Lecture_4.ipynb

{
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  {
   "cell_type": "markdown",
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   "source": [
    "# Lecture 4: Data Preproccessing with Pandas\n",
    "\n",
    "Instructor: Md Shahidullah Kawsar\n",
    "<br>Data Scientist, IDARE, Houston, TX, USA\n",
    "\n",
    "#### Objectives:\n",
    "- How to extract new information from a column?\n",
    "- How to create a column based on a condition or function?\n",
    "- Removing a string from a column\n",
    "- Checking the unique values for each column\n",
    "- performing calculation in dataframe columns\n",
    "- dataframe sorting\n",
    "- dataframe slicing\n",
    "\n",
    "\n",
    "#### References:\n",
    "[1] Data Source: https://stats.espncricinfo.com/ci/content/records/223646.html\n",
    "<br>[2] pandas split: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.split.html\n",
    "<br>[3] pandas concatenation: https://pandas.pydata.org/docs/reference/api/pandas.concat.html\n",
    "<br>[4] pandas replace: https://pandas.pydata.org/docs/reference/api/pandas.Series.str.replace.html\n",
    "<br>[5] pandas column rename: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rename.html\n",
    "<br>[6] pandas sorting: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.sort_values.html\n",
    "<br>[7] pandas counting unique values: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.value_counts.html\n",
    "<br>[8] pandas drop: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.drop.html\n",
    "<br>[9] pandas data type conversion: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.astype.html\n",
    "<br>[10] **Self Study:** difference between .loc and .iloc: https://www.analyticsvidhya.com/blog/2020/02/loc-iloc-pandas/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 465,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# display 100 rows of the dataframe\n",
    "pd.options.display.max_rows = 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Reading an excel file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 466,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\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>Player</th>\n",
       "      <th>Span</th>\n",
       "      <th>Mat</th>\n",
       "      <th>Inns</th>\n",
       "      <th>NO</th>\n",
       "      <th>Runs</th>\n",
       "      <th>HS</th>\n",
       "      <th>Ave</th>\n",
       "      <th>100</th>\n",
       "      <th>50</th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SR Tendulkar (INDIA)</td>\n",
       "      <td>1989-2013</td>\n",
       "      <td>200</td>\n",
       "      <td>329</td>\n",
       "      <td>33</td>\n",
       "      <td>15921</td>\n",
       "      <td>248*</td>\n",
       "      <td>53.78</td>\n",
       "      <td>51</td>\n",
       "      <td>68</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RT Ponting (AUS)</td>\n",
       "      <td>1995-2012</td>\n",
       "      <td>168</td>\n",
       "      <td>287</td>\n",
       "      <td>29</td>\n",
       "      <td>13378</td>\n",
       "      <td>257</td>\n",
       "      <td>51.85</td>\n",
       "      <td>41</td>\n",
       "      <td>62</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JH Kallis (ICC/SA)</td>\n",
       "      <td>1995-2013</td>\n",
       "      <td>166</td>\n",
       "      <td>280</td>\n",
       "      <td>40</td>\n",
       "      <td>13289</td>\n",
       "      <td>224</td>\n",
       "      <td>55.37</td>\n",
       "      <td>45</td>\n",
       "      <td>58</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>R Dravid (ICC/INDIA)</td>\n",
       "      <td>1996-2012</td>\n",
       "      <td>164</td>\n",
       "      <td>286</td>\n",
       "      <td>32</td>\n",
       "      <td>13288</td>\n",
       "      <td>270</td>\n",
       "      <td>52.31</td>\n",
       "      <td>36</td>\n",
       "      <td>63</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AN Cook (ENG)</td>\n",
       "      <td>2006-2018</td>\n",
       "      <td>161</td>\n",
       "      <td>291</td>\n",
       "      <td>16</td>\n",
       "      <td>12472</td>\n",
       "      <td>294</td>\n",
       "      <td>45.35</td>\n",
       "      <td>33</td>\n",
       "      <td>57</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Player       Span  Mat  Inns  NO   Runs    HS    Ave  100  \\\n",
       "0  SR Tendulkar (INDIA)  1989-2013  200   329  33  15921  248*  53.78   51   \n",
       "1      RT Ponting (AUS)  1995-2012  168   287  29  13378   257  51.85   41   \n",
       "2    JH Kallis (ICC/SA)  1995-2013  166   280  40  13289   224  55.37   45   \n",
       "3  R Dravid (ICC/INDIA)  1996-2012  164   286  32  13288   270  52.31   36   \n",
       "4         AN Cook (ENG)  2006-2018  161   291  16  12472   294  45.35   33   \n",
       "\n",
       "   50   0  \n",
       "0  68  14  \n",
       "1  62  17  \n",
       "2  58  16  \n",
       "3  63   8  \n",
       "4  57   9  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.read_excel(\"test_cricket.xlsx\", sheet_name='runs')\n",
    "\n",
    "display(df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### How can you extract the country information from the 'Player' column if thre were no \"(\" and \")\" symbol?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 467,
   "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>Player</th>\n",
       "      <th>Span</th>\n",
       "      <th>Mat</th>\n",
       "      <th>Inns</th>\n",
       "      <th>NO</th>\n",
       "      <th>Runs</th>\n",
       "      <th>HS</th>\n",
       "      <th>Ave</th>\n",
       "      <th>100</th>\n",
       "      <th>50</th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SR Tendulkar INDIA</td>\n",
       "      <td>1989-2013</td>\n",
       "      <td>200</td>\n",
       "      <td>329</td>\n",
       "      <td>33</td>\n",
       "      <td>15921</td>\n",
       "      <td>248*</td>\n",
       "      <td>53.78</td>\n",
       "      <td>51</td>\n",
       "      <td>68</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RT Ponting AUS</td>\n",
       "      <td>1995-2012</td>\n",
       "      <td>168</td>\n",
       "      <td>287</td>\n",
       "      <td>29</td>\n",
       "      <td>13378</td>\n",
       "      <td>257</td>\n",
       "      <td>51.85</td>\n",
       "      <td>41</td>\n",
       "      <td>62</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JH Kallis ICC/SA</td>\n",
       "      <td>1995-2013</td>\n",
       "      <td>166</td>\n",
       "      <td>280</td>\n",
       "      <td>40</td>\n",
       "      <td>13289</td>\n",
       "      <td>224</td>\n",
       "      <td>55.37</td>\n",
       "      <td>45</td>\n",
       "      <td>58</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>R Dravid ICC/INDIA</td>\n",
       "      <td>1996-2012</td>\n",
       "      <td>164</td>\n",
       "      <td>286</td>\n",
       "      <td>32</td>\n",
       "      <td>13288</td>\n",
       "      <td>270</td>\n",
       "      <td>52.31</td>\n",
       "      <td>36</td>\n",
       "      <td>63</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AN Cook ENG</td>\n",
       "      <td>2006-2018</td>\n",
       "      <td>161</td>\n",
       "      <td>291</td>\n",
       "      <td>16</td>\n",
       "      <td>12472</td>\n",
       "      <td>294</td>\n",
       "      <td>45.35</td>\n",
       "      <td>33</td>\n",
       "      <td>57</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Player       Span  Mat  Inns  NO   Runs    HS    Ave  100  50  \\\n",
       "0  SR Tendulkar INDIA  1989-2013  200   329  33  15921  248*  53.78   51  68   \n",
       "1      RT Ponting AUS  1995-2012  168   287  29  13378   257  51.85   41  62   \n",
       "2    JH Kallis ICC/SA  1995-2013  166   280  40  13289   224  55.37   45  58   \n",
       "3  R Dravid ICC/INDIA  1996-2012  164   286  32  13288   270  52.31   36  63   \n",
       "4         AN Cook ENG  2006-2018  161   291  16  12472   294  45.35   33  57   \n",
       "\n",
       "    0  \n",
       "0  14  \n",
       "1  17  \n",
       "2  16  \n",
       "3   8  \n",
       "4   9  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "file = df.copy()\n",
    "\n",
    "file['Player'] = file['Player'].str.replace(\"(\", \"\")\n",
    "file['Player'] = file['Player'].str.replace(\")\", \"\")\n",
    "file['Player'] = file['Player'].str.replace(\"\\xa0\", \" \")\n",
    "\n",
    "display(file.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 468,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\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>Player</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[SR, Tendulkar, INDIA]</td>\n",
       "      <td>INDIA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[RT, Ponting, AUS]</td>\n",
       "      <td>AUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[JH, Kallis, ICC/SA]</td>\n",
       "      <td>ICC/SA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>[R, Dravid, ICC/INDIA]</td>\n",
       "      <td>ICC/INDIA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>[AN, Cook, ENG]</td>\n",
       "      <td>ENG</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Player    Country\n",
       "0  [SR, Tendulkar, INDIA]      INDIA\n",
       "1      [RT, Ponting, AUS]        AUS\n",
       "2    [JH, Kallis, ICC/SA]     ICC/SA\n",
       "3  [R, Dravid, ICC/INDIA]  ICC/INDIA\n",
       "4         [AN, Cook, ENG]        ENG"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "file_player = file['Player'].str.split(\" \")\n",
    "file_player = pd.DataFrame(file_player)\n",
    "\n",
    "file_player['Country'] = file_player['Player'].str[-1]\n",
    "\n",
    "print(type(file_player))\n",
    "\n",
    "display(file_player.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 469,
   "metadata": {},
   "outputs": [],
   "source": [
    "# print(file['Player'].values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Codes from Lecture 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 470,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\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>Player</th>\n",
       "      <th>Span</th>\n",
       "      <th>Match</th>\n",
       "      <th>Innings</th>\n",
       "      <th>NotOut</th>\n",
       "      <th>Runs</th>\n",
       "      <th>Highest_score</th>\n",
       "      <th>Average</th>\n",
       "      <th>Centuries</th>\n",
       "      <th>Half_centuries</th>\n",
       "      <th>Ducks</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SR Tendulkar</td>\n",
       "      <td>1989-2013</td>\n",
       "      <td>200</td>\n",
       "      <td>329</td>\n",
       "      <td>33</td>\n",
       "      <td>15921</td>\n",
       "      <td>248*</td>\n",
       "      <td>53.78</td>\n",
       "      <td>51</td>\n",
       "      <td>68</td>\n",
       "      <td>14</td>\n",
       "      <td>INDIA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RT Ponting</td>\n",
       "      <td>1995-2012</td>\n",
       "      <td>168</td>\n",
       "      <td>287</td>\n",
       "      <td>29</td>\n",
       "      <td>13378</td>\n",
       "      <td>257</td>\n",
       "      <td>51.85</td>\n",
       "      <td>41</td>\n",
       "      <td>62</td>\n",
       "      <td>17</td>\n",
       "      <td>AUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JH Kallis</td>\n",
       "      <td>1995-2013</td>\n",
       "      <td>166</td>\n",
       "      <td>280</td>\n",
       "      <td>40</td>\n",
       "      <td>13289</td>\n",
       "      <td>224</td>\n",
       "      <td>55.37</td>\n",
       "      <td>45</td>\n",
       "      <td>58</td>\n",
       "      <td>16</td>\n",
       "      <td>ICC/SA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>R Dravid</td>\n",
       "      <td>1996-2012</td>\n",
       "      <td>164</td>\n",
       "      <td>286</td>\n",
       "      <td>32</td>\n",
       "      <td>13288</td>\n",
       "      <td>270</td>\n",
       "      <td>52.31</td>\n",
       "      <td>36</td>\n",
       "      <td>63</td>\n",
       "      <td>8</td>\n",
       "      <td>ICC/INDIA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AN Cook</td>\n",
       "      <td>2006-2018</td>\n",
