Daily Task 3 & 4 - query function & list comprehension.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4dd0dee9",
   "metadata": {},
   "source": [
    "## Daily Task 3 - Query Function of data_frame"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "511a302e",
   "metadata": {},
   "source": [
    "### Example - 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "33393248",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b400dff6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       Name  Age Company      Designation  Salary\n",
      "0     Pooja   28    Govt              IPS  120000\n",
      "1  Vrushali   29    Infy   Data Scientist   90000\n",
      "2     Karan   30     L&T  Senior Engineer   80000\n",
      "3      Mona   25  Google          Trainee  350000\n",
      "4     Divya   27  Sports          Caption  150000\n",
      "5    Yogesh   29     IBM       HR Manager   60000\n"
     ]
    }
   ],
   "source": [
    "info = { \"Name\" : ['Pooja','Vrushali','Karan','Mona','Divya','Yogesh'],\n",
    "         \"Age\" : [28,29,30,25,27,29],\n",
    "         \"Company\" : ['Govt','Infy','L&T','Google','Sports','IBM'],\n",
    "         \"Designation\" : ['IPS','Data Scientist','Senior Engineer','Trainee','Caption','HR Manager'],\n",
    "         \"Salary\" : [120000,90000,80000,350000,150000,60000]\n",
    "    }\n",
    "\n",
    "employees = pd.DataFrame(info)\n",
    "print(employees)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6807b9bc",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Age</th>\n",
       "      <th>Company</th>\n",
       "      <th>Designation</th>\n",
       "      <th>Salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Pooja</td>\n",
       "      <td>28</td>\n",
       "      <td>Govt</td>\n",
       "      <td>IPS</td>\n",
       "      <td>120000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Vrushali</td>\n",
       "      <td>29</td>\n",
       "      <td>Infy</td>\n",
       "      <td>Data Scientist</td>\n",
       "      <td>90000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Mona</td>\n",
       "      <td>25</td>\n",
       "      <td>Google</td>\n",
       "      <td>Trainee</td>\n",
       "      <td>350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Divya</td>\n",
       "      <td>27</td>\n",
       "      <td>Sports</td>\n",
       "      <td>Caption</td>\n",
       "      <td>150000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Name  Age Company     Designation  Salary\n",
       "0     Pooja   28    Govt             IPS  120000\n",
       "1  Vrushali   29    Infy  Data Scientist   90000\n",
       "3      Mona   25  Google         Trainee  350000\n",
       "4     Divya   27  Sports         Caption  150000"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "employees.query('Salary > 80000')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "46c39365",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Age</th>\n",
       "      <th>Company</th>\n",
       "      <th>Designation</th>\n",
       "      <th>Salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Vrushali</td>\n",
       "      <td>29</td>\n",
       "      <td>Infy</td>\n",
       "      <td>Data Scientist</td>\n",
       "      <td>90000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Yogesh</td>\n",
       "      <td>29</td>\n",
       "      <td>IBM</td>\n",
       "      <td>HR Manager</td>\n",
       "      <td>60000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Name  Age Company     Designation  Salary\n",
       "1  Vrushali   29    Infy  Data Scientist   90000\n",
       "5    Yogesh   29     IBM      HR Manager   60000"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "employees.query('Age == 29')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d287f89",
   "metadata": {},
   "source": [
    "### Example -2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6c885a5a",
   "metadata": {},
   "outputs": [
    {
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       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>smoker</th>\n",
       "      <th>region</th>\n",
       "      <th>charges</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>19</td>\n",
       "      <td>female</td>\n",
       "      <td>27.900</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>16884.92400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>33.770</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1725.55230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>28</td>\n",
       "      <td>male</td>\n",
       "      <td>33.000</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>4449.46200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>33</td>\n",
       "      <td>male</td>\n",
       "      <td>22.705</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>21984.47061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>32</td>\n",
       "      <td>male</td>\n",
       "      <td>28.880</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>3866.85520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>1333</th>\n",
       "      <td>50</td>\n",
       "      <td>male</td>\n",
       "      <td>30.970</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>10600.54830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1334</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>31.920</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2205.98080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1335</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>36.850</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1629.83350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1336</th>\n",
       "      <td>21</td>\n",
       "      <td>female</td>\n",
       "      <td>25.800</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>2007.94500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1337</th>\n",
       "      <td>61</td>\n",
       "      <td>female</td>\n",
       "      <td>29.070</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>northwest</td>\n",
       "      <td>29141.36030</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1338 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      age     sex     bmi  children smoker     region      charges\n",
       "0      19  female  27.900         0    yes  southwest  16884.92400\n",
       "1      18    male  33.770         1     no  southeast   1725.55230\n",
       "2      28    male  33.000         3     no  southeast   4449.46200\n",
       "3      33    male  22.705         0     no  northwest  21984.47061\n",
       "4      32    male  28.880         0     no  northwest   3866.85520\n",
