imdb-celebrities-dataset-analysis.ipynb

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    {
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     "output_type": "stream",
     "text": [
      "/kaggle/input/imdb-top100-celebrities-dataset/celebrity_data.csv\n"
     ]
    }
   ],
   "source": [
    "# This Python 3 environment comes with many helpful analytics libraries installed\n",
    "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n",
    "# For example, here's several helpful packages to load\n",
    "\n",
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "\n",
    "# Input data files are available in the read-only \"../input/\" directory\n",
    "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
    "\n",
    "import os\n",
    "for dirname, _, filenames in os.walk('/kaggle/input'):\n",
    "    for filename in filenames:\n",
    "        print(os.path.join(dirname, filename))\n",
    "\n",
    "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n",
    "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session"
   ]
  },
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   },
   "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",
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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>Rank</th>\n",
       "      <th>Name</th>\n",
       "      <th>Date_of_birth</th>\n",
       "      <th>height</th>\n",
       "      <th>Role</th>\n",
       "      <th>Awards</th>\n",
       "      <th>Famous_for</th>\n",
       "      <th>Birth_place</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Sofia Boutella</td>\n",
       "      <td>April 3, 1982</td>\n",
       "      <td>5′ 5″ (1.65 m)</td>\n",
       "      <td>['Actress', 'Soundtrack']</td>\n",
       "      <td>1 win &amp; 2 nominations</td>\n",
       "      <td>Kingsman: The Secret Service (2014)</td>\n",
       "      <td>Bab El Oued, Algeria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Ed Skrein</td>\n",
       "      <td>March 29, 1983</td>\n",
       "      <td>6′ 1″ (1.85 m)</td>\n",
       "      <td>['Actor', 'Director', 'Writer']</td>\n",
       "      <td>2 wins &amp; 2 nominations</td>\n",
       "      <td>Deadpool (2016)</td>\n",
       "      <td>Camden, London, England, UK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Barry Keoghan</td>\n",
       "      <td>October 18, 1992</td>\n",
       "      <td>5′ 8″ (1.73 m)</td>\n",
       "      <td>['Actor']</td>\n",
       "      <td>11 wins &amp; 76 nominations total</td>\n",
       "      <td>The Killing of a Sacred Deer (2017)</td>\n",
       "      <td>Dublin, Ireland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Serinda Swan</td>\n",
       "      <td>July 11, 1984</td>\n",
       "      <td>5′ 7″ (1.70 m)</td>\n",
       "      <td>['Actress', 'Producer', 'Director']</td>\n",
       "      <td>2 nominations</td>\n",
       "      <td>Coroner (2019–2022)</td>\n",
       "      <td>West Vancouver, British Columbia, Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Alan Ritchson</td>\n",
       "      <td>November 28, 1982</td>\n",
       "      <td>6′ 3″ (1.91 m)</td>\n",
       "      <td>['Actor', 'Producer', 'Director']</td>\n",
       "      <td>3 wins &amp; 3 nominations</td>\n",
       "      <td>Teenage Mutant Ninja Turtles (2014)</td>\n",
       "      <td>Grand Forks, North Dakota, USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>96</td>\n",
       "      <td>Kristin Minter</td>\n",
       "      <td>November 22, 1965</td>\n",
       "      <td>5′ 8″ (1.73 m)</td>\n",
       "      <td>['Actress']</td>\n",
       "      <td>1 nomination</td>\n",
       "      <td>ER (1995–2003)</td>\n",
       "      <td>Miami, Florida, USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>97</td>\n",
       "      <td>Zac Efron</td>\n",
       "      <td>October 18, 1987</td>\n",
       "      <td>5′ 8″ (1.73 m)</td>\n",
       "      <td>['Actor', 'Producer', 'Soundtrack']</td>\n",
       "      <td>35 wins &amp; 44 nominations</td>\n",
       "      <td>17 Again (2009)</td>\n",
       "      <td>San Luis Obispo, California, USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>98</td>\n",
       "      <td>Emma Corrin</td>\n",
       "      <td>December 13, 1995</td>\n",
       "      <td>5′ 8″ (1.73 m)</td>\n",
       "      <td>['Actress', 'Music Department', 'Soundtrack']</td>\n",
       "      <td>10 wins &amp; 10 nominations total</td>\n",
       "      <td>Lady Chatterley's Lover (2022)</td>\n",
       "      <td>Royal Tunbridge Wells, Kent, England, UK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>99</td>\n",
       "      <td>Kelly Reilly</td>\n",
       "      <td>July 18, 1977</td>\n",
       "      <td>5′ 6″ (1.68 m)</td>\n",
       "      <td>['Actress', 'Producer']</td>\n",
       "      <td>7 wins &amp; 12 nominations</td>\n",
       "      <td>Pride &amp; Prejudice (2005)</td>\n",
       "      <td>Surrey, England, UK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>100</td>\n",
       "      <td>Kamar de los Reyes</td>\n",
       "      <td>November 8, 1967</td>\n",
       "      <td>5′ 10″ (1.78 m)</td>\n",
       "      <td>['Actor', 'Writer', 'Producer']</td>\n",
       "      <td>1 win &amp; 6 nominations</td>\n",
       "      <td>Sleepy Hollow (2017– )</td>\n",
       "      <td>San Juan, Puerto Rico</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Rank                Name      Date_of_birth           height  \\\n",
       "0      1      Sofia Boutella      April 3, 1982   5′ 5″ (1.65 m)   \n",
       "1      2           Ed Skrein     March 29, 1983   6′ 1″ (1.85 m)   \n",
       "2      3       Barry Keoghan   October 18, 1992   5′ 8″ (1.73 m)   \n",
       "3      4        Serinda Swan      July 11, 1984   5′ 7″ (1.70 m)   \n",
       "4      5       Alan Ritchson  November 28, 1982   6′ 3″ (1.91 m)   \n",
       "..   ...                 ...                ...              ...   \n",
