4MABrFu3DiEhIQCAjIwMLF++HLVq1cr13Lp166a2vHbtWlhaWuLKlSuoWbOmtD4wMBAdOnQAAAQHB6NGjRq4ceMGqlevjkWLFqFt27b45ptvAADOzs44efKk2sjx20JDQxEcHJzrdiIiIiIioryUyuIUeFXEdejQAcePH8epU6ewf/9+zJkzB6tXr4avry9q1aqFqKgo6OrqQldXF0OHDsWUKVOQmpqKY8eOoXnz5gU67oULF9C/f38sXboUTZo0AQBcvnwZmZmZcHZ2VmublpYGCwsLaVlXVxfu7u559h8XF4fJkyfj9OnTuH//PlQqFQAgMTFRrTh9sx8bGxsAQHJyMqpXr47Y2Fh07dpVrd9GjRrlWZwGBQUhICBAWlYqlbC1tYWWKEJLFPOMmQoPcy2fsjo6MNfRKe4wShXmW37MubyYb3kx3/JivuVXknJeRsNYSm1xCgB6enpo06YN2rRpg0mTJsHPzw9TpkyBr68vPD09ERUVBYVCgebNm8Pc3BwuLi44ceIEjh07hnHjxuX7eHfu3MHnn38OPz8/DB48WFqfmpoKbW1tnDt3Dtra2mr7GBkZSf/W19d/5yRInTp1QpUqVbBq1SpUqFABKpUKNWvWRHp6ulo7nTdeIFl9ZhWyBaFQKLJdHk1ERERERKSpUl2cvs3V1VW6dLd58+ZYu3YtypQpg7Zt2wJ49YiYn376CdevX8/xftMsurq6yMzMVFv34sULdO7cGdWrV8f8+fPVttWuXRuZmZlITk5G06ZNCxz/gwcPcO3aNaxatUrq58SJE/nux8XFBadPn1Zbd+rUqQLHRURERERE9C6lsjh98OABevTogUGDBsHd3R3GxsY4e/Ys5syZg86dOwMAmjVrhidPnmDv3r3SREaenp7o3r07bGxssl2C+yY7OzucPn0aCQkJMDIygrm5OYYNG4bbt28jMjIS9+7dk9qam5vD2dkZffv2hY+PD8LCwlC7dm3cu3cPkZGRcHd3l+4NfZeyZcvCwsICP/zwA2xsbJCYmIgJEybkOz+jR49GkyZNMG/ePHTu3BkHDx7M85JeIiIiIiKi91UqHyVjZGSEhg0bYsGCBWjWrBlq1qyJSZMmYciQIVi6dCmAV4Wem5sbLC0tpRl1mzVrBpVK9c77TQMDA6GtrQ1XV1dYWloiMTERx44dQ1JSElxdXWFjYyP9nDx5EgCwbt06+Pj4YNy4cahWrRq6dOmCmJgYVK5cWePz0tLSwpYtW3Du3DnUrFkTY8eOxdy5c/Odn08++QSrVq3CokWLUKtWLRw6dAjfffddvvshIiIiIiLSlCCKnEGFCp9SqYSpqSnKr1kDLQOD4g7no5f1KBlOiCQPlSAg1tu7RE008DF7+Hr6eeZbPsy5vJhveTHf8mK+5VcSc55VG6SkpMDExCTXdqVy5JSIiIiIiIhKllJ5zynJJ6579zy/HaHCURK/IfuYPSyBD7cmIiIi+tBx5JSIiIiIiIiKHYtTIiIiIiIiKna8rJeKlFNEBCdEkgEnRJJX1oRIRERERFR4OHJKRERERERExY7FKRERERERERU7FqcllK+vL7p06ZKvfezs7LBw4cIiiYeIiIiIiKgosTgtAr6+vhAEQfqxsLBA27Zt8ccffxTpcWNiYjB06NAiPQYREREREVFRYHFaRNq2bYukpCQkJSUhMjISZcqUQceOHYv0mJaWljDg5ENERERERPQBYnFaRBQKBaytrWFtbQ0PDw9MmDABt2/fxr179wAAt2/fRs+ePWFmZgZzc3N07twZCQkJufb35MkT9O3bF4aGhrCxscGCBQvg6emJMWPGSG3evKw3ISEBgiDg4sWL0vbHjx9DEARERUUBAKKioiAIAg4ePIjatWtDX18fLVu2RHJyMvbv3w8XFxeYmJigT58+ePbsWSFniIiIiIiI6P/xUTIySE1NxaZNm+Do6AgLCwtkZGTAy8sLjRo1wvHjx1GmTBnMmDFDuvRXV1c3Wx8BAQGIjo7Gnj17YGVlhcmTJ+P8+fPw8PB47/imTp2KpUuXwsDAAD179kTPnj2hUCjw448/IjU1FV27dsWSJUswfvz4XPtIS0tDWlqatKxUKgG8fsTJ68ecUNFRMceyUgkCHmVkFHcYpQZzLT/mXF7Mt7yYb3kx3/IriTlXahgTi9MisnfvXhgZGQEAnj59ChsbG+zduxdaWlr48ccfoVKpsHr1agivi4p169bBzMwMUVFR+Oyzz9T6evLkCdavX48ff/wRrVq1ktpXqFChUGKdMWMGmjRpAgAYPHgwgoKCEB8fD3t7ewBA9+7dcfTo0TyL09DQUAQHBxdKPEREREREVPqwOC0iLVq0wPfffw8AePToEZYvX4527drhzJkzuHTpEm7cuAFjY2O1fV68eIH4+Phsff3999/IyMhAgwYNpHWmpqaoVq1aocTq7u4u/dvKygoGBgZSYZq17syZM3n2ERQUhICAAGlZqVTC1tYWWqIILVEslDjp3Zhr+ZTV0YG5jk5xh1GqMN/yY87lxXzLi/mWF/Mtv5KU8zIaxsLitIgYGhrC0dFRWl69ejVMTU2xatUqpKamom7duti8eXO2/SwtLQvl+Fpar24nFt8oVjJyGU7XeePFIgiC2nLWOpVKlefxFAoFFApFQcMlIiIiIqJSjhMiyUQQBGhpaeH58+eoU6cO4uLiUL58eTg6Oqr9mJqaZtvX3t4eOjo6iImJkdalpKTg+vXruR4vq8hNSkqS1r05ORIREREREVFJwuK0iKSlpeHOnTu4c+cOYmNjMWrUKKSmpqJTp07o27cvypUrh86dO+P48eO4efMmoqKiMHr0aPzzzz/Z+jI2NsaAAQPw9ddf4+jRo/jrr78wePBgaGlpSfesvk1fXx+ffPIJZs2ahdjYWBw7dgzfffddUZ82ERERERFRgbA4LSIHDhyAjY0NbGxs0LBhQ8TExGDbtm3w9PSEgYEBfvvtN1SuXBne3t5wcXHB4MGD8eLFC5iYmOTY3/z589GoUSN07NgRrVu3RpMmTeDi4gI9Pb1cY1i7di1evnyJunXrYsyYMZgxY0ZRnS4REREREdF7EUSRM6h8iJ4+fYqKFSsiLCwMgwcPLu5wslEqlTA1NUX5NWugZWBQ3OF89LIeJcMJkeShEgTEenuXqIkGPmYPX98vz3zLhzmXF/MtL+ZbXsy3/EpizrNqg5SUlFwH4wBOiPTBuHDhAq5evYoGDRogJSUF06ZNAwB07ty5mCMjIiIiIiJ6fyxOPyDz5s3DtWvXoKuri7p16+L48eMoV65ccYeVp7ju3fP8doQKR0n8huxj9rAEPtyaiIiI6EPH4vQDUbt2bZw7d664wyAiIiIiIioSnBCJiIiIiIiIih2LUyIiIiIiIip2vKyXipRTRARn65UBZ+uVV9ZsvURERERUeDhySkRERERERMWOxalMoqKiIAgCHj9+/F792NnZYeHChdKyIAjYtWvXe/WpCU9PT4wZM6bIj0NERERERKUTL+stBMLrSypzM2XKFHh6ehbKsWJiYmBoaFgofREREREREZUULE4LQVJSkvTvn3/+GZMnT8a1a9ekdUZGRjh79myhHMvS0rJQ+iEiIiIiIipJeFlvIbC2tpZ+TE1NIQiC2jojIyOp7blz51CvXj0YGBigcePGakVsfHw8OnfuDCsrKxgZGaF+/fo4cuSI2rHevqz3bePHj4ezszMMDAxgb2+PSZMmISMjQ9o+depUeHh4YOPGjbCzs4OpqSm++OILPHnyRGrz9OlT+Pj4wMjICDY2NggLCyuELBEREREREeWuQCOnAwYMwODBg9GsWbPCjuejN3HiRISFhcHS0hJffvklBg0ahOjoaABAamoq2rdvj5kzZ0KhUGDDhg3o1KkTrl27hsqVK2vUv7GxMcLDw1GhQgVcvnwZQ4YMgbGxMb755hupTXx8PHbt2oW9e/fi0aNH6NmzJ2bNmoWZM2cCAL7++mscO3YMu3fvRvny5fHtt9/i/Pnz8PDwyPW4aWlpSEtLk5aVSiWA17PIvuOyZ3p/KuZYVipBwKM3vvShosVcy485lxfzLS/mW17Mt/xKYs6VGsZUoJHTlJQUtG7dGk5OTggJCcG///5bkG5KpZkzZ6J58+ZwdXXFhAkTcPLkSbx48QIAUKtWLQwbNgw1a9aEk5MTpk+fDgcHB+zZs0fj/r/77js0btwYdnZ26NSpEwIDA7F161a1NiqVCuHh4ahZsyaaNm2K/v37IzIyEsCrAnnNmjWYN28eWrVqBTc3N6xfvx4vX77M87ihoaEwNTWVfmxtbfOZGSIiIiIiKs0KNHK6a9cu3Lt3Dxs3bsT69esxZcoUtG7dGoMHD0bnzp2ho6NT2HF+NNzd3aV/29jYAACSk5NRuXJlpKamYurUqdi3bx+SkpLw8uVLPH/+HImJiRr3//PPP2Px4sWIj49HamoqXr58CRMTE7U2dnZ2MDY2VosjOTkZwKtR1fT0dDRs2FDabm5ujmrVquV53KCgIAQEBEjLSqUStra20BJFPntTRsy1fMrq6MCcf+tkxXzLjzmXF/MtL+ZbXsy3/EpSzstoGEuB7zm1tLREQEAALl26hNOnT8PR0RH9+/dHhQoVMHbsWMTFxRW064/am4V71iy/KpUKABAYGIidO3ciJCQEx48fx8WLF+Hm5ob09HSN+v7999/Rt29ftG/fHnv37sWFCxcwceLEbPu//eWBIAhSDAWlUChgYmKi9kNERERERKSp954QKSkpCYcPH8bhw4ehra2N9u3b4/Lly3B1dcWCBQsKI8ZSIzo6Gr6+vujatSvc3NxgbW2NhIQEjfc/efIkqlSpgokTJ6JevXpwcnLCrVu38hWDg4MDdHR0cPr0aWndo0ePcP369Xz1Q0RERERElB8Fuqw3IyMDe/bswbp163Do0CG4u7tjzJgx6NOnjzRitnPnTgwaNAhjx44t1IA/Zk5OTtixYwc6deoEQRAwadKkfI1oOjk5ITExEVu2bEH9+vWxb98+7Ny5M18xGBkZYfDgwfj6669hYWGB8uXLY+LEidDS4sTORERERERUdApUnNrY2EClUqF37944c+ZMjrO4tmjRAmZmZu8ZXukyf/58DBo0CI0bN0a5cuUwfvx4adZbTXz++ecYO3Ys/P39kZaWhg4dOmDSpEmYOnVqvuKYO3cuUlNT0alTJxgbG2PcuHFISUnJ59kQERERERFpThDF/M+gsnHjRvTo0QN6enpFERN9BJRKJUxNTVF+zRpoGRgUdzgfvaxHyXBCJHmoBAGx3t4laqKBj9nD19PPM9/yYc7lxXzLi/mWF/Mtv5KY86zaICUlJc+5aQo0ctq/f/8CB0ZERERERET0tgIVp0+fPsWsWbMQGRmJ5OTkbPdF/v3334USHH344rp358y9MiiJ35B9zB6WwIdbExEREX3oClSc+vn54dixY+jfvz9sbGykR6IQERERERERFUSBitP9+/dj3759aNKkSWHHQ0RERERERKVQgZ4PUrZsWZibmxd2LERERERERFRKFWjkdPr06Zg8eTLWr18PA87ESnlwiojgbL0y4Gy98sqarZeIiIiICk+BitOwsDDEx8fDysoKdnZ20HlrEpbz588XSnBERERERERUOhSoOO3SpUshh0FERERERESlWYGK0ylTphR2HERERERERFSKFWhCJCo8vr6+EAQh28+NGzeKOzQiIiIiIiLZFGjkNDMzEwsWLMDWrVuRmJiI9PR0te0PHz4slOBKi7Zt22LdunVq6ywtLdWW09PToaurK2dYREREREREsinQyGlwcDDmz5+PXr16ISUlBQEBAfD29oaWlhamTp1ayCF+/BQKBaytrdV+WrVqBX9/f4wZMwblypWDl5cXAGD+/Plwc3ODoaEhbG1tMWLECKSmpkp9hYeHw8zMDAcPHoSLiwuMjIzQtm1bJCUlqR1z7dq1qFGjBhQKBWxsbODv7y9te/z4Mfz8/GBpaQkTExO0bNkSly5dkicZRERERERUKhVo5HTz5s1YtWoVOnTogKlTp6J3795wcHCAu7s7Tp06hdGjRxd2nKXS+vXrMXz4cERHR0vrtLS0sHjxYlStWhV///03RowYgW+++QbLly+X2jx79gzz5s3Dxo0boaWlhX79+iEwMBCbN28GAHz//fcICAjArFmz0K5dO6SkpKgdo0ePHtDX18f+/fthamqKlStXolWrVrh+/Xquz7dNS0tDWlqatKxUKgG8fsTJ68ecUNFRMceyUgkCHmVkFHcYpQZzLT/mXF7Mt7yYb3kx3/IriTlXahhTgYrTO3fuwM3NDQBgZGSElJQUAEDHjh0xadKkgnRZqu3duxdGRkbScrt27QAATk5OmDNnjlrbMWPGSP+2s7PDjBkz8OWXX6oVpxkZGVixYgUcHBwAAP7+/pg2bZq0fcaMGRg3bhy++uoraV39+vUBACdOnMCZM2eQnJwMhUIBAJg3bx527dqFiIgIDB06NMdzCA0NRXBwcEFOn4iIiIiIqGDFaaVKlZCUlITKlSvDwcEBhw4dQp06dRATEyMVNKS5Fi1a4Pvvv5eWDQ0N0bt3b9StWzdb2yNHjiA0NBRXr16FUqnEy5cv8eLFCzx79gwGBgYAAAMDA6kwBQAbGxskJycDAJKTk/Hff/+hVatWOcZy6dIlpKamwsLCQm398+fPER8fn+s5BAUFISAgQFpWKpWwtbWFlihCSxQ1yAIVBuZaPmV1dGD+1jOeqWgx3/JjzuXFfMuL+ZYX8y2/kpTzMhrGUqDitGvXroiMjETDhg0xatQo9OvXD2vWrEFiYiLGjh1bkC5LNUNDQzg6Oua4/k0JCQno2LEjhg8fjpkzZ8Lc3BwnTpzA4MGDkZ6eLhWnOm/98gVBgPi6aNHX188zltTUVNjY2CAqKirbNjMzs1z3UygU/GKCiIiIiIgKrEDF6axZs6R/9+rVC5UrV8bvv/8OJycndOrUqdCCI3Xnzp2DSqVCWFgYtLRezWW1devWfPVhbGwMOzs7REZGokWLFtm216lTB3fu3EGZMmVgZ2dXGGETERERERG9U4GK07c1atQIjRo1KoyuKA+Ojo7IyMjAkiVL0KlTJ0RHR2PFihX57mfq1Kn48ssvUb58ebRr1w5PnjxBdHQ0Ro0ahdatW6NRo0bo0qUL5syZA2dnZ/z333/Yt28funbtinr16hXBmRERERERUWlXoEfJAMC1a9fg7++PVq1aSY89uXbtWmHGRm+pVasW5s+fj9mzZ6NmzZrYvHkzQkND893PgAEDsHDhQixfvhw1atRAx44dERcXB+DVJcC//PILmjVrhoEDB8LZ2RlffPEFbt26BSsrq8I+JSIiIiIiIgCAIIr5n0Fl+/bt+OKLL1CvXj1pxPTUqVOIiYnBli1b0K1bt0IPlD4sSqUSpqamKL9mDbRe3wtLRSfrUTKcEEkeKkFArLd3iZpo4GP28PX088y3fJhzeTHf8mK+5cV8y68k5jyrNkhJSYGJiUmu7QpUnDo4OKBv375qjycBgClTpmDTpk15zupKpYOmL0AqHCXxj9DHjPmWF/MtP+ZcXsy3vJhveTHf8iuJOde0NijQZb1JSUnw8fHJtr5fv35ISkoqSJdERERERERUihWoOPX09MTx48ezrT9x4gSaNm363kERERERERFR6VKg2Xo///xzjB8/HufOncMnn3wC4NU9p9u2bUNwcDD27Nmj1paIiIiIiIgoLwW65zTrGZvv7FwQkJmZme+g6MPHCZHkxQl65FUS7+X4mDHf8mPO5cV8y4v5lhfzLb+SmHNN7zkt0MipSqUqcGBEREREREREbyvwc06JiIiIiIiICkuBRk4BICYmBkePHkVycnK2kdT58+e/d2Akj4SEBFStWhUXLlyAh4dHcYdDRERERESlVIFGTkNCQtCwYUOsW7cOZ8+exYULF6SfixcvFnKIH6/ff/8d2tra6NChQ6H2Gx4eDjMzM43a2traIikpCTVr1izUGIiIiIiIiPKjQCOnixYtwtq1a+Hr61vI4ZQua9aswahRo7BmzRr8999/qFChgqzHT09Ph66uLqytrWU9LhERERER0dsKNHKqpaWFJk2aFHYspUpqaip+/vlnDB8+HB06dEB4eLi0LaeRz127dkEQBGn50qVLaNGiBYyNjWFiYoK6devi7NmziIqKwsCBA5GSkgJBECAIAqZOnQoAsLOzw/Tp0+Hj4wMTExMMHToUCQkJEARBGvHOzMzE4MGDUbVqVejr66NatWpYtGhREWeDiIiIiIhKuwKNnI4dOxbLli3DwoULCzmc0mPr1q2oXr06qlWrhn79+mHMmDEICgpSK0Dz0rdvX9SuXRvff/89tLW1cfHiRejo6KBx48ZYuHAhJk+ejGvXrgEAjIyMpP3mzZuHyZMnY8qUKTn2q1KpUKlSJWzbtg0WFhY4efIkhg4dChsbG/Ts2TPXeNLS0pCWliYtK5XKV/0JAqDhOVHBqQQBj15PG05Fj7mWF/MtP+ZcXsy3vJhveTHf8iuJOVdqGFOBitPAwEB06NABDg4OcHV1hc5bz9DZsWNHQbotVdasWYN+/foBANq2bYuUlBQcO3YMnp6eGu2fmJiIr7/+GtWrVwcAODk5SdtMTU0hCEKOl+u2bNkS48aNk5YTEhLUtuvo6CA4OFharlq1Kn7//Xds3bo1z+I0NDRUbT8iIiIiIqL8KFBxOnr0aBw9ehQtWrSAhYWFxqN99Mq1a9dw5swZ7Ny5EwBQpkwZ9OrVC2vWrNG4OA0ICICfnx82btyI1q1bo0ePHnBwcHjnfvXq1Xtnm2XLlmHt2rVITEzE8+fPkZ6e/s6ZfIOCghAQECAtK5VK2NraQksUoSWK7zwmvb+yOjol6mHLpQHzLS/mW37MubyYb3kx3/JivuVXknJeRsNYClScrl+/Htu3by/0WWZLizVr1uDly5dqEyCJogiFQoGlS5dCS0sL4lsFXcZbQ+FTp05Fnz59sG/fPuzfvx9TpkzBli1b0LVr1zyPbWhomOf2LVu2IDAwEGFhYWjUqBGMjY0xd+5cnD59Os/9FAoFFApFnm2IiIiIiIhyU6Di1NzcXKNROsru5cuX2LBhA8LCwvDZZ5+pbevSpQt++uknVKlSBU+ePMHTp0+lYjKnR/Q4OzvD2dkZY8eORe/evbFu3Tp07doVurq6yMzMLFB80dHRaNy4MUaMGCGti4+PL1BfREREREREmirQbL1Tp07FlClT8OzZs8KO56O3d+9ePHr0CIMHD0bNmjXVfrp164Y1a9agYcOGMDAwwLfffov4+Hj8+OOParP5Pn/+HP7+/oiKisKtW7cQHR2NmJgYuLi4AHg1K29qaioiIyNx//79fP2enJyccPbsWRw8eBDXr1/HpEmTEBMTU9hpICIiIiIiUlOg4nTx4sXYv38/rKys4Obmhjp16qj9UO7WrFmD1q1bw9TUNNu2bt264ezZs/jnn3+wadMm/PLLL3Bzc8NPP/0kPQ4GALS1tfHgwQP4+PjA2dkZPXv2RLt27aQJiRo3bowvv/wSvXr1gqWlJebMmaNxfMOGDYO3tzd69eqFhg0b4sGDB2qjqEREREREREVBEN++uVED75qVNbfHlFDpoVQqYWpqivJr1kDLwKC4w/noqQQBsd7eJerG94/Zw9f3gDPf8mC+5cecy4v5lhfzLS/mW34lMedZtUFKSgpMTExybVege05ZfBIREREREVFhKlBxmuXcuXOIjY0FANSoUQO1a9culKDo4xHXvXue345Q4XhYAh+2TERERESUHwUqTpOTk/HFF18gKioKZmZmAIDHjx+jRYsW2LJlCywtLQszRiIiIiIiIvrIFWhCpFGjRuHJkyf466+/8PDhQzx8+BB//vknlEolRo8eXdgxEhERERER0UeuQCOnBw4cwJEjR6RHlwCAq6srli1blu3ZnVS6OUVEcEIkGWRNiERERERE9KEq0MipSqWCTg6zP+no6EClUr13UERERERERFS6FKg4bdmyJb766iv8999/0rp///0XY8eORatWrQotOCIiIiIiIiodClScLl26FEqlEnZ2dnBwcICDgwOqVq0KpVKJJUuWFHaMJLPw8HBpoisAmDp1Kjw8PIotHiIiIiIi+vgV6J5TW1tbnD9/HkeOHMHVq1cBAC4uLmjdunWhBlfa+fr6Yv369dKyubk56tevjzlz5sDd3b3IjturVy+0b9++yPonIiIiIiJ6W75GTn/99Ve4urpCqVRCEAS0adMGo0aNwqhRo1C/fn3UqFEDx48fL6pYS6W2bdsiKSkJSUlJiIyMRJkyZdCxY8dc22cUwvMu9fX1Ub58+ffuh4iIiIiISFP5Kk4XLlyIIUOGwMTEJNs2U1NTDBs2DPPnzy+04AhQKBSwtraGtbU1PDw8MGHCBNy+fRv37t1DQkICBEHAzz//jObNm0NPTw+bN2/GgwcP0Lt3b1SsWBEGBgZwc3PDTz/9JPWZtd/bP56engCyX9ZLRERERERU1PJ1We+lS5cwe/bsXLd/9tlnmDdv3nsHRTlLTU3Fpk2b4OjoCAsLCzx9+hQAMGHCBISFhaF27drQ09PDixcvULduXYwfPx4mJibYt28f+vfvDwcHBzRo0AC2trZISkqS+r1z5w5at26NZs2aFTi2tLQ0pKWlSctKpRLAq0ecQBAK3C9pRiUIeFQIo+akGeZaXsy3/JhzeTHf8mK+5cV8y68k5lypYUz5Kk7v3r2b4yNkpM7KlMG9e/fy0yW9w969e2FkZAQAePr0KWxsbLB3715oaf3/oPeYMWPg/dYzLgMDA6V/jxo1CgcPHsTWrVvRoEEDaGtrw9raGgDw4sULdOnSBY0aNcLUqVMLHGdoaCiCg4MLvD8REREREZVu+SpOK1asiD///BOOjo45bv/jjz9gY2NTKIHRKy1atMD3338PAHj06BGWL1+Odu3a4cyZM1KbevXqqe2TmZmJkJAQbN26Ff/++y/S09ORlpYGAwODbP0PGjQIT548weHDh9UK3vwKCgpCQECAtKxUKmFrawstUYSWKBa4X9JcWR0dmOfx5REVPuZbXsy3/JhzeTHf8mK+5cV8y68k5byMhrHkqzht3749Jk2ahLZt20JPT09t2/PnzzFlypQ8J+uh/DM0NFT7MmD16tUwNTXFqlWr4OfnJ7V509y5c7Fo0SIsXLgQbm5uMDQ0xJgxY5Cenq7WbsaMGTh48CDOnDkDY2Pj94pToVBAoVC8Vx9ERERERFR65as4/e6777Bjxw44OzvD398f1apVAwBcvXoVy5YtQ2ZmJiZOnFgkgdIrgiBAS0sLz58/z7VNdHQ0OnfujH79+gEAVCoVrl+/DldXV6nN9u3bMW3aNOzfvx8ODg5FHjcREREREVFe8lWcWllZ4eTJkxg+fDiCgoIgvr5cUxAEeHl5YdmyZbCysiqSQEurtLQ03LlzB8Cry3qXLl2K1NRUdOrUKdd9nJycEBERgZMnT6Js2bKYP38+7t69KxWnf/75J3x8fDB+/HjUqFFD6l9XVxfm5uZFf1JERERERERvyVdxCgBVqlTBL7/8gkePHuHGjRsQRRFOTk4oW7ZsUcRX6h04cEC6j9fY2BjVq1fHtm3b4OnpiYSEhBz3+e677/D333/Dy8sLBgYGGDp0KLp06YKUlBQAwNmzZ/Hs2TPMmDEDM2bMkPZr3rw5oqKiivqUiIiIiIiIshFEkbPVUOFTKpUwNTVF+TVroJXDRExUuFSCgFhv7xJ14/vH7OHr6dCZb3kw3/JjzuXFfMuL+ZYX8y2/kpjzrNogJSUFJiYmubYr+PSsRERERERERIUk35f1EuVHXPfueX47QoXjYQl82DIRERERUX5w5JSIiIiIiIiKHYtTIiIiIiIiKnYsTomIiIiIiKjY8Z5TKlJOERGcrVcGWbP1EhERERF9qDhySkRERERERMWOxSlBEATs2rWruMMgIiIiIqJSjMWpTO7cuYNRo0bB3t4eCoUCtra26NSpEyIjI4s7NCIiIiIiomLHe05lkJCQgCZNmsDMzAxz586Fm5sbMjIycPDgQYwcORJXr14t7hCJiIiIiIiKFUdOZTBixAgIgoAzZ86gW7ducHZ2Ro0aNRAQEIBTp04BAObPnw83NzcYGhrC1tYWI0aMQGpqqtRHeHg4zMzMcPDgQbi4uMDIyAht27ZFUlKS1CYmJgZt2rRBuXLlYGpqiubNm+P8+fNqscTFxaFZs2bQ09ODq6srDh8+nC3e8ePHw9nZGQYGBrC3t8ekSZOQkZFRRNkhIiIiIiLiyGmRe/jwIQ4cOICZM2fC0NAw23YzMzMAgJaWFhYvXoyqVavi77//xogRI/DNN99g+fLlUttnz55h3rx52LhxI7S0tNCvXz8EBgZi8+bNAIAnT55gwIABWLJkCURRRFhYGNq3b4+4uDgYGxtDpVLB29sbVlZWOH36NFJSUjBmzJhsMRkbGyM8PBwVKlTA5cuXMWTIEBgbG+Obb77J9TzT0tKQlpYmLSuVSgCvZpGFIBQkdZQPKkHAI36BIBvmWl7Mt/yYc3kx3/JivuXFfMuvJOZcqWFMLE6L2I0bNyCKIqpXr55nuzeLRDs7O8yYMQNffvmlWnGakZGBFStWwMHBAQDg7++PadOmSdtbtmyp1ucPP/wAMzMzHDt2DB07dsSRI0dw9epVHDx4EBUqVAAAhISEoF27dmr7fffdd2qxBAYGYsuWLXkWp6GhoQgODs7zHImIiIiIiHLD4rSIiaKoUbsjR44gNDQUV69ehVKpxMuXL/HixQs8e/YMBq+fE2pgYCAVpgBgY2OD5ORkafnu3bv47rvvEBUVheTkZGRmZuLZs2dITEwEAMTGxsLW1lYqTAGgUaNG2WL5+eefsXjxYsTHxyM1NRUvX76EiYlJnvEHBQUhICBAWlYqlbC1tYWWKEJLwxzQ+ymrowNzHZ3iDqNUYb7lxXzLjzmXF/MtL+ZbXsy3/EpSzstoGAvvOS1iTk5OEAQhz0mPEhIS0LFjR7i7u2P79u04d+4cli1bBgBIT0+X2um89UsVBEGt+B0wYAAuXryIRYsW4eTJk7h48SIsLCzU+niX33//HX379kX79u2xd+9eXLhwARMnTnxnHwqFAiYmJmo/REREREREmuLIaREzNzeHl5cXli1bhtGjR2e77/Tx48c4d+4cVCoVwsLCoKX16vuCrVu35vtY0dHRWL58Odq3bw8AuH37Nu7fvy9td3Fxwe3bt5GUlAQbGxsAkCZkynLy5ElUqVIFEydOlNbdunUr37EQERERERHlB0dOZbBs2TJkZmaiQYMG2L59O+Li4hAbG4vFixejUaNGcHR0REZGBpYsWYK///4bGzduxIoVK/J9HCcnJ2zcuBGxsbE4ffo0+vbtC319fWl769at4ezsjAEDBuDSpUs4fvy4WhGa1UdiYiK2bNmC+Ph4LF68GDt37nzvHBAREREREeWFxakM7O3tcf78ebRo0QLjxo1DzZo10aZNG0RGRuL7779HrVq1MH/+fMyePRs1a9bE5s2bERoamu/jrFmzBo8ePUKdOnXQv39/jB49GuXLl5e2a2lpYefOnXj+/DkaNGgAPz8/zJw5U62Pzz//HGPHjoW/vz88PDxw8uRJTJo06b1zQERERERElBdB1HTGHqJ8UCqVMDU1Rfk1a6D1ekInKjoqQUCst3eJuvH9Y/bw9XTozLc8mG/5MefyYr7lxXzLi/mWX0nMeVZtkJKSkufcNBw5JSIiIiIiomLHCZGoSMV1786Ze2XwsAQ+bJmIiIiIKD84ckpERERERETFjsUpERERERERFTsWp0RERERERFTseM8pFSmniAjO1iuDrNl6iYiIiIg+VBw5JSIiIiIiomLH4pSIiIiIiIiKHYvTQhAeHg4zM7MPru83JSQkQBAEXLx4sciPRURERERE9LZSU5z6+vpCEATMmjVLbf2uXbsgCILG/djZ2WHhwoWFHB0REREREVHpVmqKUwDQ09PD7Nmz8ejRo+IORSMZGRnFHQIREREREZEsSlVx2rp1a1hbWyM0NDTXNidOnEDTpk2hr68PW1tbjB49Gk+fPgUAeHp64tatWxg7diwEQcg24nrw4EG4uLjAyMgIbdu2RVJSktr21atXw8XFBXp6eqhevTqWL18ubcu6rPbnn39G8+bNoaenh82bN2eLLz4+Hp07d4aVlRWMjIxQv359HDlyRK2NnZ0dQkJCMGjQIBgbG6Ny5cr44Ycf1NqcOXMGtWvXhp6eHurVq4cLFy6obX/06BH69u0LS0tL6Ovrw8nJCevWrcsju0RERERERAVXqh4lo62tjZCQEPTp0wejR49GpUqV1LbHx8ejbdu2mDFjBtauXYt79+7B398f/v7+WLduHXbs2IFatWph6NChGDJkiNq+z549w7x587Bx40ZoaWmhX79+CAwMlArMzZs3Y/LkyVi6dClq166NCxcuYMiQITA0NMSAAQOkfiZMmICwsDCpcDx48KDacVJTU9G+fXvMnDkTCoUCGzZsQKdOnXDt2jVUrlxZahcWFobp06fj22+/RUREBIYPH47mzZujWrVqSE1NRceOHdGmTRts2rQJN2/exFdffaV2nEmTJuHKlSvYv38/ypUrhxs3buD58+e55jYtLQ1paWnSslKpBPDqESfIx2XTVDAqQcAjjrTLhrmWF/MtP+ZcXsy3vJhveTHf8iuJOVdqGFOpKk4BoGvXrvDw8MCUKVOwZs0atW2hoaHo27cvxowZAwBwcnLC4sWL0bx5c3z//fcwNzeHtrY2jI2NYW1trbZvRkYGVqxYAQcHBwCAv78/pk2bJm2fMmUKwsLC4P36WZRVq1bFlStXsHLlSrXidMyYMVKbnNSqVQu1atWSlqdPn46dO3diz5498Pf3l9a3b98eI0aMAACMHz8eCxYswNGjR1GtWjX8+OOPUKlUWLNmDfT09FCjRg38888/GD58uLR/YmIiateujXr16gF4NRqbl9DQUAQHB+fZhoiIiIiIKDelrjgFgNmzZ6Nly5YIDAxUW3/p0iX88ccfapfTiqIIlUqFmzdvwsXFJdc+DQwMpMIUAGxsbJCcnAwAePr0KeLj4zF48GC1EdeXL1/C1NRUrZ+sYjA3qampmDp1Kvbt24ekpCS8fPkSz58/R2Jiolo7d3d36d+CIMDa2lqKJzY2Fu7u7tDT05PaNGrUSG3/4cOHo1u3bjh//jw+++wzdOnSBY0bN841rqCgIAQEBEjLSqUStra20BJFaIlinudEhaOsjg7MdXSKO4xShfmWF/MtP+ZcXsy3vJhveTHf8itJOS+jYSylsjht1qwZvLy8EBQUBF9fX2l9amoqhg0bhtGjR2fb581LZnOi81bCBUGA+LooS01NBQCsWrUKDRs2VGunra2ttmxoaJjncQIDA3H48GHMmzcPjo6O0NfXR/fu3ZGenv7OeFQqVZ59v6ldu3a4desWfvnlFxw+fBitWrXCyJEjMW/evBzbKxQKKBQKjfsnIiIiIiJ6U6ksTgFg1qxZ8PDwQLVq1aR1derUwZUrV+Do6Jjrfrq6usjMzMzXsaysrFChQgX8/fff6Nu3b4FjBoDo6Gj4+vqia9euAF4VvgkJCfnqw8XFBRs3bsSLFy+k0dNTp05la2dpaYkBAwZgwIABaNq0Kb7++utci1MiIiIiIqL3Uapm632Tm5sb+vbti8WLF0vrxo8fj5MnT8Lf3x8XL15EXFwcdu/erXYvp52dHX777Tf8+++/uH//vsbHCw4ORmhoKBYvXozr16/j8uXLWLduHebPn5+vuJ2cnLBjxw5cvHgRly5dQp8+ffI1IgoAffr0gSAIGDJkCK5cuYJffvklW9E5efJk7N69Gzdu3MBff/2FvXv35nlZMxERERER0fsotcUpAEybNk2tsHN3d8exY8dw/fp1NG3aFLVr18bkyZNRoUIFtX0SEhLg4OAAS0tLjY/l5+eH1atXY926dXBzc0Pz5s0RHh6OqlWr5ivm+fPno2zZsmjcuDE6deoELy8v1KlTJ199GBkZ4X//+x8uX76M2rVrY+LEiZg9e7ZaG11dXQQFBcHd3R3NmjWDtrY2tmzZkq/jEBERERERaUoQRc5WQ4VPqVTC1NQU5desgZaBQXGH89FTCQJivb1L1I3vH7OHr6dDZ77lwXzLjzmXF/MtL+ZbXsy3/EpizrNqg5SUFJiYmOTartTec0ryiOvePc8XIBWOhyXweVZERERERPlRqi/rJSIiIiIiopKBxSkREREREREVOxanREREREREVOx4zykVKaeICE6IJIOsCZGIiIiIiD5UHDklIiIiIiKiYsfilIiIiIiIiIodi9MPmKenJ8aMGVPkx5k6dSo8PDyK/DhERERERFR6sTgtJr6+vujSpUtxh0FERERERFQisDgtgdLT04s7BCIiIiIiIlmxOC0BPD094e/vjzFjxqBcuXLw8vICAPz5559o164djIyMYGVlhf79++P+/fu59rNx40bUq1cPxsbGsLa2Rp8+fZCcnCxtj4qKgiAIiIyMRL169WBgYIDGjRvj2rVrav3MmjULVlZWMDY2xuDBg/HixYuiOXEiIiIiIqLX+CiZEmL9+vUYPnw4oqOjAQCPHz9Gy5Yt4efnhwULFuD58+cYP348evbsiV9//TXHPjIyMjB9+nRUq1YNycnJCAgIgK+vL3755Re1dhMnTkRYWBgsLS3x5ZdfYtCgQdJxt27diqlTp2LZsmX49NNPsXHjRixevBj29vZ5xp+Wloa0tDRpWalUAnj1iBMIQoHzQppRCQIeZWQUdxilBnMtL+Zbfsy5vJhveTHf8mK+5VcSc67UMCYWpyWEk5MT5syZIy3PmDEDtWvXRkhIiLRu7dq1sLW1xfXr1+Hs7Jytj0GDBkn/tre3x+LFi1G/fn2kpqbCyMhI2jZz5kw0b94cADBhwgR06NABL168gJ6eHhYuXIjBgwdj8ODBUhxHjhx55+hpaGgogoODC3byRERERERU6rE4LSHq1q2rtnzp0iUcPXpUrajMEh8fn2Nxeu7cOUydOhWXLl3Co0ePoFKpAACJiYlwdXWV2rm7u0v/trGxAQAkJyejcuXKiI2NxZdffqnWb6NGjXD06NE84w8KCkJAQIC0rFQqYWtrCy1RhJYo5rkvFY6yOjow19Ep7jBKFeZbXsy3/JhzeTHf8mK+5cV8y68k5byMhrGwOC0hDA0N1ZZTU1PRqVMnzJ49O1vbrILyTU+fPoWXlxe8vLywefNmWFpaIjExEV5eXtkmWNJ548UhvL7kNquQLSiFQgGFQvFefRARERERUenF4rSEqlOnDrZv3w47OzuUKfPuX9PVq1fx4MEDzJo1C7a2tgCAs2fP5vu4Li4uOH36NHx8fKR1p06dync/RERERERE+cHZekuokSNH4uHDh+jduzdiYmIQHx+PgwcPYuDAgcjMzMzWvnLlytDV1cWSJUvw999/Y8+ePZg+fXq+j/vVV19h7dq1WLduHa5fv44pU6bgr7/+KoxTIiIiIiIiyhWL0xKqQoUKiI6ORmZmJj777DO4ublhzJgxMDMzg5ZW9l+bpaUlwsPDsW3bNri6umLWrFmYN29evo/bq1cvTJo0Cd988w3q1q2LW7duYfjw4YVxSkRERERERLkSRJGz1VDhUyqVMDU1Rfk1a6BlYFDc4Xz0VIKAWG/vEnXj+8fs4evp0JlveTDf8mPO5cV8y4v5lhfzLb+SmPOs2iAlJQUmJia5tuPIKRERERERERU7TohERSque/c8vx2hwvGwBD5smYiIiIgoPzhySkRERERERMWOxSkREREREREVO17WS0XKKSKCEyLJIGtCJCIiIiKiDxVHTomIiIiIiKjYsTglIiIiIiKiYsfitBQSBAG7du0CACQkJEAQBFy8eLFYYyIiIiIiotKN95x+YHx9ffH48WOpuHxftra2SEpKQrly5QqlPyIiIiIiooJgcVrKaWtrw9raurjDICIiIiKiUo6X9X7APD09MXr0aHzzzTcwNzeHtbU1pk6dqtYmLi4OzZo1g56eHlxdXXH48GG17W9f1puZmYnBgwejatWq0NfXR7Vq1bBo0SKZzoiIiIiIiEorjpx+4NavX4+AgACcPn0av//+O3x9fdGkSRO0adMGKpUK3t7esLKywunTp5GSkoIxY8bk2Z9KpUKlSpWwbds2WFhY4OTJkxg6dChsbGzQs2fPXPdLS0tDWlqatKxUKl/1JwiAIBTKuVLuVIKARxkZxR1GqcFcy4v5lh9zLi/mW17Mt7yYb/mVxJwrNYyJxekHzt3dHVOmTAEAODk5YenSpYiMjESbNm1w5MgRXL16FQcPHkSFChUAACEhIWjXrl2u/eno6CA4OFharlq1Kn7//Xds3bo1z+I0NDRUbT8iIiIiIqL8YHH6gXN3d1dbtrGxQXJyMgAgNjYWtra2UmEKAI0aNXpnn8uWLcPatWuRmJiI58+fIz09HR4eHnnuExQUhICAAGlZqVTC1tYWWqIILVHMxxlRQZXV0YG5jk5xh1GqMN/yYr7lx5zLi/mWF/MtL+ZbfiUp52U0jIXF6QdO561ftCAIUKlUBe5vy5YtCAwMRFhYGBo1agRjY2PMnTsXp0+fznM/hUIBhUJR4OMSEREREVHpxuL0I+bi4oLbt28jKSkJNjY2AIBTp07luU90dDQaN26MESNGSOvi4+OLNE4iIiIiIiLO1vsRa926NZydnTFgwABcunQJx48fx8SJE/Pcx8nJCWfPnsXBgwdx/fp1TJo0CTExMTJFTEREREREpRWL04+YlpYWdu7ciefPn6NBgwbw8/PDzJkz89xn2LBh8Pb2Rq9evdCwYUM8ePBAbRSViIiIiIioKAiiyNlqqPAplUqYmpqi/Jo10DIwKO5wPnoqQUCst3eJuvH9Y/bw9XTozLc8mG/5MefyYr7lxXzLi/mWX0nMeVZtkJKSAhMTk1zbceSUiIiIiIiIih0nRKIiFde9e57fjlDheFgCH7ZMRERERJQfHDklIiIiIiKiYsfilIiIiIiIiIodi1MiIiIiIiIqdrznlIqUU0QEZ+uVQdZsvUREREREHyqOnBIREREREVGxY3FKRERERERExY7FqQx8fX0hCAJmzZqltn7Xrl0QBKGYoiIiIiIiIio5WJzKRE9PD7Nnz8ajR48Krc/09PRC64uIiIiIiKg4sTiVSevWrWFtbY3Q0NBc22zfvh01atSAQqGAnZ0dwsLC1Lbb2dlh+vTp8PHxgYmJCYYOHYru3bvD399fajNmzBgIgoCrV68CeFXAGhoa4siRIwCAAwcO4NNPP4WZmRksLCzQsWNHxMfHS/u3bNlSrT8AuHfvHnR1dREZGfneeSAiIiIiIsoJZ+uViba2NkJCQtCnTx+MHj0alSpVUtt+7tw59OzZE1OnTkWvXr1w8uRJjBgxAhYWFvD19ZXazZs3D5MnT8aUKVMAAL/88gtWrlwpbT927BjKlSuHqKgoVK9eHTExMcjIyEDjxo0BAE+fPkVAQADc3d2RmpqKyZMno2vXrrh48SK0tLTg5+cHf39/hIWFQaFQAAA2bdqEihUromXLlrmeX1paGtLS0qRlpVIJ4NUssuCly0VOJQh4lJFR3GGUGsy1vJhv+THn8mK+5cV8y4v5ll9JzLlSw5g4ciqjrl27wsPDQyos3zR//ny0atUKkyZNgrOzM3x9feHv74+5c+eqtWvZsiXGjRsHBwcHODg4wNPTE1euXMG9e/fw6NEjXLlyBV999RWioqIAAFFRUahfvz4MXj/OpVu3bvD29oajoyM8PDywdu1aXL58GVeuXAEAeL9+HMnu3bulY4aHh0v3zeYmNDQUpqam0o+tre175YqIiIiIiEqX/2vv3uNyvP8/gL+uSnfp7ixkKqzQSSQjfVVia+Z8DLHCxn7ynZbmp20p+UYZlkNmiNiYw4avzWJbU8iQqLEl1oTvRpHDrVil+/r94ev+7V4HRd1X7l7Px+N+PO7r9Lne17s2j3efw8WeUw