       "      <td>161</td>\n",
       "      <td>291</td>\n",
       "      <td>16</td>\n",
       "      <td>12472</td>\n",
       "      <td>294</td>\n",
       "      <td>45.35</td>\n",
       "      <td>33</td>\n",
       "      <td>57</td>\n",
       "      <td>9</td>\n",
       "      <td>ENG</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Player       Span  Match  Innings  NotOut   Runs Highest_score  \\\n",
       "0  SR Tendulkar   1989-2013    200      329      33  15921          248*   \n",
       "1    RT Ponting   1995-2012    168      287      29  13378           257   \n",
       "2     JH Kallis   1995-2013    166      280      40  13289           224   \n",
       "3      R Dravid   1996-2012    164      286      32  13288           270   \n",
       "4       AN Cook   2006-2018    161      291      16  12472           294   \n",
       "\n",
       "   Average  Centuries  Half_centuries  Ducks    Country  \n",
       "0    53.78         51              68     14      INDIA  \n",
       "1    51.85         41              62     17        AUS  \n",
       "2    55.37         45              58     16     ICC/SA  \n",
       "3    52.31         36              63      8  ICC/INDIA  \n",
       "4    45.35         33              57      9        ENG  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# renaming the column names\n",
    "df = df.rename(columns={'Mat':'Match', \n",
    "                        'Inns':'Innings',\n",
    "                        'NO': 'NotOut',\n",
    "                        'HS': 'Highest_score',\n",
    "                        'Ave': 'Average',\n",
    "                        100: 'Centuries',\n",
    "                        50: 'Half_centuries',\n",
    "                        0: 'Ducks'})\n",
    "\n",
    "# splitting the 'Player' column to get the information about 'Country'\n",
    "df_player = df['Player'].str.split(\"(\", expand=True)\n",
    "\n",
    "# concatinating 'Country' with the main dataframe\n",
    "df = pd.concat([df, df_player], axis=1)\n",
    "\n",
    "# dropping the 'Player' columns\n",
    "df = df.drop('Player', axis=1)\n",
    "\n",
    "# renaming the column names\n",
    "df = df.rename(columns={0: 'Player',\n",
    "                        1: 'Country'})\n",
    "\n",
    "# remove the \")\" from the 'Country' column\n",
    "df['Country'] = df['Country'].str.replace(\")\", \"\")\n",
    "\n",
    "# rearrange the columns\n",
    "new_col_sequence = ['Player', 'Span', 'Match', 'Innings', 'NotOut', 'Runs', 'Highest_score',\n",
    "                    'Average', 'Centuries', 'Half_centuries', 'Ducks', 'Country']\n",
    "df = df[new_col_sequence]\n",
    "\n",
    "display(df.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 471,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### How to create a column based on a condition or function?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 472,
   "metadata": {},
   "outputs": [],
   "source": [
    "def icc_check(x):\n",
    "    if \"ICC\" in x:\n",
    "        return \"Yes\"\n",
    "    else:\n",
    "        return \"No\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 473,
   "metadata": {},
   "outputs": [],
   "source": [
    "# def INDIA_check(x):\n",
    "#     if \"INDIA\" in x:\n",
    "#         return 1\n",
    "#     else:\n",
    "#         return 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 474,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\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>Player</th>\n",
       "      <th>Span</th>\n",
       "      <th>Match</th>\n",
       "      <th>Innings</th>\n",
       "      <th>NotOut</th>\n",
       "      <th>Runs</th>\n",
       "      <th>Highest_score</th>\n",
       "      <th>Average</th>\n",
       "      <th>Centuries</th>\n",
       "      <th>Half_centuries</th>\n",
       "      <th>Ducks</th>\n",
       "      <th>Country</th>\n",
       "      <th>played_for_ICC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SR Tendulkar</td>\n",
       "      <td>1989-2013</td>\n",
       "      <td>200</td>\n",
       "      <td>329</td>\n",
       "      <td>33</td>\n",
       "      <td>15921</td>\n",
       "      <td>248*</td>\n",
       "      <td>53.78</td>\n",
       "      <td>51</td>\n",
       "      <td>68</td>\n",
       "      <td>14</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RT Ponting</td>\n",
       "      <td>1995-2012</td>\n",
       "      <td>168</td>\n",
       "      <td>287</td>\n",
       "      <td>29</td>\n",
       "      <td>13378</td>\n",
       "      <td>257</td>\n",
       "      <td>51.85</td>\n",
       "      <td>41</td>\n",
       "      <td>62</td>\n",
       "      <td>17</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JH Kallis</td>\n",
       "      <td>1995-2013</td>\n",
       "      <td>166</td>\n",
       "      <td>280</td>\n",
       "      <td>40</td>\n",
       "      <td>13289</td>\n",
       "      <td>224</td>\n",
       "      <td>55.37</td>\n",
       "      <td>45</td>\n",
       "      <td>58</td>\n",
       "      <td>16</td>\n",
       "      <td>ICC/SA</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>R Dravid</td>\n",
       "      <td>1996-2012</td>\n",
       "      <td>164</td>\n",
       "      <td>286</td>\n",
       "      <td>32</td>\n",
       "      <td>13288</td>\n",
       "      <td>270</td>\n",
       "      <td>52.31</td>\n",
       "      <td>36</td>\n",
       "      <td>63</td>\n",
       "      <td>8</td>\n",
       "      <td>ICC/INDIA</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AN Cook</td>\n",
       "      <td>2006-2018</td>\n",
       "      <td>161</td>\n",
       "      <td>291</td>\n",
       "      <td>16</td>\n",
       "      <td>12472</td>\n",
       "      <td>294</td>\n",
       "      <td>45.35</td>\n",
       "      <td>33</td>\n",
       "      <td>57</td>\n",
       "      <td>9</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>KC Sangakkara</td>\n",
       "      <td>2000-2015</td>\n",
       "      <td>134</td>\n",
       "      <td>233</td>\n",
       "      <td>17</td>\n",
       "      <td>12400</td>\n",
       "      <td>319</td>\n",
       "      <td>57.40</td>\n",
       "      <td>38</td>\n",
       "      <td>52</td>\n",
       "      <td>11</td>\n",
       "      <td>SL</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>BC Lara</td>\n",
       "      <td>1990-2006</td>\n",
       "      <td>131</td>\n",
       "      <td>232</td>\n",
       "      <td>6</td>\n",
       "      <td>11953</td>\n",
       "      <td>400*</td>\n",
       "      <td>52.88</td>\n",
       "      <td>34</td>\n",
       "      <td>48</td>\n",
       "      <td>17</td>\n",
       "      <td>ICC/WI</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>S Chanderpaul</td>\n",
       "      <td>1994-2015</td>\n",
       "      <td>164</td>\n",
       "      <td>280</td>\n",
       "      <td>49</td>\n",
       "      <td>11867</td>\n",
       "      <td>203*</td>\n",
       "      <td>51.37</td>\n",
       "      <td>30</td>\n",
       "      <td>66</td>\n",
       "      <td>15</td>\n",
       "      <td>WI</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DPMD Jayawardene</td>\n",
       "      <td>1997-2014</td>\n",
       "      <td>149</td>\n",
       "      <td>252</td>\n",
       "      <td>15</td>\n",
       "      <td>11814</td>\n",
       "      <td>374</td>\n",
       "      <td>49.84</td>\n",
       "      <td>34</td>\n",
       "      <td>50</td>\n",
       "      <td>15</td>\n",
       "      <td>SL</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>AR Border</td>\n",
       "      <td>1978-1994</td>\n",
       "      <td>156</td>\n",
       "      <td>265</td>\n",
       "      <td>44</td>\n",
       "      <td>11174</td>\n",
       "      <td>205</td>\n",
       "      <td>50.56</td>\n",
       "      <td>27</td>\n",
       "      <td>63</td>\n",
       "      <td>11</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Player       Span  Match  Innings  NotOut   Runs Highest_score  \\\n",
       "0      SR Tendulkar   1989-2013    200      329      33  15921          248*   \n",
       "1        RT Ponting   1995-2012    168      287      29  13378           257   \n",
       "2         JH Kallis   1995-2013    166      280      40  13289           224   \n",
       "3          R Dravid   1996-2012    164      286      32  13288           270   \n",
       "4           AN Cook   2006-2018    161      291      16  12472           294   \n",
       "5     KC Sangakkara   2000-2015    134      233      17  12400           319   \n",
       "6           BC Lara   1990-2006    131      232       6  11953          400*   \n",
       "7     S Chanderpaul   1994-2015    164      280      49  11867          203*   \n",
       "8  DPMD Jayawardene   1997-2014    149      252      15  11814           374   \n",
       "9         AR Border   1978-1994    156      265      44  11174           205   \n",
       "\n",
       "   Average  Centuries  Half_centuries  Ducks    Country played_for_ICC  \n",
       "0    53.78         51              68     14      INDIA             No  \n",
       "1    51.85         41              62     17        AUS             No  \n",
       "2    55.37         45              58     16     ICC/SA            Yes  \n",
       "3    52.31         36              63      8  ICC/INDIA            Yes  \n",
       "4    45.35         33              57      9        ENG             No  \n",
       "5    57.40         38              52     11         SL             No  \n",
       "6    52.88         34              48     17     ICC/WI            Yes  \n",
       "7    51.37         30              66     15         WI             No  \n",
       "8    49.84         34              50     15         SL             No  \n",
       "9    50.56         27              63     11        AUS             No  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['played_for_ICC'] = df['Country'].apply(icc_check)\n",
    "# df['played_for_INDIA'] = df['Country'].apply(INDIA_check)\n",
    "\n",
    "display(df.head(10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 475,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No     90\n",
       "Yes     7\n",
       "Name: played_for_ICC, dtype: int64"
      ]
     },
     "execution_count": 475,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['played_for_ICC'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Removing \"ICC/\" from the 'Country'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 476,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>Span</th>\n",
       "      <th>Match</th>\n",
       "      <th>Innings</th>\n",
       "      <th>NotOut</th>\n",
       "      <th>Runs</th>\n",
       "      <th>Highest_score</th>\n",
       "      <th>Average</th>\n",
       "      <th>Centuries</th>\n",
       "      <th>Half_centuries</th>\n",
       "      <th>Ducks</th>\n",
       "      <th>Country</th>\n",
       "      <th>played_for_ICC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SR Tendulkar</td>\n",
       "      <td>1989-2013</td>\n",
       "      <td>200</td>\n",
       "      <td>329</td>\n",
       "      <td>33</td>\n",
       "      <td>15921</td>\n",
       "      <td>248*</td>\n",
       "      <td>53.78</td>\n",
       "      <td>51</td>\n",
       "      <td>68</td>\n",
       "      <td>14</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RT Ponting</td>\n",
       "      <td>1995-2012</td>\n",
       "      <td>168</td>\n",
       "      <td>287</td>\n",
       "      <td>29</td>\n",
       "      <td>13378</td>\n",
       "      <td>257</td>\n",
       "      <td>51.85</td>\n",
       "      <td>41</td>\n",
       "      <td>62</td>\n",
       "      <td>17</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JH Kallis</td>\n",
       "      <td>1995-2013</td>\n",
       "      <td>166</td>\n",
       "      <td>280</td>\n",
       "      <td>40</td>\n",
       "      <td>13289</td>\n",
       "      <td>224</td>\n",
       "      <td>55.37</td>\n",
       "      <td>45</td>\n",
       "      <td>58</td>\n",
       "      <td>16</td>\n",
       "      <td>SA</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>R Dravid</td>\n",
       "      <td>1996-2012</td>\n",