       "...   ...     ...     ...       ...    ...        ...          ...\n",
       "1333   50    male  30.970         3     no  northwest  10600.54830\n",
       "1334   18  female  31.920         0     no  northeast   2205.98080\n",
       "1335   18  female  36.850         0     no  southeast   1629.83350\n",
       "1336   21  female  25.800         0     no  southwest   2007.94500\n",
       "1337   61  female  29.070         0    yes  northwest  29141.36030\n",
       "\n",
       "[1338 rows x 7 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "insurance_data = pd.read_csv('E:\\Data Science by John\\pandas\\insurance.csv')\n",
    "insurance_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "cb10ac36",
   "metadata": {},
   "outputs": [
    {
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       "      <td>27.900</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>16884.92400</td>\n",
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       "      <th>1</th>\n",
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       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
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       "      <th>2</th>\n",
       "      <td>28</td>\n",
       "      <td>male</td>\n",
       "      <td>33.000</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>4449.46200</td>\n",
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       "    <tr>\n",
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       "      <td>male</td>\n",
       "      <td>28.880</td>\n",
       "      <td>0</td>\n",
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       "      <td>northwest</td>\n",
       "      <td>3866.85520</td>\n",
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       "      <th>5</th>\n",
       "      <td>31</td>\n",
       "      <td>female</td>\n",
       "      <td>25.740</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>3756.62160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>46</td>\n",
       "      <td>female</td>\n",
       "      <td>33.440</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>8240.58960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>37</td>\n",
       "      <td>female</td>\n",
       "      <td>27.740</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>7281.50560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>37</td>\n",
       "      <td>male</td>\n",
       "      <td>29.830</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>6406.41070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>60</td>\n",
       "      <td>female</td>\n",
       "      <td>25.840</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>28923.13692</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "   age     sex     bmi  children smoker     region      charges\n",
       "0   19  female  27.900         0    yes  southwest  16884.92400\n",
       "1   18    male  33.770         1     no  southeast   1725.55230\n",
       "2   28    male  33.000         3     no  southeast   4449.46200\n",
       "3   33    male  22.705         0     no  northwest  21984.47061\n",
       "4   32    male  28.880         0     no  northwest   3866.85520\n",
       "5   31  female  25.740         0     no  southeast   3756.62160\n",
       "6   46  female  33.440         1     no  southeast   8240.58960\n",
       "7   37  female  27.740         3     no  northwest   7281.50560\n",
       "8   37    male  29.830         2     no  northeast   6406.41070\n",
       "9   60  female  25.840         0     no  northwest  28923.13692"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "insurance_data.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c0d0ba35",
   "metadata": {},
   "outputs": [
    {
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       "      <th>charges</th>\n",
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       "      <th>3</th>\n",
       "      <td>33</td>\n",
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       "      <td>22.705</td>\n",
       "      <td>0</td>\n",
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       "      <th>4</th>\n",
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       "      <th>5</th>\n",
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       "      <td>southeast</td>\n",
       "      <td>3756.62160</td>\n",
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       "      <th>6</th>\n",
       "      <td>46</td>\n",
       "      <td>female</td>\n",
       "      <td>33.440</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>8240.58960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>37</td>\n",
       "      <td>female</td>\n",
       "      <td>27.740</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>7281.50560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1329</th>\n",
       "      <td>52</td>\n",
       "      <td>male</td>\n",
       "      <td>38.600</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>10325.20600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1330</th>\n",
       "      <td>57</td>\n",
       "      <td>female</td>\n",
       "      <td>25.740</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>12629.16560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1332</th>\n",
       "      <td>52</td>\n",
       "      <td>female</td>\n",
       "      <td>44.700</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>11411.68500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1333</th>\n",
       "      <td>50</td>\n",
       "      <td>male</td>\n",
       "      <td>30.970</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>10600.54830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1337</th>\n",
       "      <td>61</td>\n",
       "      <td>female</td>\n",
       "      <td>29.070</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>northwest</td>\n",
       "      <td>29141.36030</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>894 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      age     sex     bmi  children smoker     region      charges\n",
       "3      33    male  22.705         0     no  northwest  21984.47061\n",
       "4      32    male  28.880         0     no  northwest   3866.85520\n",
       "5      31  female  25.740         0     no  southeast   3756.62160\n",
       "6      46  female  33.440         1     no  southeast   8240.58960\n",
       "7      37  female  27.740         3     no  northwest   7281.50560\n",
       "...   ...     ...     ...       ...    ...        ...          ...\n",
       "1329   52    male  38.600         2     no  southwest  10325.20600\n",
       "1330   57  female  25.740         2     no  southeast  12629.16560\n",