2Lj4+Hn58fwsPD1fbn5uZi+PDhavu8vLyQkJCAyspK6OrqAgA8PDzUznFxcYGFhQXS09Ohr6+PHj16YMiQIUhMTATwqCfV19dXdf7Fixcxf/58nDhxAjdv3oRSqQQAXLlyBS4uLjAwMMDkyZOxceNGjBs3DqdPn8a5c+ewb9++Wp8rIiICYWFhqm2FQgEbGxvoiCJ0RLF+SaKnYt6iBSxatJA6jGaF+dYs5lvzmHPNYr41i/nWLOZb85pSzvXqGAuLUw3z9vaGv78/IiIi1Ibr1pWRkZHatiAI8Pb2RlpaGmQyGXx9fdGtWzeUlZXh3LlzOHbsmFohPHToUNjZ2WH9+vVo164dlEolXFxc1BZXeuONN9C9e3f85z//waZNm+Dn5wc7O7ta45LJZKphwERERERERPXF4lQCcXFx6N69O7p06aLa5+joiIyMDLXzMjIy0LlzZ1WvaU18fHywfv16yGQyxMbGQkdHB97e3vjwww9RVlYGLy8vAEBxcTHy8vKwfv169OvXDwBw9OjRKu25urrCw8MD69evx7Zt27B69epnfWQiIiIiIqJacc6pBFxdXREYGIiVK1eq9s2ZMwepqalYuHAhLly4gM2bN2P16tVVhv9W5/G8059//hn/+Mc/VPu2bt0KDw8PVW+rubk5LC0tsW7dOvz666/44Ycf1Ibi/tUbb7yBuLg4iKKIkSNHNsBTExERERER1YzFqURiYmJU8z0BwN3dHTt37sT27dvh4uKC+fPnIyYmpk5Df11dXWFmZobu3btDLpcDeFScVlZWqs031dHRwfbt25GVlQUXFxe88847VRZcemzChAnQ09PDhAkTYGBg8EzPSkRERERE9CSCKHK1GqqqoKAAL774IjIzM+Hu7l7v6xUKBUxNTdE6KQk6/10pmBqPUhCQO2pUk5r4rs1u/Xc5dOZbM5hvzWPONYv51izmW7OYb81rijl/XBvcvXsXJiYmNZ7HOaekpqKiAsXFxfjggw/Qp0+fpypMiYiIiIiI6ovFKanJyMhA//790blzZ3zxxRfP3N7FMWNq/esINYxbTfBly0RERERE9cHilNT4+vqCI72JiIiIiEjTuCASERERERERSY7FKREREREREUmOw3qpUTl88QVX69WAx6v1EhERERE9r9hzSkRERERERJJjcUpERERERESSY3HayNLS0iAIAu7cudPgbZ8/fx59+vSBgYEBunfvXuN5ycnJMDMza/D7ExERERERNZRmUZzeuHED//M//wNbW1vIZDK0bdsW/v7+yMjIaND7+Pr6IjQ0tEHbnDFjBnR1dbFr164qx6KiomBkZIS8vDykpqbW2EZAQAAuXLjQoHERERERERE1pGaxINLo0aNRXl6OzZs3o1OnTigsLERqaiqKi4ulDq1W9+/fx/bt2zF37lxs3LgRY8eOVTuen5+PwYMHw87OrsY2KioqYGhoCENDw8YOl4iIiIiI6Klpfc/pnTt3cOTIEcTHx6N///6ws7PDSy+9hIiICAwbNkx13pUrVzB8+HDI5XKYmJhg3LhxKCwsVB0PDg7GiBEj1NoODQ2Fr6+v6nh6ejpWrFgBQRAgCAIKCgpU52ZlZcHDwwMtW7ZE3759kZeX98TYd+3aBScnJ8ybNw+HDx/G1atXVccEQUBWVhZiYmIgCAKio6NRUFAAQRCwY8cO+Pj4wMDAAFu3bq12WO9XX32FXr16wcDAAK1atcLIkSNVxz799FN4eHjA2NgYbdu2xcSJE1FUVFSHbBMRERERET0dre85lcvlkMvl2Lt3L/r06QOZTFblHKVSqSpM09PT8fDhQ4SEhCAgIABpaWl1us+KFStw4cIFuLi4ICYmBgBgZWWlKlDff/99LFu2DFZWVnjrrbcwderUJw4rTkpKwqRJk2BqaopBgwYhOTkZkZGRAIBr165h4MCBePXVVxEeHg65XI6bN28CAObNm4dly5ahR48eMDAwwMGDB9Xa3b9/P0aOHIn3338fW7ZsQXl5Ob755hvV8YqKCixcuBBdunRBUVERwsLCEBwcrHbO35WVlaGsrEy1rVAoHuVWEABBqFMO6ekpBQG3KyqkDqPZYK41i/nWPOZcs5hvzWK+NYv51rymmHNFHWPS+uJUT08PycnJePPNN7F27Vq4u7vDx8cH48ePR7du3QAAqampOHv2LC5dugQbGxsAwJYtW+Ds7IzMzEz06tXrifcxNTWFvr4+WrZsibZt21Y5HhsbCx8fHwCPisfBgwfjzz//hIGBQbXtXbx4EcePH8fu3bsBAJMmTUJYWBg++OADCIKAtm3bQk9PD3K5XHW/x8VpaGgoRtXyzsvY2FiMHz8eCxYsUO1zc3NTfZ86darqe6dOnbBy5Ur06tULJSUlkMvl1ba5ePFitfaIiIiIiIjqQ+uLU+DRnNPBgwfjyJEjOH78OFJSUrBkyRJs2LABwcHByM3NhY2NjaowBQAnJyeYmZkhNze3TsXpkzwuhAHA2toaAFBUVARbW9tqz9+4cSP8/f3RqlUrAMBrr72GadOm4YcffsCAAQNqvZeHh0etx7Ozs/Hmm2/WeDwrKwvR0dHIycnB7du3oVQqATwa+uzk5FTtNREREQgLC1NtKxQK2NjYQEcUoSOKtcZDDcO8RQtYtGghdRjNCvOtWcy35jHnmsV8axbzrVnMt+Y1pZzr1TEWrZ9z+piBgQFefvllREZG4tixYwgODkZUVFSdr9fR0YH4tyKroh5d5i3+8gMR/jvM9XHR93eVlZXYvHkz9u/fDz09Pejp6aFly5a4desWNm7c+MR7GRkZ1Xq8tsWRSktL4e/vDxMTE2zduhWZmZnYs2cPAKC8vLzG62QyGUxMTNQ+REREREREddVsitO/c3JyQmlpKQDA0dERV69eVVtw6JdffsGdO3dUPYVWVla4du2aWhvZ2dlq2/r6+qisrHzm2L755hvcu3cPZ86cQXZ2turz+eefY/fu3c/8ztRu3brV+OqZ8+fPo7i4GHFxcejXrx+6du3KxZCIiIiIiKjRaX1xWlxcDD8/P3z22Wf46aefcOnSJezatQtLlizB8OHDAQADBw6Eq6srAgMDcfr0aZw8eRKvv/46fHx8VENk/fz8cOrUKWzZsgUXL15EVFQUzp07p3avDh064MSJEygoKMDNmzdr7Bl9kqSkJAwePBhubm5wcXFRfcaNGwczMzNs3br1mXISFRWFzz//HFFRUcjNzcXZs2cRHx8PALC1tYW+vj5WrVqF3377Dfv27cPChQuf6X5ERERERERPovXFqVwuR+/evfHRRx/B29sbLi4uiIyMxJtvvonVq1cDeDTM9t///jfMzc3h7e2NgQMHolOnTtixY4eqHX9/f0RGRmLu3Lno1asX7t27h9dff13tXuHh4dDV1YWTkxOsrKxw5cqVesdbWFiI/fv3Y/To0VWO6ejoYOTIkUhKSqp3u3/l6+uLXbt2Yd++fejevTv8/Pxw8uRJAI96iJOTk1WvsYmLi8PSpUuf6X5ERERERERPIoh/n0hJ1AAUCgVMTU3ROikJOi1bSh2O1lMKAnJHjWpSE9+12a3/zjdnvjWD+dY85lyzmG/NYr41i/nWvKaY88e1wd27d2tdm6ZZrNZL0rk4ZgwXR9KAW03wfVZERERERPWh9cN6iYiIiIiIqOljcUpERERERESSY3FKREREREREkuOcU2pUDl98wQWRNODxgkhERERERM8r9pwSERERERGR5FicEhERERERkeRYnDaw4OBgjBgxQrXt6+uL0NDQJhNPdaSOkYiIiIiISCvnnN64cQPz58/H/v37UVhYCHNzc7i5uWH+/Pnw8vLSaCy7d+9Gizq8APfBgwd44YUXoKOjg99//x0ymUwD0T1S1xiJiIiIiIgai1YWp6NHj0Z5eTk2b96MTp06obCwEKmpqSguLtZ4LBYWFnU678svv4SzszNEUcTevXsREBBQ6/kVFRUNVlDWNUYiIiIiIqLGonXDeu/cuYMjR44gPj4e/fv3h52dHV566SVERERg2LBhqvOWL18OV1dXGBkZwcbGBjNnzkRJSYnqeHR0NLp3767WdkJCAjp06KDarqysRFhYGMzMzGBpaYm5c+dCFEW1a+o6ZDYpKQmTJk3CpEmTkJSUVOW4IAj4+OOPMWzYMBgZGSE2NhaVlZWYNm0aOnbsCENDQ3Tp0gUrVqyotv0FCxbAysoKJiYmeOutt1BeXl5jjJ9++ik8PDxgbGyMtm3bYuLEiSgqKnriMxARERERET0tres5lcvlkMvl2Lt3L/r06VPj8FgdHR2sXLkSHTt2xG+//YaZM2di7ty5WLNmTZ3vtWzZMiQnJ2Pjxo1wdHTEsmXLsGfPHvj5+dUr5vz8fPz444/YvXs3RFHEO++8g8uXL8POzk7tvOjoaMTFxSEhIQF6enpQKpVo3749du3aBUtLSxw7dgzTp0+HtbU1xo0bp7ouNTUVBgYGSEtLQ0FBAaZMmQJLS0vExsZWG09FRQUWLlyILl26oKioCGFhYQgODsY333xT4zOUlZWhrKxMta1QKAA8esUJBKFe+aD6UwoCbldUSB1Gs8FcaxbzrXnMuWYx35rFfGsW8615TTHnijrGpHU9p3p6ekhOTsbmzZthZmYGLy8vvPfee/jpp5/UzgsNDUX//v3RoUMH+Pn54V//+hd27txZr3slJCQgIiICo0aNgqOjI9auXQtTU9N6x7xx40YMGjQI5ubmsLCwgL+/PzZt2lTlvIkTJ2LKlCno1KkTbG1t0aJFCyxYsAAeHh7o2LEjAgMDMWXKlCrPoa+vj40bN8LZ2RmDBw9GTEwMVq5cCaVSWW08U6dOxaBBg9CpUyf06dMHK1euREpKilrP8t8tXrwYpqamqo+NjU2980BERERERM2X1vWcAo/mnA4ePBhHjhzB8ePHkZKSgiVLlmDDhg0IDg4GAHz//fdYvHgxzp8/D4VCgYcPH+LPP//E/fv30bJlyyfe4+7du7h27Rp69+6t2qenpwcPD48qQ3trU1lZic2bN6sNx500aRLCw8Mxf/586Oj8/98PPDw8qlyfmJiIjRs34sqVK3jw4AHKy8urDEd2c3NTeyZPT0+UlJTg6tWrVXpnASArKwvR0dHIycnB7du3VUXslStX4OTkVO1zREREICwsTLWtUChgY2MDHVGETj3yQU/PvEULWHBhK41ivjWL+dY85lyzmG/NYr41i/nWvKaUc706xqJ1PaePGRgY4OWXX0ZkZCSOHTuG4OBgREVFAQAKCgowZMgQdOvWDV9++SWysrKQmJgIAKq5mDo6OlWKzIpG6CI/ePAgfv/9dwQEBEBPTw96enoYP348Ll++jNTUVLVzjYyM1La3b9+O8PBwTJs2Dd9++y2ys7MxZcoUtfmk9VVaWgp/f3+YmJhg69atyMzMxJ49ewCg1nZlMhlMTEzUPkRERERERHWltcXp3zk5OaG0tBTAo55BpVKJZcuWoU+fPujcuTP++OMPtfOtrKxw/fp1tQI1Oztb9d3U1BTW1tY4ceKEat/Dhw+RlZVVr7iSkpIwfvx4ZGdnq33Gjx9f7cJIf5WRkYG+ffti5syZ6NGjB+zt7ZGfn1/lvJycHDx48EC1ffz4ccjl8mqH3p4/fx7FxcWIi4tDv3790LVrVy6GREREREREjU7rhvUWFxdj7NixmDp1Krp16wZjY2OcOnUKS5YswfDhwwEA9vb2qKiowKpVqzB06FBkZGRg7dq1au34+vrixo0bWLJkCcaMGYMDBw4gJSVFrUdw9uzZiIuLg4ODA7p27Yrly5fjzp07dY71xo0b+Oqrr7Bv3z64uLioHXv99dcxcuRI3Lp1q8ZXvTg4OGDLli04ePAgOnbsiE8//RSZmZno2LGj2nnl5eWYNm0aPvjgAxQUFCAqKgqzZs1SGzL8mK2tLfT19bFq1Sq89dZbOHfuHBYuXFjnZyIiIiIiInoaWtdzKpfL0bt3b3z00Ufw9vaGi4sLIiMj8eabb2L16tUAHs3BXL58OeLj4+Hi4oKtW7di8eLFau04OjpizZo1SExMhJubG06ePInw8HC1c+bMmYPJkycjKCgInp6eMDY2xsiRI+sc65YtW2BkZIQBAwZUOTZgwAAYGhris88+q/H6GTNmYNSoUQgICEDv3r1RXFyMmTNnVtuWg4MDvL29ERAQgGHDhiE6OrraNq2srJCcnIxdu3bByckJcXFxWLp0aZ2fiYiIiIiI6GkIYn1W7yGqI4VCAVNTU7ROSoJOHRaYomejFATkjhrVpCa+a7Nb/51/znxrBvOtecy5ZjHfmsV8axbzrXlNMeePa4O7d+/WujaN1vWcEhERERER0fNH6+acUtNyccwYrtyrAbea4MuWiYiIiIjqgz2nREREREREJDkWp0RERERERCQ5DuulRuXwxRdcEEkDHi+IRERERET0vGLPKREREREREUmOxSkRERERERFJjsXpc6hDhw5ISEiQOgwiIiIiIqIGw+JUAoIg1PqJjo6u9frMzExMnz5dM8ESERERERFpABdEksC1a9dU33fs2IH58+cjLy9PtU8ul9d6vZWVVaPFRkREREREJAX2nEqgbdu2qo+pqSkEQVBtl5aWIjAwEG3atIFcLkevXr3w/fffq13/12G94eHhGDJkiOpYQkICBEHAgQMHVPvs7e2xYcMGAI96XV9++WW0atUKpqam8PHxwenTp9XaFwQBGzZswMiRI9GyZUs4ODhg3759jZQNIiIiIiIi9pw2OSUlJXjttdcQGxsLmUyGLVu2YOjQocjLy4OtrW2V8318fLBhwwZUVlZCV1cX6enpaNWqFdLS0vDqq6/i999/R35+Pnx9fQEA9+7dQ1BQEFatWgVRFLFs2TK89tpruHjxIoyNjVXtLliwAEuWLMGHH36IVatWITAwEJcvX4aFhUW1cZeVlaGsrEy1rVAoADx6xQkEoQEzRNVRCgJuV1RIHUazwVxrFvOtecy5ZjHfmsV8axbzrXlNMeeKOsbEntMmxs3NDTNmzICLiwscHBywcOFCvPjiizX2XPbr1w/37t3DmTNnIIoiDh8+jDlz5iAtLQ0AkJaWhhdeeAH29vYAAD8/P0yaNAldu3aFo6Mj1q1bh/v37yM9PV2t3eDgYEyYMAH29vZYtGgRSkpKcPLkyRrjXrx4MUxNTVUfGxubhkkIERERERE1C+w5bWJKSkoQHR2N/fv349q1a3j48CEePHiAK1euVHu+mZkZ3NzckJaWBn19fejr62P69OmIiopCSUkJ0tPT4ePjozq/sLAQH3zwAdLS0lBUVITKykrcv3+/SvvdunVTfTcyMoKJiQmKiopqjDsiIgJhYWGqbYVCARsbG+iIInRE8WnTQfVg3qIFLFq0kDqMZoX51izmW/OYc81ivjWL+dYs5lvzmlLO9eoYC4vTJiY8PBzfffcdli5dCnt7exgaGmLMmDEoLy+v8RpfX1+kpaVBJpPBx8cHFhYWcHR0xNGjR5Geno45c+aozg0KCkJxcTFWrFgBOzs7yGQyeHp6Vmm/xd9+gQRBgFKprDEGmUwGmUz2lE9NRERERETNHYvTJiYjIwPBwcEYOXIkgEc9qQUFBbVe4+Pjg40bN0JPTw+vvvoqgEcF6+eff44LFy6o5ps+bn/NmjV47bXXAABXr17FzZs3G+VZiIiIiIiI6opzTpsYBwcH7N69G9nZ2cjJycHEiRNr7bEEAG9vb9y7dw9ff/21qhD19fXF1q1bYW1tjc6dO6u1/+mnnyI3NxcnTpxAYGAgDA0NG/ORiIiIiIiInojFaROzfPlymJubo2/fvhg6dCj8/f3h7u5e6zXm5uZwdXWFlZUVunbtCuBRwapUKtXmmwJAUlISbt++DXd3d0yePBlvv/02Wrdu3WjPQ0REREREVBeCKHK1Gmp4CoUCpqamaJ2UBJ2WLaUOR+spBQG5o0Y1qYnv2uzWf5dDZ741g/nWPOZcs5hvzWK+NYv51rymmPPHtcHdu3dhYmJS43nsOSUiIiIiIiLJcUEkalQXx4yp9a8j1DBuNcGXLRMRERER1QeLU2oUj0eLKxQKiSNpHhT/LU7r+g4pejbMt2Yx35rHnGsW861ZzLdmMd+a1xRz/rgmeNKMUhan1CiKi4sBADY2NhJHQkRERERETcG9e/dgampa43EWp9QoLCwsAABXrlyp9ReQGoZCoYCNjQ2uXr3KYdQawHxrFvOtecy5ZjHfmsV8axbzrXlNMeeiKOLevXto165dreexOKVGoaPzaK0tU1PTJvMfRXNgYmLCfGsQ861ZzLfmMeeaxXxrFvOtWcy35jW1nNelw4qr9RIREREREZHkWJwSERERERGR5FicUqOQyWSIioqCTCaTOpRmgfnWLOZbs5hvzWPONYv51izmW7OYb817nnMuiE9az5eIiIiIiIiokbHnlIiIiIiIiCTH4pSIiIiIiIgkx+KUiIiIiIiIJMfilIiIiIiIiCTH4pQaXGJiIjp06AADAwP07t0bJ0+elDokrXX48GEMHToU7dq1gyAI2Lt3r9QhabXFixejV69eMDY2RuvWrTFixAjk5eVJHZbW+vjjj9GtWzfVS8Q9PT2RkpIidVjNRlxcHARBQGhoqNShaK3o6GgIgqD26dq1q9RhabXff/8dkyZNgqWlJQwNDeHq6opTp05JHZZW6tChQ5Xfb0EQEBISInVoWqmyshKRkZHo2LEjDA0N8eKLL2LhwoV43ta+ZXFKDWrHjh0ICwtDVFQUTp8+DTc3N/j7+6OoqEjq0LRSaWkp3NzckJiYKHUozUJ6ejpCQkJw/PhxfPfdd6ioqMArr7yC0tJSqUPTSu3bt0dcXByysrJw6tQp+Pn5Yfjw4fj555+lDk3rZWZm4pNPPkG3bt2kDkXrOTs749q1a6rP0aNHpQ5Ja92+fRteXl5o0aIFUlJS8Msvv2DZsmUwNzeXOjStlJmZqfa7/d133wEAxo4dK3Fk2ik+Ph4ff/wxVq9ejdzcXMTHx2PJkiVYtWqV1KHVC18lQw2qd+/e6NWrF1avXg0AUCqVsLGxwT//+U/MmzdP4ui0myAI2LNnD0aMGCF1KM3GjRs30Lp1a6Snp8Pb21vqcJoFCwsLfPjhh5g2bZrUoWitkpISuLu7Y82aNfjXv/6F7t27IyEhQeqwtFJ0dDT27t2L7OxsqUNpFubNm4eMjAwcOXJE6lCapdDQUHz99de4ePEiBEGQOhytM2TIELRp0wZJSUmqfaNHj4ahoSE+++wzCSOrH/acUoMpLy9HVlYWBg4cqNqno6ODgQMH4scff5QwMqLGcffuXQCPCiZqXJWVldi+fTtKS0vh6ekpdThaLSQkBIMHD1b7fzk1nosXL6Jdu3bo1KkTAgMDceXKFalD0lr79u2Dh4cHxo4di9atW6NHjx5Yv3691GE1C+Xl5fjss88wdepUFqaNpG/fvkhNTcWFCxcAADk5OTh69CgGDRokcWT1oyd1AKQ9bt68icrKSrRp00Ztf5s2bXD+/HmJoiJqHEqlEqGhofDy8oKLi4vU4Wits2fPwtPTE3/++Sfkcjn27NkDJycnqcPSWtu3b8fp06eRmZkpdSjNQu/evZGcnIwuXbrg2rVrWLBgAfr164dz587B2NhY6vC0zm+//YaPP/4YYWFheO+995CZmYm3334b+vr6CAoKkjo8rbZ3717cuXMHwcHBUoeitebNmweFQoGuXbtCV1cXlZWViI2NRWBgoNSh1QuLUyKipxASEoJz585xflgj69KlC7Kzs3H37l188cUXCAoKQnp6OgvURnD16lXMnj0b3333HQwMDKQOp1n4a49Gt27d0Lt3b9jZ2WHnzp0cut4IlEolPDw8sGjRIgBAjx49cO7cOaxdu5bFaSNLSkrCoEGD0K5dO6lD0Vo7d+7E1q1bsW3bNjg7OyM7OxuhoaFo167dc/X7zeKUGkyrVq2gq6uLwsJCtf2FhYVo27atRFERNbxZs2bh66+/xuHDh9G+fXupw9Fq+vr6sLe3BwD