       "      <td>164</td>\n",
       "      <td>286</td>\n",
       "      <td>32</td>\n",
       "      <td>13288</td>\n",
       "      <td>270</td>\n",
       "      <td>52.31</td>\n",
       "      <td>36</td>\n",
       "      <td>63</td>\n",
       "      <td>8</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AN Cook</td>\n",
       "      <td>2006-2018</td>\n",
       "      <td>161</td>\n",
       "      <td>291</td>\n",
       "      <td>16</td>\n",
       "      <td>12472</td>\n",
       "      <td>294</td>\n",
       "      <td>45.35</td>\n",
       "      <td>33</td>\n",
       "      <td>57</td>\n",
       "      <td>9</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Player       Span  Match  Innings  NotOut   Runs Highest_score  \\\n",
       "0  SR Tendulkar   1989-2013    200      329      33  15921          248*   \n",
       "1    RT Ponting   1995-2012    168      287      29  13378           257   \n",
       "2     JH Kallis   1995-2013    166      280      40  13289           224   \n",
       "3      R Dravid   1996-2012    164      286      32  13288           270   \n",
       "4       AN Cook   2006-2018    161      291      16  12472           294   \n",
       "\n",
       "   Average  Centuries  Half_centuries  Ducks Country played_for_ICC  \n",
       "0    53.78         51              68     14   INDIA             No  \n",
       "1    51.85         41              62     17     AUS             No  \n",
       "2    55.37         45              58     16      SA            Yes  \n",
       "3    52.31         36              63      8   INDIA            Yes  \n",
       "4    45.35         33              57      9     ENG             No  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['Country'] = df['Country'].str.replace(\"ICC/\", \"\")\n",
    "\n",
    "display(df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking the unique values for each column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 477,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ENG      22\n",
       "AUS      20\n",
       "INDIA    12\n",
       "WI       12\n",
       "SL       10\n",
       "PAK       8\n",
       "SA        7\n",
       "NZ        6\n",
       "Name: Country, dtype: int64"
      ]
     },
     "execution_count": 477,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Country'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Find number of years played"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 479,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df['start_year'] = df['Span'].str[0:4]\n",
    "\n",
    "# df['end_year'] = df['Span'].str[5:]\n",
    "\n",
    "# display(df.head(10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 480,
   "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",
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       "\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>Player</th>\n",
       "      <th>Match</th>\n",
       "      <th>Innings</th>\n",
       "      <th>NotOut</th>\n",
       "      <th>Runs</th>\n",
       "      <th>Highest_score</th>\n",
       "      <th>Average</th>\n",
       "      <th>Centuries</th>\n",
       "      <th>Half_centuries</th>\n",
       "      <th>Ducks</th>\n",
       "      <th>Country</th>\n",
       "      <th>played_for_ICC</th>\n",
       "      <th>start_year</th>\n",
       "      <th>end_year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SR Tendulkar</td>\n",
       "      <td>200</td>\n",
       "      <td>329</td>\n",
       "      <td>33</td>\n",
       "      <td>15921</td>\n",
       "      <td>248*</td>\n",
       "      <td>53.78</td>\n",
       "      <td>51</td>\n",
       "      <td>68</td>\n",
       "      <td>14</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>No</td>\n",
       "      <td>1989</td>\n",
       "      <td>2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RT Ponting</td>\n",
       "      <td>168</td>\n",
       "      <td>287</td>\n",
       "      <td>29</td>\n",
       "      <td>13378</td>\n",
       "      <td>257</td>\n",
       "      <td>51.85</td>\n",
       "      <td>41</td>\n",
       "      <td>62</td>\n",
       "      <td>17</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>1995</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JH Kallis</td>\n",
       "      <td>166</td>\n",
       "      <td>280</td>\n",
       "      <td>40</td>\n",
       "      <td>13289</td>\n",
       "      <td>224</td>\n",
       "      <td>55.37</td>\n",
       "      <td>45</td>\n",
       "      <td>58</td>\n",
       "      <td>16</td>\n",
       "      <td>SA</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1995</td>\n",
       "      <td>2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>R Dravid</td>\n",
       "      <td>164</td>\n",
       "      <td>286</td>\n",
       "      <td>32</td>\n",
       "      <td>13288</td>\n",
       "      <td>270</td>\n",
       "      <td>52.31</td>\n",
       "      <td>36</td>\n",
       "      <td>63</td>\n",
       "      <td>8</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1996</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AN Cook</td>\n",
       "      <td>161</td>\n",
       "      <td>291</td>\n",
       "      <td>16</td>\n",
       "      <td>12472</td>\n",
       "      <td>294</td>\n",
       "      <td>45.35</td>\n",
       "      <td>33</td>\n",
       "      <td>57</td>\n",
       "      <td>9</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>2006</td>\n",
       "      <td>2018</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Player  Match  Innings  NotOut   Runs Highest_score  Average  \\\n",
       "0  SR Tendulkar     200      329      33  15921          248*    53.78   \n",
       "1    RT Ponting     168      287      29  13378           257    51.85   \n",
       "2     JH Kallis     166      280      40  13289           224    55.37   \n",
       "3      R Dravid     164      286      32  13288           270    52.31   \n",
       "4       AN Cook     161      291      16  12472           294    45.35   \n",
       "\n",
       "   Centuries  Half_centuries  Ducks Country played_for_ICC start_year end_year  \n",
       "0         51              68     14   INDIA             No       1989     2013  \n",
       "1         41              62     17     AUS             No       1995     2012  \n",
       "2         45              58     16      SA            Yes       1995     2013  \n",
       "3         36              63      8   INDIA            Yes       1996     2012  \n",
       "4         33              57      9     ENG             No       2006     2018  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# splitting the 'Span' column based on the \"-\"\n",
    "df_span = df['Span'].str.split(\"-\", expand=True)\n",
    "\n",
    "# conccatinating the new dataframe with the main dataframe\n",
    "df = pd.concat([df, df_span], axis=1)\n",
    "\n",
    "# renaming the newly created column names\n",
    "df = df.rename(columns={0: \"start_year\",\n",
    "                        1: \"end_year\"})\n",
    "\n",
    "# removing the \"Span\" column\n",
    "df = df.drop(\"Span\", axis=1)\n",
    "\n",
    "display(df.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 481,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 97 entries, 0 to 96\n",
      "Data columns (total 14 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   Player          97 non-null     object \n",
      " 1   Match           97 non-null     int64  \n",
      " 2   Innings         97 non-null     int64  \n",
      " 3   NotOut          97 non-null     int64  \n",
      " 4   Runs            97 non-null     int64  \n",
      " 5   Highest_score   97 non-null     object \n",
      " 6   Average         97 non-null     float64\n",
      " 7   Centuries       97 non-null     int64  \n",
      " 8   Half_centuries  97 non-null     int64  \n",
      " 9   Ducks           97 non-null     int64  \n",
      " 10  Country         97 non-null     object \n",
      " 11  played_for_ICC  97 non-null     object \n",
      " 12  start_year      97 non-null     object \n",
      " 13  end_year        97 non-null     object \n",
      "dtypes: float64(1), int64(7), object(6)\n",
      "memory usage: 10.7+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Data type conversion**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 482,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 97 entries, 0 to 96\n",
      "Data columns (total 14 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   Player          97 non-null     object \n",
      " 1   Match           97 non-null     int64  \n",
      " 2   Innings         97 non-null     int64  \n",
      " 3   NotOut          97 non-null     int64  \n",
      " 4   Runs            97 non-null     int64  \n",
      " 5   Highest_score   97 non-null     object \n",
      " 6   Average         97 non-null     float64\n",
      " 7   Centuries       97 non-null     int64  \n",
      " 8   Half_centuries  97 non-null     int64  \n",
      " 9   Ducks           97 non-null     int64  \n",
      " 10  Country         97 non-null     object \n",
      " 11  played_for_ICC  97 non-null     object \n",
      " 12  start_year      97 non-null     int64  \n",
      " 13  end_year        97 non-null     int64  \n",
      "dtypes: float64(1), int64(9), object(4)\n",
      "memory usage: 10.7+ KB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "df['start_year'] = df['start_year'].astype('int') \n",
    "df['end_year'] = df['end_year'].astype('int')\n",
    "\n",
    "print(df.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 483,
   "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>Player</th>\n",
       "      <th>Match</th>\n",
       "      <th>Innings</th>\n",
       "      <th>NotOut</th>\n",
       "      <th>Runs</th>\n",
       "      <th>Highest_score</th>\n",
       "      <th>Average</th>\n",
       "      <th>Centuries</th>\n",
       "      <th>Half_centuries</th>\n",
       "      <th>Ducks</th>\n",
       "      <th>Country</th>\n",
       "      <th>played_for_ICC</th>\n",
       "      <th>years_played</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SR Tendulkar</td>\n",
       "      <td>200</td>\n",
       "      <td>329</td>\n",
       "      <td>33</td>\n",
       "      <td>15921</td>\n",
       "      <td>248*</td>\n",
       "      <td>53.78</td>\n",
       "      <td>51</td>\n",
       "      <td>68</td>\n",
       "      <td>14</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>No</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RT Ponting</td>\n",
       "      <td>168</td>\n",
       "      <td>287</td>\n",
       "      <td>29</td>\n",
       "      <td>13378</td>\n",
       "      <td>257</td>\n",
       "      <td>51.85</td>\n",
       "      <td>41</td>\n",
       "      <td>62</td>\n",
       "      <td>17</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JH Kallis</td>\n",
       "      <td>166</td>\n",
       "      <td>280</td>\n",
       "      <td>40</td>\n",
       "      <td>13289</td>\n",
       "      <td>224</td>\n",
       "      <td>55.37</td>\n",
       "      <td>45</td>\n",
       "      <td>58</td>\n",
       "      <td>16</td>\n",
       "      <td>SA</td>\n",
       "      <td>Yes</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>R Dravid</td>\n",
       "      <td>164</td>\n",
       "      <td>286</td>\n",
       "      <td>32</td>\n",
       "      <td>13288</td>\n",
       "      <td>270</td>\n",
       "      <td>52.31</td>\n",
       "      <td>36</td>\n",
       "      <td>63</td>\n",
       "      <td>8</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>Yes</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AN Cook</td>\n",
       "      <td>161</td>\n",
       "      <td>291</td>\n",
       "      <td>16</td>\n",
       "      <td>12472</td>\n",
       "      <td>294</td>\n",
       "      <td>45.35</td>\n",
       "      <td>33</td>\n",
       "      <td>57</td>\n",
       "      <td>9</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>KC Sangakkara</td>\n",
       "      <td>134</td>\n",
       "      <td>233</td>\n",
       "      <td>17</td>\n",
       "      <td>12400</td>\n",
       "      <td>319</td>\n",