       "95    96      Kristin Minter  November 22, 1965   5′ 8″ (1.73 m)   \n",
       "96    97           Zac Efron   October 18, 1987   5′ 8″ (1.73 m)   \n",
       "97    98         Emma Corrin  December 13, 1995   5′ 8″ (1.73 m)   \n",
       "98    99        Kelly Reilly      July 18, 1977   5′ 6″ (1.68 m)   \n",
       "99   100  Kamar de los Reyes   November 8, 1967  5′ 10″ (1.78 m)   \n",
       "\n",
       "                                             Role  \\\n",
       "0                       ['Actress', 'Soundtrack']   \n",
       "1                 ['Actor', 'Director', 'Writer']   \n",
       "2                                       ['Actor']   \n",
       "3             ['Actress', 'Producer', 'Director']   \n",
       "4               ['Actor', 'Producer', 'Director']   \n",
       "..                                            ...   \n",
       "95                                    ['Actress']   \n",
       "96            ['Actor', 'Producer', 'Soundtrack']   \n",
       "97  ['Actress', 'Music Department', 'Soundtrack']   \n",
       "98                        ['Actress', 'Producer']   \n",
       "99                ['Actor', 'Writer', 'Producer']   \n",
       "\n",
       "                            Awards                           Famous_for  \\\n",
       "0            1 win & 2 nominations  Kingsman: The Secret Service (2014)   \n",
       "1           2 wins & 2 nominations                      Deadpool (2016)   \n",
       "2   11 wins & 76 nominations total  The Killing of a Sacred Deer (2017)   \n",
       "3                    2 nominations                  Coroner (2019–2022)   \n",
       "4           3 wins & 3 nominations  Teenage Mutant Ninja Turtles (2014)   \n",
       "..                             ...                                  ...   \n",
       "95                    1 nomination                       ER (1995–2003)   \n",
       "96        35 wins & 44 nominations                      17 Again (2009)   \n",
       "97  10 wins & 10 nominations total       Lady Chatterley's Lover (2022)   \n",
       "98         7 wins & 12 nominations             Pride & Prejudice (2005)   \n",
       "99           1 win & 6 nominations               Sleepy Hollow (2017– )   \n",
       "\n",
       "                                 Birth_place  \n",
       "0                       Bab El Oued, Algeria  \n",
       "1                Camden, London, England, UK  \n",
       "2                            Dublin, Ireland  \n",
       "3   West Vancouver, British Columbia, Canada  \n",
       "4             Grand Forks, North Dakota, USA  \n",
       "..                                       ...  \n",
       "95                       Miami, Florida, USA  \n",
       "96          San Luis Obispo, California, USA  \n",
       "97  Royal Tunbridge Wells, Kent, England, UK  \n",
       "98                       Surrey, England, UK  \n",
       "99                     San Juan, Puerto Rico  \n",
       "\n",
       "[100 rows x 8 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
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    }
   ],
   "source": [
    "data = pd.read_csv(\"/kaggle/input/imdb-top100-celebrities-dataset/celebrity_data.csv\")\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c968c48",
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    "tags": []
   },
   "source": [
    "Let's see the columns in the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "05e2b13a",
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    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Rank',\n",
       " 'Name',\n",
       " 'Date_of_birth',\n",
       " 'height',\n",
       " 'Role',\n",
       " 'Awards',\n",
       " 'Famous_for',\n",
       " 'Birth_place']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(data.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0fc2b40",
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     "start_time": "2024-03-22T17:50:19.558777",
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    },
    "tags": []
   },
   "source": [
    "Total celebrities in the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cd3c210c",
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   "outputs": [],
   "source": []
  },
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    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Sofia Boutella',\n",
       " 'Ed Skrein',\n",
       " 'Barry Keoghan',\n",
       " 'Serinda Swan',\n",
       " 'Alan Ritchson',\n",
       " 'Lee Sun-kyun',\n",
       " 'Taylor Momsen',\n",
       " 'Sydney Sweeney',\n",
       " 'Jessica Parker Kennedy',\n",
       " 'Staz Nair',\n",
       " 'Emerald Fennell',\n",
       " 'Timothée Chalamet',\n",
       " 'Jacob Elordi',\n",
       " 'Charlie Hunnam',\n",
       " 'Michiel Huisman',\n",
       " 'Michelle Monaghan',\n",
       " 'Carey Mulligan',\n",
       " 'Willa Fitzgerald',\n",
       " 'Macaulay Culkin',\n",
       " 'Nicolette Scorsese',\n",
       " 'Margot Robbie',\n",
       " 'Alison Oliver',\n",
       " 'Julia Roberts',\n",
       " \"Beverly D'Angelo\",\n",
       " 'Peter Billingsley',\n",
       " 'Bae Doona',\n",
       " 'Zack Snyder',\n",
       " 'Melinda Dillon',\n",
       " 'Donna Reed',\n",
       " 'Florence Pugh',\n",
       " 'Jena Malone',\n",
       " 'Vera-Ellen',\n",
       " 'Thomas Brodie-Sangster',\n",
       " 'Millie Gibson',\n",
       " 'Glen Powell',\n",
       " 'Juno Temple',\n",
       " 'Rosamund Pike',\n",
       " 'Rachel Zegler',\n",
       " 'Emma Stone',\n",
       " 'Juliette Lewis',\n",
       " 'Virginia Kull',\n",
       " 'Cleopatra Coleman',\n",
       " 'Fra Fee',\n",
       " 'Alexandra Daddario',\n",
       " 'Shelley Hennig',\n",
       " 'Nicolas Cage',\n",
       " 'Heike Makatsch',\n",
       " 'Ellen Latzen',\n",
       " 'Tom Blyth',\n",
       " \"Myha'la\",\n",
       " 'Walker Scobell',\n",
       " 'Hannah Waddingham',\n",