       "1332   52  female  44.700         3     no  southwest  11411.68500\n",
       "1333   50    male  30.970         3     no  northwest  10600.54830\n",
       "1337   61  female  29.070         0    yes  northwest  29141.36030\n",
       "\n",
       "[894 rows x 7 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "insurance_data.query('age > 30')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "da6fccae",
   "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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>smoker</th>\n",
       "      <th>region</th>\n",
       "      <th>charges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>37</td>\n",
       "      <td>male</td>\n",
       "      <td>29.830</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>6406.41070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>37</td>\n",
       "      <td>male</td>\n",
       "      <td>28.025</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>6203.90175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>55</td>\n",
       "      <td>female</td>\n",
       "      <td>32.775</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>12268.63225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>31</td>\n",
       "      <td>male</td>\n",
       "      <td>36.300</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>38711.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>31</td>\n",
       "      <td>female</td>\n",
       "      <td>36.630</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>4949.75870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1319</th>\n",
       "      <td>39</td>\n",
       "      <td>female</td>\n",
       "      <td>26.315</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>7201.70085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1323</th>\n",
       "      <td>42</td>\n",
       "      <td>female</td>\n",
       "      <td>40.370</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>43896.37630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1328</th>\n",
       "      <td>23</td>\n",
       "      <td>female</td>\n",
       "      <td>24.225</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>22395.74424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1329</th>\n",
       "      <td>52</td>\n",
       "      <td>male</td>\n",
       "      <td>38.600</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>10325.20600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1330</th>\n",
       "      <td>57</td>\n",
       "      <td>female</td>\n",
       "      <td>25.740</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>12629.16560</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>240 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      age     sex     bmi  children smoker     region      charges\n",
       "8      37    male  29.830         2     no  northeast   6406.41070\n",
       "24     37    male  28.025         2     no  northwest   6203.90175\n",
       "27     55  female  32.775         2     no  northwest  12268.63225\n",
       "29     31    male  36.300         2    yes  southwest  38711.00000\n",
       "41     31  female  36.630         2     no  southeast   4949.75870\n",
       "...   ...     ...     ...       ...    ...        ...          ...\n",
       "1319   39  female  26.315         2     no  northwest   7201.70085\n",
       "1323   42  female  40.370         2    yes  southeast  43896.37630\n",
       "1328   23  female  24.225         2     no  northeast  22395.74424\n",
       "1329   52    male  38.600         2     no  southwest  10325.20600\n",
       "1330   57  female  25.740         2     no  southeast  12629.16560\n",
       "\n",
       "[240 rows x 7 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "insurance_data.query('children == 2')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0f00e12",
   "metadata": {},
   "source": [
    "### =========================================================================="
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26ba2145",
   "metadata": {},
   "source": [
    "## Daily Task 4 - List Comprehension\n",
    "### syntax for list comprehension : [expression for item in list]\n",
    "### e.g  [expression for item in list] as [[x for x in fruits]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e710d49",
   "metadata": {},
   "source": [
    "### Example - 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "caab3dfc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[13, 16, 19, 22, 25, 28]]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nums =[]\n",
    "values = [i for i in range(1,30,3) if i>10]\n",
    "nums = [values]\n",
    "nums"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "69873f85",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[13, 16, 19, 22, 25, 28], 31]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nums.append(31)\n",
    "nums"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99b8d860",
   "metadata": {},
   "source": [
    "### Exapmle - 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "cd02030d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['apple', 'banana', 'mango']\n"
     ]
    }
   ],
   "source": [
    "fruits = [\"apple\", \"banana\", \"cherry\", \"kiwi\", \"mango\"]\n",
    "req_fruits = [x for x in fruits if \"a\" in x]\n",
    "\n",
    "print(req_fruits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "4b7dde3b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['banana', 'mango']"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "req_fruits_1 = [f for f in fruits if 'n' in f]\n",
    "req_fruits_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "25f6daca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2000, 2004, 2008]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "years = [2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010]\n",
    "leap_year = [y for y in years if y%4 ==0]\n",
    "leap_year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5e44c5bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2005, 2006, 2007, 2008, 2009, 2010]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[y for y in years if y>=2005]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f348a62f",
   "metadata": {},
   "source": [
    "### Example - 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "bde1cfdb",
   "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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>smoker</th>\n",
       "      <th>region</th>\n",
       "      <th>charges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19</td>\n",
       "      <td>female</td>\n",