       "      <td>57.40</td>\n",
       "      <td>38</td>\n",
       "      <td>52</td>\n",
       "      <td>11</td>\n",
       "      <td>SL</td>\n",
       "      <td>No</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>BC Lara</td>\n",
       "      <td>131</td>\n",
       "      <td>232</td>\n",
       "      <td>6</td>\n",
       "      <td>11953</td>\n",
       "      <td>400*</td>\n",
       "      <td>52.88</td>\n",
       "      <td>34</td>\n",
       "      <td>48</td>\n",
       "      <td>17</td>\n",
       "      <td>WI</td>\n",
       "      <td>Yes</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>S Chanderpaul</td>\n",
       "      <td>164</td>\n",
       "      <td>280</td>\n",
       "      <td>49</td>\n",
       "      <td>11867</td>\n",
       "      <td>203*</td>\n",
       "      <td>51.37</td>\n",
       "      <td>30</td>\n",
       "      <td>66</td>\n",
       "      <td>15</td>\n",
       "      <td>WI</td>\n",
       "      <td>No</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DPMD Jayawardene</td>\n",
       "      <td>149</td>\n",
       "      <td>252</td>\n",
       "      <td>15</td>\n",
       "      <td>11814</td>\n",
       "      <td>374</td>\n",
       "      <td>49.84</td>\n",
       "      <td>34</td>\n",
       "      <td>50</td>\n",
       "      <td>15</td>\n",
       "      <td>SL</td>\n",
       "      <td>No</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>AR Border</td>\n",
       "      <td>156</td>\n",
       "      <td>265</td>\n",
       "      <td>44</td>\n",
       "      <td>11174</td>\n",
       "      <td>205</td>\n",
       "      <td>50.56</td>\n",
       "      <td>27</td>\n",
       "      <td>63</td>\n",
       "      <td>11</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Player  Match  Innings  NotOut   Runs Highest_score  Average  \\\n",
       "0      SR Tendulkar     200      329      33  15921          248*    53.78   \n",
       "1        RT Ponting     168      287      29  13378           257    51.85   \n",
       "2         JH Kallis     166      280      40  13289           224    55.37   \n",
       "3          R Dravid     164      286      32  13288           270    52.31   \n",
       "4           AN Cook     161      291      16  12472           294    45.35   \n",
       "5     KC Sangakkara     134      233      17  12400           319    57.40   \n",
       "6           BC Lara     131      232       6  11953          400*    52.88   \n",
       "7     S Chanderpaul     164      280      49  11867          203*    51.37   \n",
       "8  DPMD Jayawardene     149      252      15  11814           374    49.84   \n",
       "9         AR Border     156      265      44  11174           205    50.56   \n",
       "\n",
       "   Centuries  Half_centuries  Ducks Country played_for_ICC  years_played  \n",
       "0         51              68     14   INDIA             No            24  \n",
       "1         41              62     17     AUS             No            17  \n",
       "2         45              58     16      SA            Yes            18  \n",
       "3         36              63      8   INDIA            Yes            16  \n",
       "4         33              57      9     ENG             No            12  \n",
       "5         38              52     11      SL             No            15  \n",
       "6         34              48     17      WI            Yes            16  \n",
       "7         30              66     15      WI             No            21  \n",
       "8         34              50     15      SL             No            17  \n",
       "9         27              63     11     AUS             No            16  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['years_played'] = df['end_year'] - df['start_year']\n",
    "\n",
    "df = df.drop(['start_year', \"end_year\"], axis=1)\n",
    "\n",
    "display(df.head(10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking the average "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 484,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df['avg'] = df['Runs']/(df['Innings'] - df['NotOut'])\n",
    "# df['avg'] = np.round(df['avg'], 2)\n",
    "\n",
    "# display(df.head(10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Top 10 batsmen: Highest Batting average"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 485,
   "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>Player</th>\n",
       "      <th>Match</th>\n",
       "      <th>Innings</th>\n",
       "      <th>NotOut</th>\n",
       "      <th>Runs</th>\n",
       "      <th>Highest_score</th>\n",
       "      <th>Average</th>\n",
       "      <th>Centuries</th>\n",
       "      <th>Half_centuries</th>\n",
       "      <th>Ducks</th>\n",
       "      <th>Country</th>\n",
       "      <th>played_for_ICC</th>\n",
       "      <th>years_played</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>DG Bradman</td>\n",
       "      <td>52</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "      <td>6996</td>\n",
       "      <td>334</td>\n",
       "      <td>99.94</td>\n",
       "      <td>29</td>\n",
       "      <td>13</td>\n",
       "      <td>7</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>SPD Smith</td>\n",
       "      <td>77</td>\n",
       "      <td>139</td>\n",
       "      <td>17</td>\n",
       "      <td>7540</td>\n",
       "      <td>239</td>\n",
       "      <td>61.80</td>\n",
       "      <td>27</td>\n",
       "      <td>31</td>\n",
       "      <td>5</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>KF Barrington</td>\n",
       "      <td>82</td>\n",
       "      <td>131</td>\n",
       "      <td>15</td>\n",
       "      <td>6806</td>\n",
       "      <td>256</td>\n",
       "      <td>58.67</td>\n",
       "      <td>20</td>\n",
       "      <td>35</td>\n",
       "      <td>5</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>WR Hammond</td>\n",
       "      <td>85</td>\n",
       "      <td>140</td>\n",
       "      <td>16</td>\n",
       "      <td>7249</td>\n",
       "      <td>336*</td>\n",
       "      <td>58.45</td>\n",
       "      <td>22</td>\n",
       "      <td>24</td>\n",
       "      <td>4</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>GS Sobers</td>\n",
       "      <td>93</td>\n",
       "      <td>160</td>\n",
       "      <td>21</td>\n",
       "      <td>8032</td>\n",
       "      <td>365*</td>\n",
       "      <td>57.78</td>\n",
       "      <td>26</td>\n",
       "      <td>30</td>\n",
       "      <td>12</td>\n",
       "      <td>WI</td>\n",
       "      <td>No</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>KC Sangakkara</td>\n",
       "      <td>134</td>\n",
       "      <td>233</td>\n",
       "      <td>17</td>\n",
       "      <td>12400</td>\n",
       "      <td>319</td>\n",
       "      <td>57.40</td>\n",
       "      <td>38</td>\n",
       "      <td>52</td>\n",
       "      <td>11</td>\n",
       "      <td>SL</td>\n",
       "      <td>No</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>JB Hobbs</td>\n",
       "      <td>61</td>\n",
       "      <td>102</td>\n",
       "      <td>7</td>\n",
       "      <td>5410</td>\n",
       "      <td>211</td>\n",
       "      <td>56.94</td>\n",
       "      <td>15</td>\n",
       "      <td>28</td>\n",
       "      <td>4</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>L Hutton</td>\n",
       "      <td>79</td>\n",
       "      <td>138</td>\n",
       "      <td>15</td>\n",
       "      <td>6971</td>\n",
       "      <td>364</td>\n",
       "      <td>56.67</td>\n",
       "      <td>19</td>\n",
       "      <td>33</td>\n",
       "      <td>5</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JH Kallis</td>\n",
       "      <td>166</td>\n",
       "      <td>280</td>\n",
       "      <td>40</td>\n",
       "      <td>13289</td>\n",
       "      <td>224</td>\n",
       "      <td>55.37</td>\n",
       "      <td>45</td>\n",
       "      <td>58</td>\n",
       "      <td>16</td>\n",
       "      <td>SA</td>\n",
       "      <td>Yes</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>KS Williamson</td>\n",
       "      <td>85</td>\n",
       "      <td>148</td>\n",
       "      <td>14</td>\n",
       "      <td>7230</td>\n",
       "      <td>251</td>\n",
       "      <td>53.95</td>\n",
       "      <td>24</td>\n",
       "      <td>33</td>\n",
       "      <td>9</td>\n",
       "      <td>NZ</td>\n",
       "      <td>No</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Player  Match  Innings  NotOut   Runs Highest_score  Average  \\\n",
       "53     DG Bradman      52       80      10   6996           334    99.94   \n",
       "38      SPD Smith      77      139      17   7540           239    61.80   \n",
       "57  KF Barrington      82      131      15   6806           256    58.67   \n",
       "46     WR Hammond      85      140      16   7249          336*    58.45   \n",
       "29      GS Sobers      93      160      21   8032          365*    57.78   \n",
       "5   KC Sangakkara     134      233      17  12400           319    57.40   \n",
       "84       JB Hobbs      61      102       7   5410           211    56.94   \n",
       "55       L Hutton      79      138      15   6971           364    56.67   \n",
       "2       JH Kallis     166      280      40  13289           224    55.37   \n",
       "47  KS Williamson      85      148      14   7230           251    53.95   \n",
       "\n",
       "    Centuries  Half_centuries  Ducks Country played_for_ICC  years_played  \n",
       "53         29              13      7     AUS             No            20  \n",
       "38         27              31      5     AUS             No            11  \n",
       "57         20              35      5     ENG             No            13  \n",
       "46         22              24      4     ENG             No            20  \n",
       "29         26              30     12      WI             No            20  \n",
       "5          38              52     11      SL             No            15  \n",
       "84         15              28      4     ENG             No            22  \n",
       "55         19              33      5     ENG             No            18  \n",
       "2          45              58     16      SA            Yes            18  \n",
       "47         24              33      9      NZ             No            11  "
      ]
     },
     "execution_count": 485,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by='Average', ascending = False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Top 10 batsmen: Highest number of centuries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 486,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>Match</th>\n",
       "      <th>Innings</th>\n",
       "      <th>NotOut</th>\n",
       "      <th>Runs</th>\n",
       "      <th>Highest_score</th>\n",
       "      <th>Average</th>\n",
       "      <th>Centuries</th>\n",
       "      <th>Half_centuries</th>\n",
       "      <th>Ducks</th>\n",
       "      <th>Country</th>\n",
       "      <th>played_for_ICC</th>\n",
       "      <th>years_played</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SR Tendulkar</td>\n",
       "      <td>200</td>\n",
       "      <td>329</td>\n",
       "      <td>33</td>\n",
       "      <td>15921</td>\n",
       "      <td>248*</td>\n",
       "      <td>53.78</td>\n",
       "      <td>51</td>\n",
       "      <td>68</td>\n",
       "      <td>14</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>No</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JH Kallis</td>\n",
       "      <td>166</td>\n",
       "      <td>280</td>\n",
       "      <td>40</td>\n",
       "      <td>13289</td>\n",
       "      <td>224</td>\n",
       "      <td>55.37</td>\n",
       "      <td>45</td>\n",
       "      <td>58</td>\n",
       "      <td>16</td>\n",
       "      <td>SA</td>\n",
       "      <td>Yes</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RT Ponting</td>\n",
       "      <td>168</td>\n",
       "      <td>287</td>\n",
       "      <td>29</td>\n",
       "      <td>13378</td>\n",
       "      <td>257</td>\n",
       "      <td>51.85</td>\n",
       "      <td>41</td>\n",