07NkTmZmZWLFiBT755BOJI9M+WVlZKCoqgru7u2pfZWUlDh8+jNWrV6OsrAy6uroSRqj9zMzM0LlzZ/z6669Sh6KVrK2tq/xhy9HREV9++aVEETUPly9fxvfff4/du3dLHYpWe/fddzFv3jyMHz8eAODq6orLly9j8eLFz1Vxyjmn1GD09fXRs2dPpKamqvYplUqkpqZyjhhpBVEUMWvWLOzZswc//PADOnbsKHVIzY5SqURZWZnUYWilAQMG4OzZs8jOzlZ9PDw8EBgYiOzsbBamGlBSUoL8/HxYW1tLHYpW8vLyqvL6rwsXLsDOzk6iiJqHTZs2oXXr1hg8eLDUoWi1+/fvQ0dHvbTT1dWFUqmUKKKnw55TalBhYWEICgqCh4cHXnrpJSQkJKC0tBRTpkyROjStVFJSovYX9kuXLiE7OxsWFhawtbWVMDLtFBISgm3btuHf//43jI2Ncf36dQCAqakpDA0NJY5O+0RERGDQoEGwtbXFvXv3sG3bNqSlpeHgwYNSh6aVjI2Nq8yfNjIygqWlJedVN5Lw8HAMHToUdnZ2+OOPPxAVFQVdXV1MmDBB6tC00jvvvIO+ffti0aJFGDduHE6ePIl169Zh3bp1UoemtZRKJTZt2oSgoCDo6bHsaExDhw5FbGwsbG1t4ezsjDNnzmD58uWYOnWq1KHVj0jUwFatWiXa2tqK+vr64ksvvSQeP35c6pC01qFDh0QAVT5BQUFSh6aVqss1AHHTpk1Sh6aVpk6dKtrZ2Yn6+vqilZWVOGDAAPHbb7+VOqxmxcfHR5w9e7bUYWitgIAA0draWtTX1xdfeOEFMSAgQPz111+lDkurffXVV6KLi4sok8nErl27iuvWrZM6JK128OBBEYCYl5cndShaT6FQiLNnzxZtbW1FAwMDsVOnTuL7778vlpWVSR1avfA9p0RERERERCQ5zjklIiIiIiIiybE4JSIiIiIiIsmxOCUiIiIiIiLJsTglIiIiIiIiybE4JSIiIiIiIsmxOCUiIiIiIiLJsTglIiIiIiIiybE4JSIiIiIiIsmxOCUiInqOFBQUQBAEZGdnSx2Kyvnz59GnTx8YGBige/fuUocjiQ4dOiAhIUHqMIiInmssTomIiOohODgYgiAgLi5Obf/evXshCIJEUUkrKioKRkZGyMvLQ2pqqtThSCIzMxPTp0+XOgwioucai1MiIqJ6MjAwQHx8PG7fvi11KA2mvLz8qa/Nz8/HP/7xD9jZ2cHS0rIBo3p+WFlZoWXLllKHQUT0XGNxSkREVE8DBw5E27ZtsXjx4hrPiY6OrjLENSEhAR06dFBtBwcHY8SIEVi0aBHatGkDMzMzxMTE4OHDh3j33XdhYWGB9u3bY9OmTVXaP3/+PPr27QsDAwO4uLggPT1d7fi5c+cwaNAgyOVytGnTBpMnT8bNmzdVx319fTFr1iyEhoaiVatW8Pf3r/Y5lEolYmJi0L59e8hkMnTv3h0HDhxQHRcEAVlZWYiJiYEgCIiOjq6xnSVLlsDe3h4ymQy2traIjY1VHT979iz8/PxgaGgIS0tLTJ8+HSUlJc+Uq8dDoLdv315jriorKzFt2jR07NgRhoaG6NKlC1asWKEW++N7L126FNbW1rC0tERISAgqKipU5/x9WO+dO3fwxhtvwMrKCiYmJvDz80NOTo7qeE5ODvr37w9jY2OYmJigZ8+eOHXqVLW5IyJqLlicEhER1ZOuri4WLVqEVatW4T//+c8ztfXDDz/gjz/+wOHDh7F8+XJERUVhyJAhMDc3x4kTJ/DWW29hxowZVe7z7rvvYs6cOThz5gw8PT0xdOhQFBcXA3hUGPn5+aFHjx44deoUDhw4gMLCQowbN06tjc2bN0NfXx8ZGRlYu3ZttfGtWLECy5Ytw9KlS/HTTz/B398fw4YNw8WLFwEA165dg7OzM+bMmYNr164hPDy82nYiIiIQFxeHyMhI/PLLL9i2bRvatGkDACgtLYW/vz/Mzc2RmZmJXbt24fvvv8esWbMaPVdKpRLt27fHrl278Msvv2D+/Pl47733sHPnTrU2Dh06hPz8fBw6dAibN29GcnIykpOTa/qxYuzYsSgqKkJKSgqysrLg7u6OAQMG4NatWwCAwMBAtG/fHpmZmcjKysK8efPQokWLGtsjImoWRCIiIqqzoKAgcfjw4aIoimKfPn3EqVOniqIoinv27BH/+s9qVFSU6ObmpnbtRx99JNrZ2am1ZWdnJ1ZWVqr2denSRezXr59q++HDh6KRkZH4+eefi6IoipcuXRIBiHFxcapzKioqxPbt24vx8fGiKIriwoULxVdeeUXt3levXhUBiHl5eaIoiqKPj4/Yo0ePJz5vu3btxNjYWLV9vXr1EmfOnKnadnNzE6OiompsQ6FQiDKZTFy/fn21x9etWyeam5uLJSUlqn379+8XdXR0xOvXr4ui2Hi5qk5ISIg4evRo1fbjez98+FC1b+zYsWJAQIBq287OTvzoo49EURTFI0eOiCYmJuKff/6p1u6LL74ofvLJJ6IoiqKxsbGYnJxcYwxERM0Re06JiIieUnx8PDZv3ozc3NynbsPZ2Rk6Ov//z3GbNm3g6uqq2tbV1YWlpSWKiorUrvP09FR919PTg4eHhyqOnJwcHDp0CHK5XPXp2rUrgEfzQx/r2bNnrbEpFAr88ccf8PLyUtvv5eVVr2fOzc1FWVkZBgwYUONxNzc3GBkZqd1DqVQiLy9Pta8xcgUAiYmJ6NmzJ6ysrCCXy7Fu3TpcuXJFrQ1nZ2fo6uqqtq2travc57GcnByUlJTA0tJS7Wdw6dIlVf7DwsLwxhtvYODAgYiLi1P7uRARNVd6UgdARET0vPL29oa/vz8iIiIQHBysdkxHRweiKKrt++scxcf+PpRTEIRq9ymVyjrHVVJSgqFDhyI+Pr7KMWtra9X3vxaDjcnQ0LBB2mmMXG3fvh3h4eFYtmwZPD09YWxsjA8//BAnTpx44r1ruk9JSQmsra2RlpZW5ZiZmRmAR3OSJ06ciP379yMlJQVRUVHYvn07Ro4cWefYiYi0DXtOiYiInkFcXBy++uor/Pjjj2r7rayscP36dbUCtSHfTXr8+HHV94cPHyIrKwuOjo4AAHd3d/z888/o0KED7O3t1T71KUhNTEzQrl07ZGRkqO3PyMiAk5NTndtxcHCAoaFhja+ZcXR0RE5ODkpLS9XuoaOjgy5dutT5PjWpLVcZGRno27cvZs6ciR49esDe3v6ZezHd3d1x/fp16OnpVcl/q1atVOd17twZ77zzDr799luMGjWq2oWviIiaExanREREz8DV1RWBgYFYuXKl2n5fX1/cuHEDS5YsQX5+PhITE5GSktJg901MTMSePXtw/vx5hISE4Pbt25g6dSoAICQkBLdu3cKECROQmZmJ/Px8HDx4EFOmTEFlZWW97vPuu+8iPj4eO3bsQF5eHubNm4fs7GzMnj27zm0YGBjgf//3fzF37lxs2bIF+fn5OH78OJKSkgA8WhzIwMAAQUFBOHfuHA4dOoR//vOfmDx5smrRpGdRW64cHBxw6tQpHDx4EBcuXEBkZCQyMzOf6X4DBw6Ep6cnRowYgW+//RYFBQU4duwY3n//fZw6dQoPHjzArFmzkJaWhsuXLyMjIwOZmZmqgpmIqLlicUpERPSMYmJiqgzxdHR0xJo1a5CYmAg3NzecPHmyxpVsn0ZcXBzi4uLg5uaGo0ePYt++fapeuce9nZWVlXjllVfg6uqK0NBQmJmZqc3ZrIu3334bYWFhmDNnDlxdXXHgwAHs27cPDg4O9WonMjISc+bMwfz58+Ho6IiAgADVnM2WLVvi4MGDuHXrFnr16oUxY8ZgwIABWL16db3uUZPacjVjxgyMGjUKAQEB6N27N4qLizFz5sxnup8gCPjmm2/g7e2NKVOmoHPnzhg/fjwuX76MNm3aQFdXF8XFxXj99dfRuXNnjBs3DoMGDcKCBQsa4nGJiJ5bgvj3CTFEREREWqCgoAAdO3bEmTNnqrxzloiImh72nBIREREREZHkWJwSERERERGR5Disl4iIiIiIiCTHnlMiIiIiIiKSHItTIiIiIiIikhyLUyIiIiIiIpIci1MiIiIiIiKSHItTIiIiIiIikhyLUyIiIiIiIpIci1MiIiIiIiKSHItTIiIiIiIiktz/AawSUzVkZltPAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "companies_worldwide_graph = plt.figure(figsize = (10, 5))\n",
    "sns.barplot(data = countries_df, y = \"Country\", x = \"Company\", color = \"c\")\n",
    "plt.grid(color = \"c\", linestyle = \"-\", linewidth = 0.1)\n",
    "plt.xlabel(\"Number of companies\")\n",
    "plt.ylabel(\"Company\")\n",
    "plt.title(\"Distribution of the most sucessful chemical companies by country\", size = 12)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Top best-selling German chemical companies in 2021\n",
    "The German chemical companies that perform the best in the year 2021 were:\n",
    "* BASF\n",
    "* Covestro\n",
    "* Evonik Industries\n",
    "* Bayer\n",
    "* Lanxess"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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>Rank</th>\n",