       "      <td>27.900</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>16884.92400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>33.770</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1725.55230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>28</td>\n",
       "      <td>male</td>\n",
       "      <td>33.000</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>4449.46200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>33</td>\n",
       "      <td>male</td>\n",
       "      <td>22.705</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>21984.47061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>32</td>\n",
       "      <td>male</td>\n",
       "      <td>28.880</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>3866.85520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1333</th>\n",
       "      <td>50</td>\n",
       "      <td>male</td>\n",
       "      <td>30.970</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>10600.54830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1334</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>31.920</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2205.98080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1335</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>36.850</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1629.83350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1336</th>\n",
       "      <td>21</td>\n",
       "      <td>female</td>\n",
       "      <td>25.800</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>2007.94500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1337</th>\n",
       "      <td>61</td>\n",
       "      <td>female</td>\n",
       "      <td>29.070</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>northwest</td>\n",
       "      <td>29141.36030</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1338 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      age     sex     bmi  children smoker     region      charges\n",
       "0      19  female  27.900         0    yes  southwest  16884.92400\n",
       "1      18    male  33.770         1     no  southeast   1725.55230\n",
       "2      28    male  33.000         3     no  southeast   4449.46200\n",
       "3      33    male  22.705         0     no  northwest  21984.47061\n",
       "4      32    male  28.880         0     no  northwest   3866.85520\n",
       "...   ...     ...     ...       ...    ...        ...          ...\n",
       "1333   50    male  30.970         3     no  northwest  10600.54830\n",
       "1334   18  female  31.920         0     no  northeast   2205.98080\n",
       "1335   18  female  36.850         0     no  southeast   1629.83350\n",
       "1336   21  female  25.800         0     no  southwest   2007.94500\n",
       "1337   61  female  29.070         0    yes  northwest  29141.36030\n",
       "\n",
       "[1338 rows x 7 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "insurance_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "02e64f41",
   "metadata": {},
   "outputs": [],
   "source": [
    "### can we use list comprehension here?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "9c9c3047",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['h', 'u', 'm', 'a', 'n']\n"
     ]
    }
   ],
   "source": [
    "human = [ letter for letter in 'human' ]\n",
    "print( human)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7b9c50c4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 10, 20, 30, 40, 50, 60, 70, 80, 90]\n"
     ]
    }
   ],
   "source": [
    "nums = [n for n in range(100) if n % 2 == 0 if n % 5 == 0]\n",
    "print(nums)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "5b0d77fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Even', 'Odd', 'Even', 'Odd', 'Even', 'Odd', 'Even', 'Odd', 'Even', 'Odd']"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numbers = [\"Even\" if i%2 == 0 else \"Odd\" for i in range(10)]\n",
    "numbers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ccb4b098",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Team</th>\n",
       "      <th>Goals</th>\n",
       "      <th>Shots on target</th>\n",
       "      <th>Shots off target</th>\n",
       "      <th>Shooting Accuracy</th>\n",
       "      <th>% Goals-to-shots</th>\n",
       "      <th>Total shots (inc. Blocked)</th>\n",
       "      <th>Hit Woodwork</th>\n",
       "      <th>Penalty goals</th>\n",
       "      <th>Penalties not scored</th>\n",
       "      <th>...</th>\n",
       "      <th>Saves made</th>\n",
       "      <th>Saves-to-shots ratio</th>\n",
       "      <th>Fouls Won</th>\n",
       "      <th>Fouls Conceded</th>\n",
       "      <th>Offsides</th>\n",
       "      <th>Yellow Cards</th>\n",
       "      <th>Red Cards</th>\n",
       "      <th>Subs on</th>\n",
       "      <th>Subs off</th>\n",
       "      <th>Players Used</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Croatia</td>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
       "      <td>12</td>\n",
       "      <td>51.9%</td>\n",
       "      <td>16.0%</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>81.3%</td>\n",
       "      <td>41</td>\n",
       "      <td>62</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Czech Republic</td>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>41.9%</td>\n",
       "      <td>12.9%</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>60.1%</td>\n",
       "      <td>53</td>\n",
       "      <td>73</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>50.0%</td>\n",
       "      <td>20.0%</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>66.7%</td>\n",
       "      <td>25</td>\n",
       "      <td>38</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>England</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>18</td>\n",
       "      <td>50.0%</td>\n",
       "      <td>17.2%</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>22</td>\n",
       "      <td>88.1%</td>\n",
       "      <td>43</td>\n",
       "      <td>45</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>France</td>\n",
       "      <td>3</td>\n",
       "      <td>22</td>\n",
       "      <td>24</td>\n",
       "      <td>37.9%</td>\n",
       "      <td>6.5%</td>\n",
       "      <td>65</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>54.6%</td>\n",
       "      <td>36</td>\n",
       "      <td>51</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Germany</td>\n",
       "      <td>10</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>47.8%</td>\n",
       "      <td>15.6%</td>\n",
       "      <td>80</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>62.6%</td>\n",
       "      <td>63</td>\n",