       "      <td>62</td>\n",
       "      <td>17</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>KC Sangakkara</td>\n",
       "      <td>134</td>\n",
       "      <td>233</td>\n",
       "      <td>17</td>\n",
       "      <td>12400</td>\n",
       "      <td>319</td>\n",
       "      <td>57.40</td>\n",
       "      <td>38</td>\n",
       "      <td>52</td>\n",
       "      <td>11</td>\n",
       "      <td>SL</td>\n",
       "      <td>No</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>R Dravid</td>\n",
       "      <td>164</td>\n",
       "      <td>286</td>\n",
       "      <td>32</td>\n",
       "      <td>13288</td>\n",
       "      <td>270</td>\n",
       "      <td>52.31</td>\n",
       "      <td>36</td>\n",
       "      <td>63</td>\n",
       "      <td>8</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>Yes</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DPMD Jayawardene</td>\n",
       "      <td>149</td>\n",
       "      <td>252</td>\n",
       "      <td>15</td>\n",
       "      <td>11814</td>\n",
       "      <td>374</td>\n",
       "      <td>49.84</td>\n",
       "      <td>34</td>\n",
       "      <td>50</td>\n",
       "      <td>15</td>\n",
       "      <td>SL</td>\n",
       "      <td>No</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>BC Lara</td>\n",
       "      <td>131</td>\n",
       "      <td>232</td>\n",
       "      <td>6</td>\n",
       "      <td>11953</td>\n",
       "      <td>400*</td>\n",
       "      <td>52.88</td>\n",
       "      <td>34</td>\n",
       "      <td>48</td>\n",
       "      <td>17</td>\n",
       "      <td>WI</td>\n",
       "      <td>Yes</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>SM Gavaskar</td>\n",
       "      <td>125</td>\n",
       "      <td>214</td>\n",
       "      <td>16</td>\n",
       "      <td>10122</td>\n",
       "      <td>236*</td>\n",
       "      <td>51.12</td>\n",
       "      <td>34</td>\n",
       "      <td>45</td>\n",
       "      <td>12</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>No</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Younis Khan</td>\n",
       "      <td>118</td>\n",
       "      <td>213</td>\n",
       "      <td>19</td>\n",
       "      <td>10099</td>\n",
       "      <td>313</td>\n",
       "      <td>52.05</td>\n",
       "      <td>34</td>\n",
       "      <td>33</td>\n",
       "      <td>19</td>\n",
       "      <td>PAK</td>\n",
       "      <td>No</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AN Cook</td>\n",
       "      <td>161</td>\n",
       "      <td>291</td>\n",
       "      <td>16</td>\n",
       "      <td>12472</td>\n",
       "      <td>294</td>\n",
       "      <td>45.35</td>\n",
       "      <td>33</td>\n",
       "      <td>57</td>\n",
       "      <td>9</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Player  Match  Innings  NotOut   Runs Highest_score  Average  \\\n",
       "0       SR Tendulkar     200      329      33  15921          248*    53.78   \n",
       "2          JH Kallis     166      280      40  13289           224    55.37   \n",
       "1         RT Ponting     168      287      29  13378           257    51.85   \n",
       "5      KC Sangakkara     134      233      17  12400           319    57.40   \n",
       "3           R Dravid     164      286      32  13288           270    52.31   \n",
       "8   DPMD Jayawardene     149      252      15  11814           374    49.84   \n",
       "6            BC Lara     131      232       6  11953          400*    52.88   \n",
       "11       SM Gavaskar     125      214      16  10122          236*    51.12   \n",
       "12       Younis Khan     118      213      19  10099           313    52.05   \n",
       "4            AN Cook     161      291      16  12472           294    45.35   \n",
       "\n",
       "    Centuries  Half_centuries  Ducks Country played_for_ICC  years_played  \n",
       "0          51              68     14   INDIA             No            24  \n",
       "2          45              58     16      SA            Yes            18  \n",
       "1          41              62     17     AUS             No            17  \n",
       "5          38              52     11      SL             No            15  \n",
       "3          36              63      8   INDIA            Yes            16  \n",
       "8          34              50     15      SL             No            17  \n",
       "6          34              48     17      WI            Yes            16  \n",
       "11         34              45     12   INDIA             No            16  \n",
       "12         34              33     19     PAK             No            17  \n",
       "4          33              57      9     ENG             No            12  "
      ]
     },
     "execution_count": 486,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by=['Centuries', \"Half_centuries\"], ascending = False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Top 10 batsmen: Highest number of half centuries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 487,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>Match</th>\n",
       "      <th>Innings</th>\n",
       "      <th>NotOut</th>\n",
       "      <th>Runs</th>\n",
       "      <th>Highest_score</th>\n",
       "      <th>Average</th>\n",
       "      <th>Centuries</th>\n",
       "      <th>Half_centuries</th>\n",
       "      <th>Ducks</th>\n",
       "      <th>Country</th>\n",
       "      <th>played_for_ICC</th>\n",
       "      <th>years_played</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SR Tendulkar</td>\n",
       "      <td>200</td>\n",
       "      <td>329</td>\n",
       "      <td>33</td>\n",
       "      <td>15921</td>\n",
       "      <td>248*</td>\n",
       "      <td>53.78</td>\n",
       "      <td>51</td>\n",
       "      <td>68</td>\n",
       "      <td>14</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>No</td>\n",
       "      <td>24</td>\n",
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       "      <th>7</th>\n",
       "      <td>S Chanderpaul</td>\n",
       "      <td>164</td>\n",
       "      <td>280</td>\n",
       "      <td>49</td>\n",
       "      <td>11867</td>\n",
       "      <td>203*</td>\n",
       "      <td>51.37</td>\n",
       "      <td>30</td>\n",
       "      <td>66</td>\n",
       "      <td>15</td>\n",
       "      <td>WI</td>\n",
       "      <td>No</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>R Dravid</td>\n",
       "      <td>164</td>\n",
       "      <td>286</td>\n",
       "      <td>32</td>\n",
       "      <td>13288</td>\n",
       "      <td>270</td>\n",
       "      <td>52.31</td>\n",
       "      <td>36</td>\n",
       "      <td>63</td>\n",
       "      <td>8</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>Yes</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>AR Border</td>\n",
       "      <td>156</td>\n",
       "      <td>265</td>\n",
       "      <td>44</td>\n",
       "      <td>11174</td>\n",
       "      <td>205</td>\n",
       "      <td>50.56</td>\n",
       "      <td>27</td>\n",
       "      <td>63</td>\n",
       "      <td>11</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RT Ponting</td>\n",
       "      <td>168</td>\n",
       "      <td>287</td>\n",
       "      <td>29</td>\n",
       "      <td>13378</td>\n",
       "      <td>257</td>\n",
       "      <td>51.85</td>\n",
       "      <td>41</td>\n",
       "      <td>62</td>\n",
       "      <td>17</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JH Kallis</td>\n",
       "      <td>166</td>\n",
       "      <td>280</td>\n",
       "      <td>40</td>\n",
       "      <td>13289</td>\n",
       "      <td>224</td>\n",
       "      <td>55.37</td>\n",
       "      <td>45</td>\n",
       "      <td>58</td>\n",
       "      <td>16</td>\n",
       "      <td>SA</td>\n",
       "      <td>Yes</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AN Cook</td>\n",
       "      <td>161</td>\n",
       "      <td>291</td>\n",
       "      <td>16</td>\n",
       "      <td>12472</td>\n",
       "      <td>294</td>\n",
       "      <td>45.35</td>\n",
       "      <td>33</td>\n",
       "      <td>57</td>\n",
       "      <td>9</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>VVS Laxman</td>\n",
       "      <td>134</td>\n",
       "      <td>225</td>\n",
       "      <td>34</td>\n",
       "      <td>8781</td>\n",
       "      <td>281</td>\n",
       "      <td>45.97</td>\n",
       "      <td>17</td>\n",
       "      <td>56</td>\n",
       "      <td>14</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>No</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>KC Sangakkara</td>\n",
       "      <td>134</td>\n",
       "      <td>233</td>\n",
       "      <td>17</td>\n",
       "      <td>12400</td>\n",
       "      <td>319</td>\n",
       "      <td>57.40</td>\n",
       "      <td>38</td>\n",
       "      <td>52</td>\n",
       "      <td>11</td>\n",
       "      <td>SL</td>\n",
       "      <td>No</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DPMD Jayawardene</td>\n",
       "      <td>149</td>\n",
       "      <td>252</td>\n",
       "      <td>15</td>\n",
       "      <td>11814</td>\n",
       "      <td>374</td>\n",
       "      <td>49.84</td>\n",
       "      <td>34</td>\n",
       "      <td>50</td>\n",
       "      <td>15</td>\n",
       "      <td>SL</td>\n",
       "      <td>No</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Player  Match  Innings  NotOut   Runs Highest_score  Average  \\\n",
       "0       SR Tendulkar     200      329      33  15921          248*    53.78   \n",
       "7      S Chanderpaul     164      280      49  11867          203*    51.37   \n",
       "3           R Dravid     164      286      32  13288           270    52.31   \n",
       "9          AR Border     156      265      44  11174           205    50.56   \n",
       "1         RT Ponting     168      287      29  13378           257    51.85   \n",
       "2          JH Kallis     166      280      40  13289           224    55.37   \n",
       "4            AN Cook     161      291      16  12472           294    45.35   \n",
       "18        VVS Laxman     134      225      34   8781           281    45.97   \n",
       "5      KC Sangakkara     134      233      17  12400           319    57.40   \n",
       "8   DPMD Jayawardene     149      252      15  11814           374    49.84   \n",
       "\n",
       "    Centuries  Half_centuries  Ducks Country played_for_ICC  years_played  \n",
       "0          51              68     14   INDIA             No            24  \n",
       "7          30              66     15      WI             No            21  \n",
       "3          36              63      8   INDIA            Yes            16  \n",
       "9          27              63     11     AUS             No            16  \n",
       "1          41              62     17     AUS             No            17  \n",
       "2          45              58     16      SA            Yes            18  \n",
       "4          33              57      9     ENG             No            12  \n",
       "18         17              56     14   INDIA             No            16  \n",
       "5          38              52     11      SL             No            15  \n",
       "8          34              50     15      SL             No            17  "
      ]
     },
     "execution_count": 487,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by=\"Half_centuries\", ascending = False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Top 10 batsmen: Highest number of years played"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 488,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\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>Player</th>\n",
       "      <th>Match</th>\n",
       "      <th>Innings</th>\n",
       "      <th>NotOut</th>\n",
       "      <th>Runs</th>\n",
       "      <th>Highest_score</th>\n",
       "      <th>Average</th>\n",
       "      <th>Centuries</th>\n",
       "      <th>Half_centuries</th>\n",
       "      <th>Ducks</th>\n",
       "      <th>Country</th>\n",