       " 'Tom Cruise',\n",
       " 'Bradley Cooper',\n",
       " 'Archie Madekwe',\n",
       " 'Anya Taylor-Joy',\n",
       " 'Hayley Atwell',\n",
       " 'Jeremy Allen White',\n",
       " 'Mary Elizabeth Winstead',\n",
       " 'Djimon Hounsou',\n",
       " 'Jennifer Lawrence',\n",
       " 'Leonardo DiCaprio',\n",
       " 'James Stewart',\n",
       " 'Abigail Spencer',\n",
       " 'Zooey Deschanel',\n",
       " 'Alison Brie',\n",
       " 'Karen Allen',\n",
       " 'Harris Dickinson',\n",
       " 'Mara Wilson',\n",
       " 'Jenna Ortega',\n",
       " 'Olivia Cooke',\n",
       " \"Catherine O'Hara\",\n",
       " 'Mark Wahlberg',\n",
       " 'Gary Oldman',\n",
       " 'Phoebe Waller-Bridge',\n",
       " 'Alan Rickman',\n",
       " 'Bruce Willis',\n",
       " 'Lily James',\n",
       " 'Vanessa Kirby',\n",
       " 'Maria Sten',\n",
       " 'Anita Dobson',\n",
       " 'Rebecca Ferguson',\n",
       " 'Rosemary Clooney',\n",
       " 'Tom Hanks',\n",
       " 'Amber Heard',\n",
       " 'Ana de Armas',\n",
       " 'Jennifer Connelly',\n",
       " 'Keira Knightley',\n",
       " 'Christine Baranski',\n",
       " 'Ncuti Gatwa',\n",
       " 'Elizabeth Perkins',\n",
       " 'Bonnie Bedelia',\n",
       " 'Ryan Gosling',\n",
       " 'Jennifer Jason Leigh',\n",
       " 'Harrison Ford',\n",
       " 'Kristin Minter',\n",
       " 'Zac Efron',\n",
       " 'Emma Corrin',\n",
       " 'Kelly Reilly',\n",
       " 'Kamar de los Reyes']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_unique_celebrities = list(data['Name'].unique())\n",
    "all_unique_celebrities "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "da7ebbb9",
   "metadata": {
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(all_unique_celebrities)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "305cf8a8",
   "metadata": {
    "papermill": {
     "duration": 0.005764,
     "end_time": "2024-03-22T17:50:19.634749",
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     "start_time": "2024-03-22T17:50:19.628985",
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    },
    "tags": []
   },
   "source": [
    "There are total 100 celebrities in the list."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79a9264b",
   "metadata": {
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     "duration": 0.00554,
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    },
    "tags": []
   },
   "source": [
    "#### Let's see the celebrities whose date of birth was pre 1950"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8d166f5c",
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   "source": [
    "import numpy as np\n",
    "\n",
    "def fetching_year(value):  # April 3, 1982\n",
    "    value = value.split(\",\")\n",
    "    if len(value) > 1:\n",
    "        return value[-1]\n",
    "    else:\n",
    "        return 0"
   ]
  },
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    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Name</th>\n",
       "      <th>Date_of_birth</th>\n",
       "      <th>height</th>\n",
       "      <th>Role</th>\n",
       "      <th>Awards</th>\n",
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       "      <th>Birth_place</th>\n",
       "      <th>year_of_birth</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Sofia Boutella</td>\n",
       "      <td>April 3, 1982</td>\n",
       "      <td>5′ 5″ (1.65 m)</td>\n",
       "      <td>['Actress', 'Soundtrack']</td>\n",
       "      <td>1 win &amp; 2 nominations</td>\n",
       "      <td>Kingsman: The Secret Service (2014)</td>\n",
       "      <td>Bab El Oued, Algeria</td>\n",
       "      <td>1982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Ed Skrein</td>\n",
       "      <td>March 29, 1983</td>\n",
       "      <td>6′ 1″ (1.85 m)</td>\n",
       "      <td>['Actor', 'Director', 'Writer']</td>\n",
       "      <td>2 wins &amp; 2 nominations</td>\n",
       "      <td>Deadpool (2016)</td>\n",
       "      <td>Camden, London, England, UK</td>\n",
       "      <td>1983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Barry Keoghan</td>\n",
       "      <td>October 18, 1992</td>\n",
       "      <td>5′ 8″ (1.73 m)</td>\n",
       "      <td>['Actor']</td>\n",
       "      <td>11 wins &amp; 76 nominations total</td>\n",
       "      <td>The Killing of a Sacred Deer (2017)</td>\n",
       "      <td>Dublin, Ireland</td>\n",
       "      <td>1992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Serinda Swan</td>\n",
       "      <td>July 11, 1984</td>\n",
       "      <td>5′ 7″ (1.70 m)</td>\n",
       "      <td>['Actress', 'Producer', 'Director']</td>\n",
       "      <td>2 nominations</td>\n",
       "      <td>Coroner (2019–2022)</td>\n",
       "      <td>West Vancouver, British Columbia, Canada</td>\n",
       "      <td>1984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Alan Ritchson</td>\n",
       "      <td>November 28, 1982</td>\n",
       "      <td>6′ 3″ (1.91 m)</td>\n",
       "      <td>['Actor', 'Producer', 'Director']</td>\n",
       "      <td>3 wins &amp; 3 nominations</td>\n",
       "      <td>Teenage Mutant Ninja Turtles (2014)</td>\n",
       "      <td>Grand Forks, North Dakota, USA</td>\n",
       "      <td>1982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>96</td>\n",
       "      <td>Kristin Minter</td>\n",
       "      <td>November 22, 1965</td>\n",
       "      <td>5′ 8″ (1.73 m)</td>\n",
       "      <td>['Actress']</td>\n",
       "      <td>1 nomination</td>\n",
       "      <td>ER (1995–2003)</td>\n",
       "      <td>Miami, Florida, USA</td>\n",
       "      <td>1965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>97</td>\n",
       "      <td>Zac Efron</td>\n",
       "      <td>October 18, 1987</td>\n",
       "      <td>5′ 8″ (1.73 m)</td>\n",
       "      <td>['Actor', 'Producer', 'Soundtrack']</td>\n",
       "      <td>35 wins &amp; 44 nominations</td>\n",