       "      <td>49</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Greece</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>18</td>\n",
       "      <td>30.7%</td>\n",
       "      <td>19.2%</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>65.1%</td>\n",
       "      <td>67</td>\n",
       "      <td>48</td>\n",
       "      <td>12</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Italy</td>\n",
       "      <td>6</td>\n",
       "      <td>34</td>\n",
       "      <td>45</td>\n",
       "      <td>43.0%</td>\n",
       "      <td>7.5%</td>\n",
       "      <td>110</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
       "      <td>74.1%</td>\n",
       "      <td>101</td>\n",
       "      <td>89</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Netherlands</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>36</td>\n",
       "      <td>25.0%</td>\n",
       "      <td>4.1%</td>\n",
       "      <td>60</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>70.6%</td>\n",
       "      <td>35</td>\n",
       "      <td>30</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Poland</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>23</td>\n",
       "      <td>39.4%</td>\n",
       "      <td>5.2%</td>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>66.7%</td>\n",
       "      <td>48</td>\n",
       "      <td>56</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Portugal</td>\n",
       "      <td>6</td>\n",
       "      <td>22</td>\n",
       "      <td>42</td>\n",
       "      <td>34.3%</td>\n",
       "      <td>9.3%</td>\n",
       "      <td>82</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>71.5%</td>\n",
       "      <td>73</td>\n",
       "      <td>90</td>\n",
       "      <td>10</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Republic of Ireland</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>36.8%</td>\n",
       "      <td>5.2%</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>17</td>\n",
       "      <td>65.4%</td>\n",
       "      <td>43</td>\n",
       "      <td>51</td>\n",
       "      <td>11</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Russia</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>31</td>\n",
       "      <td>22.5%</td>\n",
       "      <td>12.5%</td>\n",
       "      <td>59</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>77.0%</td>\n",
       "      <td>34</td>\n",
       "      <td>43</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Spain</td>\n",
       "      <td>12</td>\n",
       "      <td>42</td>\n",
       "      <td>33</td>\n",
       "      <td>55.9%</td>\n",
       "      <td>16.0%</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>93.8%</td>\n",
       "      <td>102</td>\n",
       "      <td>83</td>\n",
       "      <td>19</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Sweden</td>\n",
       "      <td>5</td>\n",
       "      <td>17</td>\n",
       "      <td>19</td>\n",
       "      <td>47.2%</td>\n",
       "      <td>13.8%</td>\n",
       "      <td>39</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>61.6%</td>\n",
       "      <td>35</td>\n",
       "      <td>51</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Ukraine</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>26</td>\n",
       "      <td>21.2%</td>\n",
       "      <td>6.0%</td>\n",
       "      <td>38</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>76.5%</td>\n",
       "      <td>48</td>\n",
       "      <td>31</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Team  Goals  Shots on target  Shots off target  \\\n",
       "0               Croatia      4               13                12   \n",
       "1        Czech Republic      4               13                18   \n",
       "2               Denmark      4               10                10   \n",
       "3               England      5               11                18   \n",
       "4                France      3               22                24   \n",
       "5               Germany     10               32                32   \n",
       "6                Greece      5                8                18   \n",
       "7                 Italy      6               34                45   \n",
       "8           Netherlands      2               12                36   \n",
       "9                Poland      2               15                23   \n",
       "10             Portugal      6               22                42   \n",
       "11  Republic of Ireland      1                7                12   \n",
       "12               Russia      5                9                31   \n",
       "13                Spain     12               42                33   \n",
       "14               Sweden      5               17                19   \n",
       "15              Ukraine      2                7                26   \n",
       "\n",
       "   Shooting Accuracy % Goals-to-shots  Total shots (inc. Blocked)  \\\n",
       "0              51.9%            16.0%                          32   \n",
       "1              41.9%            12.9%                          39   \n",
       "2              50.0%            20.0%                          27   \n",
       "3              50.0%            17.2%                          40   \n",
       "4              37.9%             6.5%                          65   \n",
       "5              47.8%            15.6%                          80   \n",
       "6              30.7%            19.2%                          32   \n",
       "7              43.0%             7.5%                         110   \n",
       "8              25.0%             4.1%                          60   \n",
       "9              39.4%             5.2%                          48   \n",
       "10             34.3%             9.3%                          82   \n",
       "11             36.8%             5.2%                          28   \n",
       "12             22.5%            12.5%                          59   \n",
       "13             55.9%            16.0%                         100   \n",
       "14             47.2%            13.8%                          39   \n",
       "15             21.2%             6.0%                          38   \n",
       "\n",
       "    Hit Woodwork  Penalty goals  Penalties not scored  ...  Saves made  \\\n",
       "0              0              0                     0  ...          13   \n",
       "1              0              0                     0  ...           9   \n",
       "2              1              0                     0  ...          10   \n",
       "3              0              0                     0  ...          22   \n",