       "      <th>played_for_ICC</th>\n",
       "      <th>years_played</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SR Tendulkar</td>\n",
       "      <td>200</td>\n",
       "      <td>329</td>\n",
       "      <td>33</td>\n",
       "      <td>15921</td>\n",
       "      <td>248*</td>\n",
       "      <td>53.78</td>\n",
       "      <td>51</td>\n",
       "      <td>68</td>\n",
       "      <td>14</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>No</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>JB Hobbs</td>\n",
       "      <td>61</td>\n",
       "      <td>102</td>\n",
       "      <td>7</td>\n",
       "      <td>5410</td>\n",
       "      <td>211</td>\n",
       "      <td>56.94</td>\n",
       "      <td>15</td>\n",
       "      <td>28</td>\n",
       "      <td>4</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>MC Cowdrey</td>\n",
       "      <td>114</td>\n",
       "      <td>188</td>\n",
       "      <td>15</td>\n",
       "      <td>7624</td>\n",
       "      <td>182</td>\n",
       "      <td>44.06</td>\n",
       "      <td>22</td>\n",
       "      <td>38</td>\n",
       "      <td>9</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>S Chanderpaul</td>\n",
       "      <td>164</td>\n",
       "      <td>280</td>\n",
       "      <td>49</td>\n",
       "      <td>11867</td>\n",
       "      <td>203*</td>\n",
       "      <td>51.37</td>\n",
       "      <td>30</td>\n",
       "      <td>66</td>\n",
       "      <td>15</td>\n",
       "      <td>WI</td>\n",
       "      <td>No</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>DG Bradman</td>\n",
       "      <td>52</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "      <td>6996</td>\n",
       "      <td>334</td>\n",
       "      <td>99.94</td>\n",
       "      <td>29</td>\n",
       "      <td>13</td>\n",
       "      <td>7</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>DCS Compton</td>\n",
       "      <td>78</td>\n",
       "      <td>131</td>\n",
       "      <td>15</td>\n",
       "      <td>5807</td>\n",
       "      <td>278</td>\n",
       "      <td>50.06</td>\n",
       "      <td>17</td>\n",
       "      <td>28</td>\n",
       "      <td>10</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>GS Sobers</td>\n",
       "      <td>93</td>\n",
       "      <td>160</td>\n",
       "      <td>21</td>\n",
       "      <td>8032</td>\n",
       "      <td>365*</td>\n",
       "      <td>57.78</td>\n",
       "      <td>26</td>\n",
       "      <td>30</td>\n",
       "      <td>12</td>\n",
       "      <td>WI</td>\n",
       "      <td>No</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>GA Gooch</td>\n",
       "      <td>118</td>\n",
       "      <td>215</td>\n",
       "      <td>6</td>\n",
       "      <td>8900</td>\n",
       "      <td>333</td>\n",
       "      <td>42.58</td>\n",
       "      <td>20</td>\n",
       "      <td>46</td>\n",
       "      <td>13</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>WR Hammond</td>\n",
       "      <td>85</td>\n",
       "      <td>140</td>\n",
       "      <td>16</td>\n",
       "      <td>7249</td>\n",
       "      <td>336*</td>\n",
       "      <td>58.45</td>\n",
       "      <td>22</td>\n",
       "      <td>24</td>\n",
       "      <td>4</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>CH Lloyd</td>\n",
       "      <td>110</td>\n",
       "      <td>175</td>\n",
       "      <td>14</td>\n",
       "      <td>7515</td>\n",
       "      <td>242*</td>\n",
       "      <td>46.67</td>\n",
       "      <td>19</td>\n",
       "      <td>39</td>\n",
       "      <td>4</td>\n",
       "      <td>WI</td>\n",
       "      <td>No</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Player  Match  Innings  NotOut   Runs Highest_score  Average  \\\n",
       "0    SR Tendulkar     200      329      33  15921          248*    53.78   \n",
       "84       JB Hobbs      61      102       7   5410           211    56.94   \n",
       "34     MC Cowdrey     114      188      15   7624           182    44.06   \n",
       "7   S Chanderpaul     164      280      49  11867          203*    51.37   \n",
       "53     DG Bradman      52       80      10   6996           334    99.94   \n",
       "73    DCS Compton      78      131      15   5807           278    50.06   \n",
       "29      GS Sobers      93      160      21   8032          365*    57.78   \n",
       "15       GA Gooch     118      215       6   8900           333    42.58   \n",
       "46     WR Hammond      85      140      16   7249          336*    58.45   \n",
       "41       CH Lloyd     110      175      14   7515          242*    46.67   \n",
       "\n",
       "    Centuries  Half_centuries  Ducks Country played_for_ICC  years_played  \n",
       "0          51              68     14   INDIA             No            24  \n",
       "84         15              28      4     ENG             No            22  \n",
       "34         22              38      9     ENG             No            21  \n",
       "7          30              66     15      WI             No            21  \n",
       "53         29              13      7     AUS             No            20  \n",
       "73         17              28     10     ENG             No            20  \n",
       "29         26              30     12      WI             No            20  \n",
       "15         20              46     13     ENG             No            20  \n",
       "46         22              24      4     ENG             No            20  \n",
       "41         19              39      4      WI             No            19  "
      ]
     },
     "execution_count": 488,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by=\"years_played\", ascending = False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Top 10 batsmen: Highest number of matches played"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 489,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>Match</th>\n",
       "      <th>Innings</th>\n",
       "      <th>NotOut</th>\n",
       "      <th>Runs</th>\n",
       "      <th>Highest_score</th>\n",
       "      <th>Average</th>\n",
       "      <th>Centuries</th>\n",
       "      <th>Half_centuries</th>\n",
       "      <th>Ducks</th>\n",
       "      <th>Country</th>\n",
       "      <th>played_for_ICC</th>\n",
       "      <th>years_played</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SR Tendulkar</td>\n",
       "      <td>200</td>\n",
       "      <td>329</td>\n",
       "      <td>33</td>\n",
       "      <td>15921</td>\n",
       "      <td>248*</td>\n",
       "      <td>53.78</td>\n",
       "      <td>51</td>\n",
       "      <td>68</td>\n",
       "      <td>14</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>No</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RT Ponting</td>\n",
       "      <td>168</td>\n",
       "      <td>287</td>\n",
       "      <td>29</td>\n",
       "      <td>13378</td>\n",
       "      <td>257</td>\n",
       "      <td>51.85</td>\n",
       "      <td>41</td>\n",
       "      <td>62</td>\n",
       "      <td>17</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>SR Waugh</td>\n",
       "      <td>168</td>\n",
       "      <td>260</td>\n",
       "      <td>46</td>\n",
       "      <td>10927</td>\n",
       "      <td>200</td>\n",
       "      <td>51.06</td>\n",
       "      <td>32</td>\n",
       "      <td>50</td>\n",
       "      <td>22</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JH Kallis</td>\n",
       "      <td>166</td>\n",
       "      <td>280</td>\n",
       "      <td>40</td>\n",
       "      <td>13289</td>\n",
       "      <td>224</td>\n",
       "      <td>55.37</td>\n",
       "      <td>45</td>\n",
       "      <td>58</td>\n",
       "      <td>16</td>\n",
       "      <td>SA</td>\n",
       "      <td>Yes</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>R Dravid</td>\n",
       "      <td>164</td>\n",
       "      <td>286</td>\n",
       "      <td>32</td>\n",
       "      <td>13288</td>\n",
       "      <td>270</td>\n",
       "      <td>52.31</td>\n",
       "      <td>36</td>\n",
       "      <td>63</td>\n",
       "      <td>8</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>Yes</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>S Chanderpaul</td>\n",
       "      <td>164</td>\n",
       "      <td>280</td>\n",
       "      <td>49</td>\n",
       "      <td>11867</td>\n",
       "      <td>203*</td>\n",
       "      <td>51.37</td>\n",
       "      <td>30</td>\n",
       "      <td>66</td>\n",
       "      <td>15</td>\n",
       "      <td>WI</td>\n",
       "      <td>No</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AN Cook</td>\n",
       "      <td>161</td>\n",
       "      <td>291</td>\n",
       "      <td>16</td>\n",
       "      <td>12472</td>\n",
       "      <td>294</td>\n",
       "      <td>45.35</td>\n",
       "      <td>33</td>\n",
       "      <td>57</td>\n",
       "      <td>9</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>AR Border</td>\n",
       "      <td>156</td>\n",
       "      <td>265</td>\n",
       "      <td>44</td>\n",
       "      <td>11174</td>\n",
       "      <td>205</td>\n",
       "      <td>50.56</td>\n",
       "      <td>27</td>\n",
       "      <td>63</td>\n",
       "      <td>11</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DPMD Jayawardene</td>\n",
       "      <td>149</td>\n",
       "      <td>252</td>\n",
       "      <td>15</td>\n",
       "      <td>11814</td>\n",
       "      <td>374</td>\n",
       "      <td>49.84</td>\n",
       "      <td>34</td>\n",
       "      <td>50</td>\n",
       "      <td>15</td>\n",
       "      <td>SL</td>\n",
       "      <td>No</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>MV Boucher</td>\n",
       "      <td>147</td>\n",
       "      <td>206</td>\n",
       "      <td>24</td>\n",
       "      <td>5515</td>\n",
       "      <td>125</td>\n",
       "      <td>30.30</td>\n",
       "      <td>5</td>\n",
       "      <td>35</td>\n",
       "      <td>17</td>\n",
       "      <td>SA</td>\n",
       "      <td>Yes</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Player  Match  Innings  NotOut   Runs Highest_score  Average  \\\n",
       "0       SR Tendulkar     200      329      33  15921          248*    53.78   \n",
       "1         RT Ponting     168      287      29  13378           257    51.85   \n",
       "10          SR Waugh     168      260      46  10927           200    51.06   \n",
       "2          JH Kallis     166      280      40  13289           224    55.37   \n",
       "3           R Dravid     164      286      32  13288           270    52.31   \n",
       "7      S Chanderpaul     164      280      49  11867          203*    51.37   \n",
       "4            AN Cook     161      291      16  12472           294    45.35   \n",
       "9          AR Border     156      265      44  11174           205    50.56   \n",
       "8   DPMD Jayawardene     149      252      15  11814           374    49.84   \n",
       "79        MV Boucher     147      206      24   5515           125    30.30   \n",
       "\n",
       "    Centuries  Half_centuries  Ducks Country played_for_ICC  years_played  \n",
       "0          51              68     14   INDIA             No            24  \n",
       "1          41              62     17     AUS             No            17  \n",
       "10         32              50     22     AUS             No            19  \n",
       "2          45              58     16      SA            Yes            18  \n",
       "3          36              63      8   INDIA            Yes            16  \n",
       "7          30              66     15      WI             No            21  \n",
       "4          33              57      9     ENG             No            12  \n",
       "9          27              63     11     AUS             No            16  \n",
       "8          34              50     15      SL             No            17  \n",
       "79          5              35     17      SA            Yes            15  "
      ]
     },