       "      <th>Company</th>\n",
       "      <th>Sales in 2021 in USD millions</th>\n",
       "      <th>Growth in 2021 in %</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>BASF</td>\n",
       "      <td>92982</td>\n",
       "      <td>32.9</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>Covestro</td>\n",
       "      <td>18813</td>\n",
       "      <td>48.5</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>Evonik Industries</td>\n",
       "      <td>17692</td>\n",
       "      <td>22.6</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>Bayer</td>\n",
       "      <td>12743</td>\n",
       "      <td>9.7</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>49</td>\n",
       "      <td>Lanxess</td>\n",
       "      <td>8940</td>\n",
       "      <td>23.8</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Rank            Company  Sales in 2021 in USD millions  \\\n",
       "0      1               BASF                          92982   \n",
       "20    21           Covestro                          18813   \n",
       "22    23  Evonik Industries                          17692   \n",
       "33    34              Bayer                          12743   \n",
       "48    49            Lanxess                           8940   \n",
       "\n",
       "    Growth in 2021 in %  Country  \n",
       "0                  32.9  Germany  \n",
       "20                 48.5  Germany  \n",
       "22                 22.6  Germany  \n",
       "33                  9.7  Germany  \n",
       "48                 23.8  Germany  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "germany"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Top best-selling German chemical companies in 2021')"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "german_companies_by_sale_graph = plt.figure(figsize = (10, 5))\n",
    "sns.barplot(data = germany, x = \"Company\", y = \"Sales in 2021 in USD millions\", color = \"deeppink\")\n",
    "plt.grid(color = \"deeppink\", linestyle = \"-\", linewidth = 0.1)\n",
    "plt.xlabel(\"Company\")\n",
    "plt.ylabel(\"Sales USD millions\")\n",
    "plt.title(\"Top best-selling German chemical companies in 2021\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Top fastest growing German chemical companies in 2021\n",
    "The German chemical producing companies that grew the most in the year 2021 were:\n",
    "* Covestro\n",
    "* BASF\n",
    "* Lanxess\n",
    "* Evonik Induestries\n",
    "* Bayer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "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>Rank</th>\n",
       "      <th>Company</th>\n",
       "      <th>Sales in 2021 in USD millions</th>\n",
       "      <th>Growth in 2021 in %</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>Covestro</td>\n",
       "      <td>18813</td>\n",
       "      <td>48.5</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>BASF</td>\n",
       "      <td>92982</td>\n",
       "      <td>32.9</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>49</td>\n",
       "      <td>Lanxess</td>\n",
       "      <td>8940</td>\n",
       "      <td>23.8</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>Evonik Industries</td>\n",
       "      <td>17692</td>\n",
       "      <td>22.6</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>Bayer</td>\n",
       "      <td>12743</td>\n",
       "      <td>9.7</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Rank            Company  Sales in 2021 in USD millions  \\\n",
       "20    21           Covestro                          18813   \n",
       "0      1               BASF                          92982   \n",
       "48    49            Lanxess                           8940   \n",
       "22    23  Evonik Industries                          17692   \n",
       "33    34              Bayer                          12743   \n",
       "\n",
       "    Growth in 2021 in %  Country  \n",
       "20                 48.5  Germany  \n",
       "0                  32.9  Germany  \n",
       "48                 23.8  Germany  \n",
       "22                 22.6  Germany  \n",
       "33                  9.7  Germany  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "germany_growth_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "german_companies_by_growth_graph = plt.figure(figsize = (10, 5))\n",
    "ax = sns.barplot(data = germany_growth_df, x = \"Company\", y = \"Growth in 2021 in %\", palette = \"RdPu_r\", hue = \"Company\")\n",
    "plt.grid(color = \"deeppink\", linestyle = \"-\", linewidth = 0.1)\n",
    "plt.xlabel(\"Company\")\n",
    "plt.ylabel(\"Growth in %\")\n",
    "plt.title(\"Top fastest growing German chemical companies in 2021\")\n",
    "for i in ax.containers:\n",
    "    ax.bar_label(i,)"
   ]
  }
 ],
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  "kernelspec": {
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