       "4              1              0                     0  ...           6   \n",
       "5              2              1                     0  ...          10   \n",
       "6              1              1                     1  ...          13   \n",
       "7              2              0                     0  ...          20   \n",
       "8              2              0                     0  ...          12   \n",
       "9              0              0                     0  ...           6   \n",
       "10             6              0                     0  ...          10   \n",
       "11             0              0                     0  ...          17   \n",
       "12             2              0                     0  ...          10   \n",
       "13             0              1                     0  ...          15   \n",
       "14             3              0                     0  ...           8   \n",
       "15             0              0                     0  ...          13   \n",
       "\n",
       "    Saves-to-shots ratio  Fouls Won Fouls Conceded  Offsides  Yellow Cards  \\\n",
       "0                  81.3%         41             62         2             9   \n",
       "1                  60.1%         53             73         8             7   \n",
       "2                  66.7%         25             38         8             4   \n",
       "3                  88.1%         43             45         6             5   \n",
       "4                  54.6%         36             51         5             6   \n",
       "5                  62.6%         63             49        12             4   \n",
       "6                  65.1%         67             48        12             9   \n",
       "7                  74.1%        101             89        16            16   \n",
       "8                  70.6%         35             30         3             5   \n",
       "9                  66.7%         48             56         3             7   \n",
       "10                 71.5%         73             90        10            12   \n",
       "11                 65.4%         43             51        11             6   \n",
       "12                 77.0%         34             43         4             6   \n",
       "13                 93.8%        102             83        19            11   \n",
       "14                 61.6%         35             51         7             7   \n",
       "15                 76.5%         48             31         4             5   \n",
       "\n",
       "    Red Cards  Subs on  Subs off  Players Used  \n",
       "0           0        9         9            16  \n",
       "1           0       11        11            19  \n",
       "2           0        7         7            15  \n",
       "3           0       11        11            16  \n",
       "4           0       11        11            19  \n",
       "5           0       15        15            17  \n",
       "6           1       12        12            20  \n",
       "7           0       18        18            19  \n",
       "8           0        7         7            15  \n",
       "9           1        7         7            17  \n",
       "10          0       14        14            16  \n",
       "11          1       10        10            17  \n",
       "12          0        7         7            16  \n",
       "13          0       17        17            18  \n",
       "14          0        9         9            18  \n",
       "15          0        9         9            18  \n",
       "\n",
       "[16 rows x 35 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "football_stats = pd.read_csv('E:\\Data Science by John\\pandas\\Euro_2012_stats_TEAM.csv')\n",
    "football_stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "05c2acd8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Goals</th>\n",
       "      <th>Shooting Accuracy</th>\n",
       "      <th>Yellow Cards</th>\n",
       "      <th>Red Cards</th>\n",
       "      <th>Players Used</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>51.9%</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>41.9%</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>50.0%</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>50.0%</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>37.9%</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10</td>\n",
       "      <td>47.8%</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5</td>\n",
       "      <td>30.7%</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>6</td>\n",
       "      <td>43.0%</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2</td>\n",
       "      <td>25.0%</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2</td>\n",
       "      <td>39.4%</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>6</td>\n",
       "      <td>34.3%</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1</td>\n",
       "      <td>36.8%</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>5</td>\n",
       "      <td>22.5%</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>12</td>\n",
       "      <td>55.9%</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>5</td>\n",
       "      <td>47.2%</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2</td>\n",
       "      <td>21.2%</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Goals Shooting Accuracy  Yellow Cards  Red Cards  Players Used\n",
       "0       4             51.9%             9          0            16\n",
       "1       4             41.9%             7          0            19\n",
       "2       4             50.0%             4          0            15\n",
       "3       5             50.0%             5          0            16\n",
       "4       3             37.9%             6          0            19\n",
       "5      10             47.8%             4          0            17\n",
       "6       5             30.7%             9          1            20\n",
       "7       6             43.0%            16          0            19\n",
       "8       2             25.0%             5          0            15\n",
       "9       2             39.4%             7          1            17\n",
       "10      6             34.3%            12          0            16\n",
       "11      1             36.8%             6          1            17\n",
       "12      5             22.5%             6          0            16\n",
       "13     12             55.9%            11          0            18\n",
       "14      5             47.2%             7          0            18\n",