       "      <td>17 Again (2009)</td>\n",
       "      <td>San Luis Obispo, California, USA</td>\n",
       "      <td>1987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>98</td>\n",
       "      <td>Emma Corrin</td>\n",
       "      <td>December 13, 1995</td>\n",
       "      <td>5′ 8″ (1.73 m)</td>\n",
       "      <td>['Actress', 'Music Department', 'Soundtrack']</td>\n",
       "      <td>10 wins &amp; 10 nominations total</td>\n",
       "      <td>Lady Chatterley's Lover (2022)</td>\n",
       "      <td>Royal Tunbridge Wells, Kent, England, UK</td>\n",
       "      <td>1995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>99</td>\n",
       "      <td>Kelly Reilly</td>\n",
       "      <td>July 18, 1977</td>\n",
       "      <td>5′ 6″ (1.68 m)</td>\n",
       "      <td>['Actress', 'Producer']</td>\n",
       "      <td>7 wins &amp; 12 nominations</td>\n",
       "      <td>Pride &amp; Prejudice (2005)</td>\n",
       "      <td>Surrey, England, UK</td>\n",
       "      <td>1977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>100</td>\n",
       "      <td>Kamar de los Reyes</td>\n",
       "      <td>November 8, 1967</td>\n",
       "      <td>5′ 10″ (1.78 m)</td>\n",
       "      <td>['Actor', 'Writer', 'Producer']</td>\n",
       "      <td>1 win &amp; 6 nominations</td>\n",
       "      <td>Sleepy Hollow (2017– )</td>\n",
       "      <td>San Juan, Puerto Rico</td>\n",
       "      <td>1967</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Rank                Name      Date_of_birth           height  \\\n",
       "0      1      Sofia Boutella      April 3, 1982   5′ 5″ (1.65 m)   \n",
       "1      2           Ed Skrein     March 29, 1983   6′ 1″ (1.85 m)   \n",
       "2      3       Barry Keoghan   October 18, 1992   5′ 8″ (1.73 m)   \n",
       "3      4        Serinda Swan      July 11, 1984   5′ 7″ (1.70 m)   \n",
       "4      5       Alan Ritchson  November 28, 1982   6′ 3″ (1.91 m)   \n",
       "..   ...                 ...                ...              ...   \n",
       "95    96      Kristin Minter  November 22, 1965   5′ 8″ (1.73 m)   \n",
       "96    97           Zac Efron   October 18, 1987   5′ 8″ (1.73 m)   \n",
       "97    98         Emma Corrin  December 13, 1995   5′ 8″ (1.73 m)   \n",
       "98    99        Kelly Reilly      July 18, 1977   5′ 6″ (1.68 m)   \n",
       "99   100  Kamar de los Reyes   November 8, 1967  5′ 10″ (1.78 m)   \n",
       "\n",
       "                                             Role  \\\n",
       "0                       ['Actress', 'Soundtrack']   \n",
       "1                 ['Actor', 'Director', 'Writer']   \n",
       "2                                       ['Actor']   \n",
       "3             ['Actress', 'Producer', 'Director']   \n",
       "4               ['Actor', 'Producer', 'Director']   \n",
       "..                                            ...   \n",
       "95                                    ['Actress']   \n",
       "96            ['Actor', 'Producer', 'Soundtrack']   \n",
       "97  ['Actress', 'Music Department', 'Soundtrack']   \n",
       "98                        ['Actress', 'Producer']   \n",
       "99                ['Actor', 'Writer', 'Producer']   \n",
       "\n",
       "                            Awards                           Famous_for  \\\n",
       "0            1 win & 2 nominations  Kingsman: The Secret Service (2014)   \n",
       "1           2 wins & 2 nominations                      Deadpool (2016)   \n",
       "2   11 wins & 76 nominations total  The Killing of a Sacred Deer (2017)   \n",
       "3                    2 nominations                  Coroner (2019–2022)   \n",
       "4           3 wins & 3 nominations  Teenage Mutant Ninja Turtles (2014)   \n",
       "..                             ...                                  ...   \n",
       "95                    1 nomination                       ER (1995–2003)   \n",
       "96        35 wins & 44 nominations                      17 Again (2009)   \n",
       "97  10 wins & 10 nominations total       Lady Chatterley's Lover (2022)   \n",
       "98         7 wins & 12 nominations             Pride & Prejudice (2005)   \n",
       "99           1 win & 6 nominations               Sleepy Hollow (2017– )   \n",
       "\n",
       "                                 Birth_place year_of_birth  \n",
       "0                       Bab El Oued, Algeria          1982  \n",
       "1                Camden, London, England, UK          1983  \n",
       "2                            Dublin, Ireland          1992  \n",
       "3   West Vancouver, British Columbia, Canada          1984  \n",
       "4             Grand Forks, North Dakota, USA          1982  \n",
       "..                                       ...           ...  \n",
       "95                       Miami, Florida, USA          1965  \n",
       "96          San Luis Obispo, California, USA          1987  \n",
       "97  Royal Tunbridge Wells, Kent, England, UK          1995  \n",
       "98                       Surrey, England, UK          1977  \n",
       "99                     San Juan, Puerto Rico          1967  \n",
       "\n",
       "[100 rows x 9 columns]"
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   "source": [
    "data[\"year_of_birth\"] = data[\"Date_of_birth\"].apply(fetching_year)\n",
    "#data[\"year_of_birth\"] = data[\"year_of_birth\"].astype(int)\n",
    "data"
   ]
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     "data": {
      "text/plain": [
       "[' 1982',\n",
       " ' 1983',\n",
       " ' 1992',\n",
       " ' 1984',\n",
       " ' 1982',\n",
       " ' 1975',\n",
       " ' 1993',\n",
       " ' 1997',\n",
       " ' 1984',\n",
       " ' 1991',\n",
       " ' 1985',\n",
       " ' 1995',\n",
       " ' 1997',\n",
       " ' 1980',\n",
       " ' 1981',\n",
       " ' 1976',\n",
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       " ' 1991',\n",