     "execution_count": 489,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by=\"Match\", ascending = False).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 490,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>Match</th>\n",
       "      <th>Innings</th>\n",
       "      <th>NotOut</th>\n",
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       "      <th>years_played</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SR Tendulkar</td>\n",
       "      <td>200</td>\n",
       "      <td>329</td>\n",
       "      <td>33</td>\n",
       "      <td>15921</td>\n",
       "      <td>248*</td>\n",
       "      <td>53.78</td>\n",
       "      <td>51</td>\n",
       "      <td>68</td>\n",
       "      <td>14</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>No</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RT Ponting</td>\n",
       "      <td>168</td>\n",
       "      <td>287</td>\n",
       "      <td>29</td>\n",
       "      <td>13378</td>\n",
       "      <td>257</td>\n",
       "      <td>51.85</td>\n",
       "      <td>41</td>\n",
       "      <td>62</td>\n",
       "      <td>17</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JH Kallis</td>\n",
       "      <td>166</td>\n",
       "      <td>280</td>\n",
       "      <td>40</td>\n",
       "      <td>13289</td>\n",
       "      <td>224</td>\n",
       "      <td>55.37</td>\n",
       "      <td>45</td>\n",
       "      <td>58</td>\n",
       "      <td>16</td>\n",
       "      <td>SA</td>\n",
       "      <td>Yes</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>R Dravid</td>\n",
       "      <td>164</td>\n",
       "      <td>286</td>\n",
       "      <td>32</td>\n",
       "      <td>13288</td>\n",
       "      <td>270</td>\n",
       "      <td>52.31</td>\n",
       "      <td>36</td>\n",
       "      <td>63</td>\n",
       "      <td>8</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>Yes</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AN Cook</td>\n",
       "      <td>161</td>\n",
       "      <td>291</td>\n",
       "      <td>16</td>\n",
       "      <td>12472</td>\n",
       "      <td>294</td>\n",
       "      <td>45.35</td>\n",
       "      <td>33</td>\n",
       "      <td>57</td>\n",
       "      <td>9</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>KC Sangakkara</td>\n",
       "      <td>134</td>\n",
       "      <td>233</td>\n",
       "      <td>17</td>\n",
       "      <td>12400</td>\n",
       "      <td>319</td>\n",
       "      <td>57.40</td>\n",
       "      <td>38</td>\n",
       "      <td>52</td>\n",
       "      <td>11</td>\n",
       "      <td>SL</td>\n",
       "      <td>No</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>BC Lara</td>\n",
       "      <td>131</td>\n",
       "      <td>232</td>\n",
       "      <td>6</td>\n",
       "      <td>11953</td>\n",
       "      <td>400*</td>\n",
       "      <td>52.88</td>\n",
       "      <td>34</td>\n",
       "      <td>48</td>\n",
       "      <td>17</td>\n",
       "      <td>WI</td>\n",
       "      <td>Yes</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>S Chanderpaul</td>\n",
       "      <td>164</td>\n",
       "      <td>280</td>\n",
       "      <td>49</td>\n",
       "      <td>11867</td>\n",
       "      <td>203*</td>\n",
       "      <td>51.37</td>\n",
       "      <td>30</td>\n",
       "      <td>66</td>\n",
       "      <td>15</td>\n",
       "      <td>WI</td>\n",
       "      <td>No</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DPMD Jayawardene</td>\n",
       "      <td>149</td>\n",
       "      <td>252</td>\n",
       "      <td>15</td>\n",
       "      <td>11814</td>\n",
       "      <td>374</td>\n",
       "      <td>49.84</td>\n",
       "      <td>34</td>\n",
       "      <td>50</td>\n",
       "      <td>15</td>\n",
       "      <td>SL</td>\n",
       "      <td>No</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>AR Border</td>\n",
       "      <td>156</td>\n",
       "      <td>265</td>\n",
       "      <td>44</td>\n",
       "      <td>11174</td>\n",
       "      <td>205</td>\n",
       "      <td>50.56</td>\n",
       "      <td>27</td>\n",
       "      <td>63</td>\n",
       "      <td>11</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Player  Match  Innings  NotOut   Runs Highest_score  Average  \\\n",
       "0      SR Tendulkar     200      329      33  15921          248*    53.78   \n",
       "1        RT Ponting     168      287      29  13378           257    51.85   \n",
       "2         JH Kallis     166      280      40  13289           224    55.37   \n",
       "3          R Dravid     164      286      32  13288           270    52.31   \n",
       "4           AN Cook     161      291      16  12472           294    45.35   \n",
       "5     KC Sangakkara     134      233      17  12400           319    57.40   \n",
       "6           BC Lara     131      232       6  11953          400*    52.88   \n",
       "7     S Chanderpaul     164      280      49  11867          203*    51.37   \n",
       "8  DPMD Jayawardene     149      252      15  11814           374    49.84   \n",
       "9         AR Border     156      265      44  11174           205    50.56   \n",
       "\n",
       "   Centuries  Half_centuries  Ducks Country played_for_ICC  years_played  \n",
       "0         51              68     14   INDIA             No            24  \n",
       "1         41              62     17     AUS             No            17  \n",
       "2         45              58     16      SA            Yes            18  \n",
       "3         36              63      8   INDIA            Yes            16  \n",
       "4         33              57      9     ENG             No            12  \n",
       "5         38              52     11      SL             No            15  \n",
       "6         34              48     17      WI            Yes            16  \n",
       "7         30              66     15      WI             No            21  \n",
       "8         34              50     15      SL             No            17  \n",
       "9         27              63     11     AUS             No            16  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(df.head(10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Removing the * symbol from the Highest_Score column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 491,
   "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>Player</th>\n",
       "      <th>Match</th>\n",
       "      <th>Innings</th>\n",
       "      <th>NotOut</th>\n",
       "      <th>Runs</th>\n",
       "      <th>Highest_score</th>\n",
       "      <th>Average</th>\n",
       "      <th>Centuries</th>\n",
       "      <th>Half_centuries</th>\n",
       "      <th>Ducks</th>\n",
       "      <th>Country</th>\n",
       "      <th>played_for_ICC</th>\n",
       "      <th>years_played</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SR Tendulkar</td>\n",
       "      <td>200</td>\n",
       "      <td>329</td>\n",
       "      <td>33</td>\n",
       "      <td>15921</td>\n",
       "      <td>248</td>\n",
       "      <td>53.78</td>\n",
       "      <td>51</td>\n",
       "      <td>68</td>\n",
       "      <td>14</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>No</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RT Ponting</td>\n",
       "      <td>168</td>\n",
       "      <td>287</td>\n",
       "      <td>29</td>\n",
       "      <td>13378</td>\n",
       "      <td>257</td>\n",
       "      <td>51.85</td>\n",
       "      <td>41</td>\n",
       "      <td>62</td>\n",
       "      <td>17</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JH Kallis</td>\n",
       "      <td>166</td>\n",
       "      <td>280</td>\n",
       "      <td>40</td>\n",
       "      <td>13289</td>\n",
       "      <td>224</td>\n",
       "      <td>55.37</td>\n",
       "      <td>45</td>\n",
       "      <td>58</td>\n",
       "      <td>16</td>\n",
       "      <td>SA</td>\n",
       "      <td>Yes</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>R Dravid</td>\n",
       "      <td>164</td>\n",
       "      <td>286</td>\n",
       "      <td>32</td>\n",
       "      <td>13288</td>\n",
       "      <td>270</td>\n",
       "      <td>52.31</td>\n",
       "      <td>36</td>\n",
       "      <td>63</td>\n",
       "      <td>8</td>\n",
       "      <td>INDIA</td>\n",
       "      <td>Yes</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AN Cook</td>\n",
       "      <td>161</td>\n",
       "      <td>291</td>\n",
       "      <td>16</td>\n",
       "      <td>12472</td>\n",
       "      <td>294</td>\n",
       "      <td>45.35</td>\n",
       "      <td>33</td>\n",
       "      <td>57</td>\n",
       "      <td>9</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>KC Sangakkara</td>\n",
       "      <td>134</td>\n",
       "      <td>233</td>\n",
       "      <td>17</td>\n",
       "      <td>12400</td>\n",
       "      <td>319</td>\n",
       "      <td>57.40</td>\n",
       "      <td>38</td>\n",
       "      <td>52</td>\n",
       "      <td>11</td>\n",
       "      <td>SL</td>\n",
       "      <td>No</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>BC Lara</td>\n",
       "      <td>131</td>\n",
       "      <td>232</td>\n",
       "      <td>6</td>\n",
       "      <td>11953</td>\n",
       "      <td>400</td>\n",
       "      <td>52.88</td>\n",
       "      <td>34</td>\n",
       "      <td>48</td>\n",
       "      <td>17</td>\n",
       "      <td>WI</td>\n",
       "      <td>Yes</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>S Chanderpaul</td>\n",
       "      <td>164</td>\n",
       "      <td>280</td>\n",
       "      <td>49</td>\n",
       "      <td>11867</td>\n",
       "      <td>203</td>\n",
       "      <td>51.37</td>\n",
       "      <td>30</td>\n",
       "      <td>66</td>\n",
       "      <td>15</td>\n",
       "      <td>WI</td>\n",
       "      <td>No</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DPMD Jayawardene</td>\n",
       "      <td>149</td>\n",
       "      <td>252</td>\n",
       "      <td>15</td>\n",
       "      <td>11814</td>\n",
       "      <td>374</td>\n",
       "      <td>49.84</td>\n",
       "      <td>34</td>\n",
       "      <td>50</td>\n",
       "      <td>15</td>\n",
       "      <td>SL</td>\n",
       "      <td>No</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>AR Border</td>\n",
       "      <td>156</td>\n",
       "      <td>265</td>\n",
       "      <td>44</td>\n",
       "      <td>11174</td>\n",
       "      <td>205</td>\n",
       "      <td>50.56</td>\n",
       "      <td>27</td>\n",
       "      <td>63</td>\n",
       "      <td>11</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Player  Match  Innings  NotOut   Runs  Highest_score  Average  \\\n",
       "0      SR Tendulkar     200      329      33  15921            248    53.78   \n",
       "1        RT Ponting     168      287      29  13378            257    51.85   \n",
       "2         JH Kallis     166      280      40  13289            224    55.37   \n",
       "3          R Dravid     164      286      32  13288            270    52.31   \n",
       "4           AN Cook     161      291      16  12472            294    45.35   \n",
       "5     KC Sangakkara     134      233      17  12400            319    57.40   \n",
       "6           BC Lara     131      232       6  11953            400    52.88   \n",
       "7     S Chanderpaul     164      280      49  11867            203    51.37   \n",
       "8  DPMD Jayawardene     149      252      15  11814            374    49.84   \n",
       "9         AR Border     156      265      44  11174            205    50.56   \n",
       "\n",
       "   Centuries  Half_centuries  Ducks Country played_for_ICC  years_played  \n",
       "0         51              68     14   INDIA             No            24  \n",
       "1         41              62     17     AUS             No            17  \n",
       "2         45              58     16      SA            Yes            18  \n",
       "3         36              63      8   INDIA            Yes            16  \n",
       "4         33              57      9     ENG             No            12  \n",
       "5         38              52     11      SL             No            15  \n",