       "15      2             21.2%             5          0            18"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "football_stats_accessed = football_stats[['Goals','Shooting Accuracy','Yellow Cards','Red Cards','Players Used']]\n",
    "football_stats_accessed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "0a5173f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Team</th>\n",
       "      <th>Goals</th>\n",
       "      <th>Shots on target</th>\n",
       "      <th>Shots off target</th>\n",
       "      <th>Shooting Accuracy</th>\n",
       "      <th>% Goals-to-shots</th>\n",
       "      <th>Total shots (inc. Blocked)</th>\n",
       "      <th>Hit Woodwork</th>\n",
       "      <th>Penalty goals</th>\n",
       "      <th>Penalties not scored</th>\n",
       "      <th>...</th>\n",
       "      <th>Saves made</th>\n",
       "      <th>Saves-to-shots ratio</th>\n",
       "      <th>Fouls Won</th>\n",
       "      <th>Fouls Conceded</th>\n",
       "      <th>Offsides</th>\n",
       "      <th>Yellow Cards</th>\n",
       "      <th>Red Cards</th>\n",
       "      <th>Subs on</th>\n",
       "      <th>Subs off</th>\n",
       "      <th>Players Used</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Germany</td>\n",
       "      <td>10</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>47.8%</td>\n",
       "      <td>15.6%</td>\n",
       "      <td>80</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>62.6%</td>\n",
       "      <td>63</td>\n",
       "      <td>49</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Italy</td>\n",
       "      <td>6</td>\n",
       "      <td>34</td>\n",
       "      <td>45</td>\n",
       "      <td>43.0%</td>\n",
       "      <td>7.5%</td>\n",
       "      <td>110</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
       "      <td>74.1%</td>\n",
       "      <td>101</td>\n",
       "      <td>89</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Portugal</td>\n",
       "      <td>6</td>\n",
       "      <td>22</td>\n",
       "      <td>42</td>\n",
       "      <td>34.3%</td>\n",
       "      <td>9.3%</td>\n",
       "      <td>82</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>71.5%</td>\n",
       "      <td>73</td>\n",
       "      <td>90</td>\n",
       "      <td>10</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Spain</td>\n",
       "      <td>12</td>\n",
       "      <td>42</td>\n",
       "      <td>33</td>\n",
       "      <td>55.9%</td>\n",
       "      <td>16.0%</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>93.8%</td>\n",
       "      <td>102</td>\n",
       "      <td>83</td>\n",
       "      <td>19</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Team  Goals  Shots on target  Shots off target Shooting Accuracy  \\\n",
       "5    Germany     10               32                32             47.8%   \n",
       "7      Italy      6               34                45             43.0%   \n",
       "10  Portugal      6               22                42             34.3%   \n",
       "13     Spain     12               42                33             55.9%   \n",
       "\n",
       "   % Goals-to-shots  Total shots (inc. Blocked)  Hit Woodwork  Penalty goals  \\\n",
       "5             15.6%                          80             2              1   \n",
       "7              7.5%                         110             2              0   \n",
       "10             9.3%                          82             6              0   \n",
       "13            16.0%                         100             0              1   \n",
       "\n",
       "    Penalties not scored  ...  Saves made  Saves-to-shots ratio  Fouls Won  \\\n",
       "5                      0  ...          10                 62.6%         63   \n",
       "7                      0  ...          20                 74.1%        101   \n",
       "10                     0  ...          10                 71.5%         73   \n",
       "13                     0  ...          15                 93.8%        102   \n",
       "\n",
       "   Fouls Conceded  Offsides  Yellow Cards  Red Cards  Subs on  Subs off  \\\n",
       "5              49        12             4          0       15        15   \n",
       "7              89        16            16          0       18        18   \n",
       "10             90        10            12          0       14        14   \n",
       "13             83        19            11          0       17        17   \n",
       "\n",
       "    Players Used  \n",
       "5             17  \n",
       "7             19  \n",
       "10            16  \n",
       "13            18  \n",
       "\n",
       "[4 rows x 35 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "football_stats.query('Goals > 5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "cf26a9c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Goals</th>\n",
       "      <th>Shooting_Accuracy</th>\n",
       "      <th>Yellow_Cards</th>\n",
       "      <th>Red_Cards</th>\n",
       "      <th>Players_Used</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>51.9%</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>41.9%</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>50.0%</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>50.0%</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>37.9%</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10</td>\n",
       "      <td>47.8%</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5</td>\n",
       "      <td>30.7%</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>6</td>\n",
       "      <td>43.0%</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2</td>\n",
       "      <td>25.0%</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2</td>\n",
       "      <td>39.4%</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>6</td>\n",
       "      <td>34.3%</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1</td>\n",
       "      <td>36.8%</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>5</td>\n",
       "      <td>22.5%</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>12</td>\n",
       "      <td>55.9%</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>5</td>\n",
       "      <td>47.2%</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2</td>\n",
       "      <td>21.2%</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Goals Shooting_Accuracy  Yellow_Cards  Red_Cards  Players_Used\n",
       "0       4             51.9%             9          0            16\n",
       "1       4             41.9%             7          0            19\n",