       " ' 1980',\n",
       " ' 1954',\n",
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       " ' 1996',\n",
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       " ' 1921',\n",
       " ' 1990',\n",
       " ' 2004',\n",
       " ' 1988',\n",
       " ' 1989',\n",
       " ' 1979',\n",
       " ' 2001',\n",
       " ' 1988',\n",
       " ' 1973',\n",
       " 0,\n",
       " ' 1987',\n",
       " ' 1987',\n",
       " ' 1986',\n",
       " ' 1987',\n",
       " ' 1964',\n",
       " ' 1971',\n",
       " ' 1980',\n",
       " ' 1995',\n",
       " ' 1996',\n",
       " ' 2009',\n",
       " ' 1974',\n",
       " ' 1962',\n",
       " ' 1975',\n",
       " ' 1995',\n",
       " ' 1996',\n",
       " ' 1982',\n",
       " ' 1991',\n",
       " ' 1984',\n",
       " ' 1964',\n",
       " ' 1990',\n",
       " ' 1974',\n",
       " ' 1908',\n",
       " ' 1981',\n",
       " ' 1980',\n",
       " ' 1982',\n",
       " ' 1951',\n",
       " ' 1996',\n",
       " ' 1987',\n",
       " ' 2002',\n",
       " ' 1993',\n",
       " ' 1954',\n",
       " ' 1971',\n",
       " ' 1958',\n",
       " ' 1985',\n",
       " ' 1946',\n",
       " ' 1955',\n",
       " ' 1989',\n",
       " ' 1988',\n",
       " 0,\n",
       " ' 1949',\n",
       " ' 1983',\n",
       " ' 1928',\n",
       " ' 1956',\n",
       " ' 1986',\n",
       " ' 1988',\n",
       " ' 1970',\n",
       " ' 1985',\n",
       " ' 1952',\n",
       " ' 1992',\n",
       " ' 1960',\n",
       " ' 1948',\n",
       " ' 1980',\n",
       " ' 1962',\n",
       " ' 1942',\n",
       " ' 1965',\n",
       " ' 1987',\n",
       " ' 1995',\n",
       " ' 1977',\n",
       " ' 1967']"
      ]
     },
     "execution_count": 8,
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   ]
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       "      <th>Rank</th>\n",
       "      <th>Name</th>\n",
       "      <th>Date_of_birth</th>\n",
       "      <th>height</th>\n",
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       "      <td>1</td>\n",
       "      <td>Sofia Boutella</td>\n",
       "      <td>April 3, 1982</td>\n",
       "      <td>5′ 5″ (1.65 m)</td>\n",
       "      <td>['Actress', 'Soundtrack']</td>\n",
       "      <td>1 win &amp; 2 nominations</td>\n",
       "      <td>Kingsman: The Secret Service (2014)</td>\n",
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       "      <td>March 29, 1983</td>\n",
       "      <td>6′ 1″ (1.85 m)</td>\n",
       "      <td>['Actor', 'Director', 'Writer']</td>\n",
       "      <td>2 wins &amp; 2 nominations</td>\n",
       "      <td>Deadpool (2016)</td>\n",
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       "      <td>1983</td>\n",
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       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Serinda Swan</td>\n",
       "      <td>July 11, 1984</td>\n",
       "      <td>5′ 7″ (1.70 m)</td>\n",
       "      <td>['Actress', 'Producer', 'Director']</td>\n",
       "      <td>2 nominations</td>\n",
       "      <td>Coroner (2019–2022)</td>\n",
       "      <td>West Vancouver, British Columbia, Canada</td>\n",
       "      <td>1984</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Alan Ritchson</td>\n",
       "      <td>November 28, 1982</td>\n",
       "      <td>6′ 3″ (1.91 m)</td>\n",
       "      <td>['Actor', 'Producer', 'Director']</td>\n",
       "      <td>3 wins &amp; 3 nominations</td>\n",
       "      <td>Teenage Mutant Ninja Turtles (2014)</td>\n",
       "      <td>Grand Forks, North Dakota, USA</td>\n",
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       "      <th>95</th>\n",
       "      <td>96</td>\n",
       "      <td>Kristin Minter</td>\n",
       "      <td>November 22, 1965</td>\n",
       "      <td>5′ 8″ (1.73 m)</td>\n",
       "      <td>['Actress']</td>\n",
       "      <td>1 nomination</td>\n",
       "      <td>ER (1995–2003)</td>\n",
       "      <td>Miami, Florida, USA</td>\n",
       "      <td>1965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
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       "      <td>Zac Efron</td>\n",
       "      <td>October 18, 1987</td>\n",
       "      <td>5′ 8″ (1.73 m)</td>\n",
       "      <td>['Actor', 'Producer', 'Soundtrack']</td>\n",
       "      <td>35 wins &amp; 44 nominations</td>\n",
       "      <td>17 Again (2009)</td>\n",
       "      <td>San Luis Obispo, California, USA</td>\n",
       "      <td>1987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>98</td>\n",
       "      <td>Emma Corrin</td>\n",
       "      <td>December 13, 1995</td>\n",
       "      <td>5′ 8″ (1.73 m)</td>\n",
       "      <td>['Actress', 'Music Department', 'Soundtrack']</td>\n",
       "      <td>10 wins &amp; 10 nominations total</td>\n",
       "      <td>Lady Chatterley's Lover (2022)</td>\n",
       "      <td>Royal Tunbridge Wells, Kent, England, UK</td>\n",
       "      <td>1995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>99</td>\n",
       "      <td>Kelly Reilly</td>\n",
       "      <td>July 18, 1977</td>\n",
       "      <td>5′ 6″ (1.68 m)</td>\n",
       "      <td>['Actress', 'Producer']</td>\n",
       "      <td>7 wins &amp; 12 nominations</td>\n",
       "      <td>Pride &amp; Prejudice (2005)</td>\n",
       "      <td>Surrey, England, UK</td>\n",
       "      <td>1977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>100</td>\n",
       "      <td>Kamar de los Reyes</td>\n",
       "      <td>November 8, 1967</td>\n",
       "      <td>5′ 10″ (1.78 m)</td>\n",
       "      <td>['Actor', 'Writer', 'Producer']</td>\n",
       "      <td>1 win &amp; 6 nominations</td>\n",
       "      <td>Sleepy Hollow (2017– )</td>\n",
       "      <td>San Juan, Puerto Rico</td>\n",
       "      <td>1967</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Rank                Name      Date_of_birth           height  \\\n",