       "6         34              48     17      WI            Yes            16  \n",
       "7         30              66     15      WI             No            21  \n",
       "8         34              50     15      SL             No            17  \n",
       "9         27              63     11     AUS             No            16  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 97 entries, 0 to 96\n",
      "Data columns (total 13 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   Player          97 non-null     object \n",
      " 1   Match           97 non-null     int64  \n",
      " 2   Innings         97 non-null     int64  \n",
      " 3   NotOut          97 non-null     int64  \n",
      " 4   Runs            97 non-null     int64  \n",
      " 5   Highest_score   97 non-null     int64  \n",
      " 6   Average         97 non-null     float64\n",
      " 7   Centuries       97 non-null     int64  \n",
      " 8   Half_centuries  97 non-null     int64  \n",
      " 9   Ducks           97 non-null     int64  \n",
      " 10  Country         97 non-null     object \n",
      " 11  played_for_ICC  97 non-null     object \n",
      " 12  years_played    97 non-null     int64  \n",
      "dtypes: float64(1), int64(9), object(3)\n",
      "memory usage: 10.0+ KB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "def star_remover(x):\n",
    "    x = str(x)\n",
    "    if \"*\" in x:\n",
    "        return x.replace(\"*\", \"\")\n",
    "    else:\n",
    "        return x\n",
    "\n",
    "\n",
    "df['Highest_score'] = df['Highest_score'].apply(star_remover)\n",
    "df['Highest_score'] = df['Highest_score'].astype('int')\n",
    "\n",
    "display(df.head(10))\n",
    "print(df.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 492,
   "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>Player</th>\n",
       "      <th>Match</th>\n",
       "      <th>Innings</th>\n",
       "      <th>NotOut</th>\n",
       "      <th>Runs</th>\n",
       "      <th>Highest_score</th>\n",
       "      <th>Average</th>\n",
       "      <th>Centuries</th>\n",
       "      <th>Half_centuries</th>\n",
       "      <th>Ducks</th>\n",
       "      <th>Country</th>\n",
       "      <th>played_for_ICC</th>\n",
       "      <th>years_played</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>BC Lara</td>\n",
       "      <td>131</td>\n",
       "      <td>232</td>\n",
       "      <td>6</td>\n",
       "      <td>11953</td>\n",
       "      <td>400</td>\n",
       "      <td>52.88</td>\n",
       "      <td>34</td>\n",
       "      <td>48</td>\n",
       "      <td>17</td>\n",
       "      <td>WI</td>\n",
       "      <td>Yes</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>ML Hayden</td>\n",
       "      <td>103</td>\n",
       "      <td>184</td>\n",
       "      <td>14</td>\n",
       "      <td>8625</td>\n",
       "      <td>380</td>\n",
       "      <td>50.73</td>\n",
       "      <td>30</td>\n",
       "      <td>29</td>\n",
       "      <td>14</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DPMD Jayawardene</td>\n",
       "      <td>149</td>\n",
       "      <td>252</td>\n",
       "      <td>15</td>\n",
       "      <td>11814</td>\n",
       "      <td>374</td>\n",
       "      <td>49.84</td>\n",
       "      <td>34</td>\n",
       "      <td>50</td>\n",
       "      <td>15</td>\n",
       "      <td>SL</td>\n",
       "      <td>No</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>GS Sobers</td>\n",
       "      <td>93</td>\n",
       "      <td>160</td>\n",
       "      <td>21</td>\n",
       "      <td>8032</td>\n",
       "      <td>365</td>\n",
       "      <td>57.78</td>\n",
       "      <td>26</td>\n",
       "      <td>30</td>\n",
       "      <td>12</td>\n",
       "      <td>WI</td>\n",
       "      <td>No</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>L Hutton</td>\n",
       "      <td>79</td>\n",
       "      <td>138</td>\n",
       "      <td>15</td>\n",
       "      <td>6971</td>\n",
       "      <td>364</td>\n",
       "      <td>56.67</td>\n",
       "      <td>19</td>\n",
       "      <td>33</td>\n",
       "      <td>5</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>ST Jayasuriya</td>\n",
       "      <td>110</td>\n",
       "      <td>188</td>\n",
       "      <td>14</td>\n",
       "      <td>6973</td>\n",
       "      <td>340</td>\n",
       "      <td>40.07</td>\n",
       "      <td>14</td>\n",
       "      <td>31</td>\n",
       "      <td>15</td>\n",
       "      <td>SL</td>\n",
       "      <td>No</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>WR Hammond</td>\n",
       "      <td>85</td>\n",
       "      <td>140</td>\n",
       "      <td>16</td>\n",
       "      <td>7249</td>\n",
       "      <td>336</td>\n",
       "      <td>58.45</td>\n",
       "      <td>22</td>\n",
       "      <td>24</td>\n",
       "      <td>4</td>\n",
       "      <td>ENG</td>\n",
       "      <td>No</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>DA Warner</td>\n",
       "      <td>86</td>\n",
       "      <td>159</td>\n",
       "      <td>7</td>\n",
       "      <td>7311</td>\n",
       "      <td>335</td>\n",
       "      <td>48.09</td>\n",
       "      <td>24</td>\n",
       "      <td>30</td>\n",
       "      <td>9</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>MA Taylor</td>\n",
       "      <td>104</td>\n",
       "      <td>186</td>\n",
       "      <td>13</td>\n",
       "      <td>7525</td>\n",
       "      <td>334</td>\n",
       "      <td>43.49</td>\n",
       "      <td>19</td>\n",
       "      <td>40</td>\n",
       "      <td>5</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>DG Bradman</td>\n",
       "      <td>52</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "      <td>6996</td>\n",
       "      <td>334</td>\n",
       "      <td>99.94</td>\n",
       "      <td>29</td>\n",
       "      <td>13</td>\n",
       "      <td>7</td>\n",
       "      <td>AUS</td>\n",
       "      <td>No</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Player  Match  Innings  NotOut   Runs  Highest_score  Average  \\\n",
       "6            BC Lara     131      232       6  11953            400    52.88   \n",
       "22         ML Hayden     103      184      14   8625            380    50.73   \n",
       "8   DPMD Jayawardene     149      252      15  11814            374    49.84   \n",
       "29         GS Sobers      93      160      21   8032            365    57.78   \n",
       "55          L Hutton      79      138      15   6971            364    56.67   \n",
       "54     ST Jayasuriya     110      188      14   6973            340    40.07   \n",
       "46        WR Hammond      85      140      16   7249            336    58.45   \n",
       "44         DA Warner      86      159       7   7311            335    48.09   \n",
       "40         MA Taylor     104      186      13   7525            334    43.49   \n",
       "53        DG Bradman      52       80      10   6996            334    99.94   \n",
       "\n",
       "    Centuries  Half_centuries  Ducks Country played_for_ICC  years_played  \n",
       "6          34              48     17      WI            Yes            16  \n",
       "22         30              29     14     AUS             No            15  \n",
       "8          34              50     15      SL             No            17  \n",
       "29         26              30     12      WI             No            20  \n",
       "55         19              33      5     ENG             No            18  \n",
       "54         14              31     15      SL             No            16  \n",
       "46         22              24      4     ENG             No            20  \n",
       "44         24              30      9     AUS             No            10  \n",
       "40         19              40      5     AUS             No            10  \n",
       "53         29              13      7     AUS             No            20  "
      ]
     },
     "execution_count": 492,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by=\"Highest_score\", ascending = False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### dataframe slicing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 493,
   "metadata": {},
   "outputs": [
    {
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       "      <td>SR Tendulkar</td>\n",
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       "          Player Country   Runs  Centuries\n",
       "0  SR Tendulkar    INDIA  15921         51\n",
       "1    RT Ponting      AUS  13378         41\n",
       "2     JH Kallis       SA  13289         45\n",
       "3      R Dravid    INDIA  13288         36\n",
       "4       AN Cook      ENG  12472         33"
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       "      <th>5</th>\n",
       "      <td>KC Sangakkara</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>BC Lara</td>\n",
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       "      <td>34</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>S Chanderpaul</td>\n",
       "      <td>WI</td>\n",
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       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DPMD Jayawardene</td>\n",
       "      <td>SL</td>\n",
       "      <td>11814</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>AR Border</td>\n",
       "      <td>AUS</td>\n",
       "      <td>11174</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>SR Waugh</td>\n",
       "      <td>AUS</td>\n",
       "      <td>10927</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "               Player Country   Runs  Centuries\n",
       "0       SR Tendulkar    INDIA  15921         51\n",
       "1         RT Ponting      AUS  13378         41\n",
       "2          JH Kallis       SA  13289         45\n",
       "3           R Dravid    INDIA  13288         36\n",
       "4            AN Cook      ENG  12472         33\n",
       "5      KC Sangakkara       SL  12400         38\n",
       "6            BC Lara       WI  11953         34\n",
       "7      S Chanderpaul       WI  11867         30\n",
       "8   DPMD Jayawardene       SL  11814         34\n",
       "9          AR Border      AUS  11174         27\n",
       "10          SR Waugh      AUS  10927         32"
      ]
     },
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     "output_type": "display_data"
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      "text/plain": [
       "              Player Country   Runs  Centuries\n",
       "0      SR Tendulkar    INDIA  15921         51\n",
       "1        RT Ponting      AUS  13378         41\n",
       "2         JH Kallis       SA  13289         45\n",
       "3          R Dravid    INDIA  13288         36\n",
       "4           AN Cook      ENG  12472         33\n",
       "5     KC Sangakkara       SL  12400         38\n",
       "6           BC Lara       WI  11953         34\n",
       "7     S Chanderpaul       WI  11867         30\n",
       "8  DPMD Jayawardene       SL  11814         34\n",
       "9         AR Border      AUS  11174         27"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(97, 4)\n",
      "(11, 4)\n",
      "(10, 4)\n"
     ]
    }
   ],
   "source": [
    "# column_name = ['Player', 'Country', 'Runs', 'Centuries']\n",
    "\n",
    "# method 1\n",
    "df_method_1 = df[['Player', 'Country', 'Runs', 'Centuries']]\n",
    "\n",
    "# method 2\n",
    "df_method_2 = df.loc[0:10, ['Player', 'Country', 'Runs', 'Centuries']]\n",
    "\n",
    "# method 3\n",
    "df_method_3 = df.iloc[0:10, [0, 10, 4, 7]]\n",
    "\n",
    "display(df_method_1.head())\n",
    "display(df_method_2)\n",
    "display(df_method_3)\n",
    "\n",
    "print(df_method_1.shape)\n",
    "print(df_method_2.shape)\n",
    "print(df_method_3.shape)"
   ]
  },
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   "cell_type": "code",
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   "source": []
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   "execution_count": null,
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   "source": []
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