       "2       4             50.0%             4          0            15\n",
       "3       5             50.0%             5          0            16\n",
       "4       3             37.9%             6          0            19\n",
       "5      10             47.8%             4          0            17\n",
       "6       5             30.7%             9          1            20\n",
       "7       6             43.0%            16          0            19\n",
       "8       2             25.0%             5          0            15\n",
       "9       2             39.4%             7          1            17\n",
       "10      6             34.3%            12          0            16\n",
       "11      1             36.8%             6          1            17\n",
       "12      5             22.5%             6          0            16\n",
       "13     12             55.9%            11          0            18\n",
       "14      5             47.2%             7          0            18\n",
       "15      2             21.2%             5          0            18"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "football_stats_accessed.columns = [column.replace(\" \",\"_\") for column in football_stats_accessed.columns]\n",
    "football_stats_accessed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "cf34a1a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Goals</th>\n",
       "      <th>Shooting_Accuracy</th>\n",
       "      <th>Yellow_Cards</th>\n",
       "      <th>Red_Cards</th>\n",
       "      <th>Players_Used</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5</td>\n",
       "      <td>30.7%</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>6</td>\n",
       "      <td>43.0%</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2</td>\n",
       "      <td>39.4%</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>6</td>\n",
       "      <td>34.3%</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1</td>\n",
       "      <td>36.8%</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>12</td>\n",
       "      <td>55.9%</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Goals Shooting_Accuracy  Yellow_Cards  Red_Cards  Players_Used\n",
       "6       5             30.7%             9          1            20\n",
       "7       6             43.0%            16          0            19\n",
       "9       2             39.4%             7          1            17\n",
       "10      6             34.3%            12          0            16\n",
       "11      1             36.8%             6          1            17\n",
       "13     12             55.9%            11          0            18"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "football_stats_accessed.query('Yellow_Cards > 10 | Red_Cards == 1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "a3c48138",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings \n",
    "warnings.filterwarnings(action = 'ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "de29d4ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>22.5</td>\n",
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       "      <td>0</td>\n",
       "      <td>16</td>\n",
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       "      <th>14</th>\n",
       "      <td>5</td>\n",
       "      <td>47.2</td>\n",
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       "      <td>0</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Goals Shooting_Accuracy  Yellow_Cards  Red_Cards  Players_Used\n",
       "0       4              51.9             9          0            16\n",
       "1       4              41.9             7          0            19\n",
       "2       4              50.0             4          0            15\n",
       "3       5              50.0             5          0            16\n",
       "4       3              37.9             6          0            19\n",
       "5      10              47.8             4          0            17\n",
       "6       5              30.7             9          1            20\n",
       "7       6              43.0            16          0            19\n",
       "8       2              25.0             5          0            15\n",
       "9       2              39.4             7          1            17\n",
       "10      6              34.3            12          0            16\n",
       "11      1              36.8             6          1            17\n",
       "12      5              22.5             6          0            16\n",
       "13     12              55.9            11          0            18\n",
       "14      5              47.2             7          0            18\n",
       "15      2              21.2             5          0            18"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "football_stats_accessed['Shooting_Accuracy'] = football_stats_accessed['Shooting_Accuracy'].str.replace('%','')\n",
    "football_stats_accessed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "eece95cd",
   "metadata": {},
   "outputs": [
    {
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       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>12</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>5</td>\n",
       "      <td>47.2</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Goals Shooting_Accuracy  Yellow_Cards  Red_Cards  Players_Used\n",
       "0       4              51.9             9          0            16\n",
       "1       4              41.9             7          0            19\n",
       "2       4              50.0             4          0            15\n",
       "3       5              50.0             5          0            16\n",
       "4       3              37.9             6          0            19\n",
       "5      10              47.8             4          0            17\n",
       "6       5              30.7             9          1            20\n",
       "7       6              43.0            16          0            19\n",
       "9       2              39.4             7          1            17\n",
       "10      6              34.3            12          0            16\n",
       "11      1              36.8             6          1            17\n",
       "13     12              55.9            11          0            18\n",
       "14      5              47.2             7          0            18"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "football_stats_accessed.query('Shooting_Accuracy > = \"30.0\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bdd6799a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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