       "0      1      Sofia Boutella      April 3, 1982   5′ 5″ (1.65 m)   \n",
       "1      2           Ed Skrein     March 29, 1983   6′ 1″ (1.85 m)   \n",
       "2      3       Barry Keoghan   October 18, 1992   5′ 8″ (1.73 m)   \n",
       "3      4        Serinda Swan      July 11, 1984   5′ 7″ (1.70 m)   \n",
       "4      5       Alan Ritchson  November 28, 1982   6′ 3″ (1.91 m)   \n",
       "..   ...                 ...                ...              ...   \n",
       "95    96      Kristin Minter  November 22, 1965   5′ 8″ (1.73 m)   \n",
       "96    97           Zac Efron   October 18, 1987   5′ 8″ (1.73 m)   \n",
       "97    98         Emma Corrin  December 13, 1995   5′ 8″ (1.73 m)   \n",
       "98    99        Kelly Reilly      July 18, 1977   5′ 6″ (1.68 m)   \n",
       "99   100  Kamar de los Reyes   November 8, 1967  5′ 10″ (1.78 m)   \n",
       "\n",
       "                                             Role  \\\n",
       "0                       ['Actress', 'Soundtrack']   \n",
       "1                 ['Actor', 'Director', 'Writer']   \n",
       "2                                       ['Actor']   \n",
       "3             ['Actress', 'Producer', 'Director']   \n",
       "4               ['Actor', 'Producer', 'Director']   \n",
       "..                                            ...   \n",
       "95                                    ['Actress']   \n",
       "96            ['Actor', 'Producer', 'Soundtrack']   \n",
       "97  ['Actress', 'Music Department', 'Soundtrack']   \n",
       "98                        ['Actress', 'Producer']   \n",
       "99                ['Actor', 'Writer', 'Producer']   \n",
       "\n",
       "                            Awards                           Famous_for  \\\n",
       "0            1 win & 2 nominations  Kingsman: The Secret Service (2014)   \n",
       "1           2 wins & 2 nominations                      Deadpool (2016)   \n",
       "2   11 wins & 76 nominations total  The Killing of a Sacred Deer (2017)   \n",
       "3                    2 nominations                  Coroner (2019–2022)   \n",
       "4           3 wins & 3 nominations  Teenage Mutant Ninja Turtles (2014)   \n",
       "..                             ...                                  ...   \n",
       "95                    1 nomination                       ER (1995–2003)   \n",
       "96        35 wins & 44 nominations                      17 Again (2009)   \n",
       "97  10 wins & 10 nominations total       Lady Chatterley's Lover (2022)   \n",
       "98         7 wins & 12 nominations             Pride & Prejudice (2005)   \n",
       "99           1 win & 6 nominations               Sleepy Hollow (2017– )   \n",
       "\n",
       "                                 Birth_place  year_of_birth  \n",
       "0                       Bab El Oued, Algeria           1982  \n",
       "1                Camden, London, England, UK           1983  \n",
       "2                            Dublin, Ireland           1992  \n",
       "3   West Vancouver, British Columbia, Canada           1984  \n",
       "4             Grand Forks, North Dakota, USA           1982  \n",
       "..                                       ...            ...  \n",
       "95                       Miami, Florida, USA           1965  \n",
       "96          San Luis Obispo, California, USA           1987  \n",
       "97  Royal Tunbridge Wells, Kent, England, UK           1995  \n",
       "98                       Surrey, England, UK           1977  \n",
       "99                     San Juan, Puerto Rico           1967  \n",
       "\n",
       "[100 rows x 9 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"year_of_birth\"] = data[\"year_of_birth\"].astype(int)\n",
    "data"
   ]
  },
  {
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    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Name</th>\n",
       "      <th>Date_of_birth</th>\n",
       "      <th>height</th>\n",
       "      <th>Role</th>\n",
       "      <th>Awards</th>\n",
       "      <th>Famous_for</th>\n",
       "      <th>Birth_place</th>\n",
       "      <th>year_of_birth</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>Melinda Dillon</td>\n",
       "      <td>October 13, 1939</td>\n",
       "      <td>5′ 8″ (1.73 m)</td>\n",
       "      <td>['Actress', 'Soundtrack']</td>\n",
       "      <td>4 wins &amp; 10 nominations total</td>\n",
       "      <td>Magnolia (1999)</td>\n",
       "      <td>Hope, Arkansas, USA</td>\n",
       "      <td>1939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>Donna Reed</td>\n",
       "      <td>January 27, 1921</td>\n",
       "      <td>5′ 3½″ (1.61 m)</td>\n",
       "      <td>['Actress', 'Soundtrack']</td>\n",
       "      <td>5 wins &amp; 9 nominations total</td>\n",
       "      <td>It's a Wonderful Life (1946)</td>\n",
       "      <td>Denison, Iowa, USA</td>\n",
       "      <td>1921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>Vera-Ellen</td>\n",
       "      <td>February 16, 1921</td>\n",
       "      <td>5′ 4″ (1.63 m)</td>\n",
       "      <td>['Actress', 'Soundtrack']</td>\n",
       "      <td>1 win</td>\n",
       "      <td>White Christmas (1954)</td>\n",
       "      <td>Norwood, Ohio, USA</td>\n",
       "      <td>1921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>63</td>\n",
       "      <td>James Stewart</td>\n",
       "      <td>May 20, 1908</td>\n",
       "      <td>6′ 3″ (1.91 m)</td>\n",
       "      <td>['Actor', 'Director', 'Producer']</td>\n",
       "      <td>31 wins &amp; 21 nominations total</td>\n",
       "      <td>Vertigo (1958)</td>\n",
       "      <td>Indiana, Pennsylvania, USA</td>\n",
       "      <td>1908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>76</td>\n",
       "      <td>Alan Rickman</td>\n",
       "      <td>February 21, 1946</td>\n",
       "      <td>6′ 1″ (1.85 m)</td>\n",
       "      <td>['Actor', 'Writer', 'Director']</td>\n",
       "      <td>19 wins &amp; 38 nominations total</td>\n",
       "      <td>Die Hard (1988)</td>\n",
       "      <td>Hammersmith, London, England, UK</td>\n",
       "      <td>1946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>81</td>\n",
       "      <td>Anita Dobson</td>\n",
       "      <td>April 29, 1949</td>\n",
       "      <td>5′ 3″ (1.60 m)</td>\n",
       "      <td>['Actress']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Red Dwarf (1993– )</td>\n",
       "      <td>Stepney, London, England, UK</td>\n",
       "      <td>1949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>83</td>\n",
       "      <td>Rosemary Clooney</td>\n",
       "      <td>May 23, 1928</td>\n",
       "      <td>5′ 6″ (1.68 m)</td>\n",
       "      <td>['Actress', 'Writer', 'Music Department']</td>\n",
       "      <td>1 win &amp; 3 nominations total</td>\n",
       "      <td>White Christmas (1954)</td>\n",
       "      <td>Maysville, Kentucky, USA</td>\n",
       "      <td>1928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>92</td>\n",
       "      <td>Bonnie Bedelia</td>\n",
       "      <td>March 25, 1948</td>\n",
       "      <td>5′ 4″ (1.63 m)</td>\n",
       "      <td>['Actress', 'Soundtrack']</td>\n",
       "      <td>3 wins &amp; 5 nominations total</td>\n",
       "      <td>Die Hard (1988)</td>\n",
       "      <td>New York City, New York, USA</td>\n",
       "      <td>1948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>95</td>\n",
       "      <td>Harrison Ford</td>\n",
       "      <td>July 13, 1942</td>\n",
       "      <td>6′ 1″ (1.85 m)</td>\n",
       "      <td>['Actor', 'Writer', 'Producer']</td>\n",
       "      <td>45 wins &amp; 58 nominations total</td>\n",
       "      <td>Raiders of the Lost Ark (1981)</td>\n",
       "      <td>Chicago, Illinois, USA</td>\n",
       "      <td>1942</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Rank              Name      Date_of_birth           height  \\\n",
       "27    28    Melinda Dillon   October 13, 1939   5′ 8″ (1.73 m)   \n",
       "28    29        Donna Reed   January 27, 1921  5′ 3½″ (1.61 m)   \n",
       "31    32        Vera-Ellen  February 16, 1921   5′ 4″ (1.63 m)   \n",
       "62    63     James Stewart       May 20, 1908   6′ 3″ (1.91 m)   \n",
       "75    76      Alan Rickman  February 21, 1946   6′ 1″ (1.85 m)   \n",
       "80    81      Anita Dobson     April 29, 1949   5′ 3″ (1.60 m)   \n",
       "82    83  Rosemary Clooney       May 23, 1928   5′ 6″ (1.68 m)   \n",
       "91    92    Bonnie Bedelia     March 25, 1948   5′ 4″ (1.63 m)   \n",
       "94    95     Harrison Ford      July 13, 1942   6′ 1″ (1.85 m)   \n",
       "\n",
       "                                         Role                          Awards  \\\n",
       "27                  ['Actress', 'Soundtrack']   4 wins & 10 nominations total   \n",
       "28                  ['Actress', 'Soundtrack']    5 wins & 9 nominations total   \n",
       "31                  ['Actress', 'Soundtrack']                           1 win   \n",
       "62          ['Actor', 'Director', 'Producer']  31 wins & 21 nominations total   \n",
       "75            ['Actor', 'Writer', 'Director']  19 wins & 38 nominations total   \n",
       "80                                ['Actress']                             NaN   \n",
       "82  ['Actress', 'Writer', 'Music Department']     1 win & 3 nominations total   \n",
       "91                  ['Actress', 'Soundtrack']    3 wins & 5 nominations total   \n",
       "94            ['Actor', 'Writer', 'Producer']  45 wins & 58 nominations total   \n",
       "\n",
       "                        Famous_for                       Birth_place  \\\n",
       "27                 Magnolia (1999)               Hope, Arkansas, USA   \n",
       "28    It's a Wonderful Life (1946)                Denison, Iowa, USA   \n",
       "31          White Christmas (1954)                Norwood, Ohio, USA   \n",
       "62                  Vertigo (1958)        Indiana, Pennsylvania, USA   \n",
       "75                 Die Hard (1988)  Hammersmith, London, England, UK   \n",
       "80              Red Dwarf (1993– )      Stepney, London, England, UK   \n",
       "82          White Christmas (1954)          Maysville, Kentucky, USA   \n",
       "91                 Die Hard (1988)      New York City, New York, USA   \n",
       "94  Raiders of the Lost Ark (1981)            Chicago, Illinois, USA   \n",
       "\n",
       "    year_of_birth  \n",
       "27           1939  \n",
       "28           1921  \n",
       "31           1921  \n",
       "62           1908  \n",
       "75           1946  \n",
       "80           1949  \n",
       "82           1928  \n",
       "91           1948  \n",
       "94           1942  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "before_1950_birth = data[(data[\"year_of_birth\"] < 1950) & (data[\"year_of_birth\"] != 0) ]\n",
    "before_1950_birth "
   ]
  },
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    {
     "data": {
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       "9"
      ]
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   ],
   "source": [
    "len(before_1950_birth)"
   ]
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   "source": [
    "\n",
    "Analyzing the Forbes dataset of celebrities using Pandas, NumPy, and Matplotlib offers numerous opportunities for exploring trends, relationships, and insights. Here are several possible questions and analyses you could perform:\n",
    "\n",
    "Descriptive Statistics:\n",
    "\n",
    "\n",
    "What are the most common roles among celebrities?\n",
    "\n",
    "How does the distribution of heights look like?\n",
    "\n",
    "What is the average age of celebrities based on their date of birth?\n",
    "\n",
    "What is the most common birthplace among celebrities?\n",
    "Temporal Analysis:\n",
    "\n",
    "How has the number of celebrities changed over the years?\n",
    "Is there any trend in the types of roles celebrities hold over time?\n",
    "Are there any patterns in the distribution of awards received over time?\n",
    "Is there a correlation between date of birth and fame?\n",
    "Comparison:\n",
    "\n",
    "How does the distribution of heights differ based on role (e.g., actors vs. athletes)?\n",
    "Are there differences in fame based on birthplace?\n",
    "Do celebrities with awards tend to be ranked higher?\n",
    "Correlation Analysis:\n",
    "\n",
    "Is there a correlation between height and rank?\n",
    "Do celebrities with more awards tend to be more famous?\n",
    "Is there a relationship between date of birth and the role of the celebrity?\n",
    "Visualization:\n",
    "\n",
    "Create histograms or box plots to visualize the distribution of ranks, heights, or ages.\n",
    "Use scatter plots to explore relationships between variables like rank and height, or fame and awards.\n",
    "Plot bar charts to compare the frequency of different roles or birthplaces.\n",
    "Text Analysis:\n",
    "\n",
    "Perform text analysis on the \"Famous_for\" column to identify common themes or keywords associated with celebrity fame.\n",
    "Use natural language processing techniques to extract insights from the \"Famous_for\" column.\n",
    "Dimensionality Reduction:\n",
    "\n",
    "Apply dimensionality reduction techniques like PCA (Principal Component Analysis) to explore relationships among variables and reduce the dataset's complexity.\n",
    "Visualize the dataset in lower-dimensional space to identify clusters or patterns.\n",
    "Outlier Detection:\n",
    "\n",
    "Identify outliers in variables like height or age that may indicate errors or unusual cases.\n",
    "Investigate outliers to understand whether they represent unique cases or data quality issues.\n",
    "Feature Engineering:\n",
    "\n",
    "Create new features based on existing ones, such as extracting the month or year from the date of birth or birthplace features.\n",
    "Combine or transform features to better represent relationships or trends in the data.\n",
    "Predictive Modeling:\n",
    "\n",
    "Build predictive models to forecast future trends in celebrity ranks or fame.\n",
    "Use regression models to predict rank based on other variables like height, awards, or role.\n",
    "By exploring these questions and conducting various analyses, you can gain valuable insights into the Forbes dataset of celebrities and uncover interesting patterns and trends within the data."
   ]
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    "What are the most common roles among celebrities?"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                         ['Actress', 'Soundtrack']\n",
       "1                   ['Actor', 'Director', 'Writer']\n",
       "2                                         ['Actor']\n",
       "3               ['Actress', 'Producer', 'Director']\n",
       "4                 ['Actor', 'Producer', 'Director']\n",
       "                          ...                      \n",
       "95                                      ['Actress']\n",
       "96              ['Actor', 'Producer', 'Soundtrack']\n",
       "97    ['Actress', 'Music Department', 'Soundtrack']\n",
       "98                          ['Actress', 'Producer']\n",
       "99                  ['Actor', 'Writer', 'Producer']\n",
       "Name: Role, Length: 100, dtype: object"
      ]
     },
     "execution_count": 12,
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   ],
   "source": [
    "data[\"Role\"]"
   ]
  },
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   "source": [
    "How does the distribution of heights look like?"
   ]
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  {
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   "source": [
    "def height_in_cm(value):\n",
    "    #5′ 5″ (1.65 m)\n",
    "    try:\n",
    "        # Split the string to extract feet and inches\n",
    "        parts = value.split('(')[1]\n",
    "        value = parts.split(' ')[0]\n",
    "        value = value.replace(\".\", \"\")\n",
    "\n",
    "        return value\n",
    "    \n",
    "    except Exception as e:\n",
    "        return \"NA\""
   ]
  },
  {
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    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Name</th>\n",
       "      <th>Date_of_birth</th>\n",
       "      <th>height</th>\n",
       "      <th>Role</th>\n",
       "      <th>Awards</th>\n",
       "      <th>Famous_for</th>\n",
       "      <th>Birth_place</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>height_in_m</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Sofia Boutella</td>\n",
       "      <td>April 3, 1982</td>\n",
       "      <td>5′ 5″ (1.65 m)</td>\n",
       "      <td>['Actress', 'Soundtrack']</td>\n",
       "      <td>1 win &amp; 2 nominations</td>\n",
       "      <td>Kingsman: The Secret Service (2014)</td>\n",
       "      <td>Bab El Oued, Algeria</td>\n",
       "      <td>1982</td>\n",
       "      <td>165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Ed Skrein</td>\n",
       "      <td>March 29, 1983</td>\n",
       "      <td>6′ 1″ (1.85 m)</td>\n",
       "      <td>['Actor', 'Director', 'Writer']</td>\n",
       "      <td>2 wins &amp; 2 nominations</td>\n",
       "      <td>Deadpool (2016)</td>\n",
       "      <td>Camden, London, England, UK</td>\n",
       "      <td>1983</td>\n",
       "      <td>185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Barry Keoghan</td>\n",
       "      <td>October 18, 1992</td>\n",
       "      <td>5′ 8″ (1.73 m)</td>\n",
       "      <td>['Actor']</td>\n",
       "      <td>11 wins &amp; 76 nominations total</td>\n",
       "      <td>The Killing of a Sacred Deer (2017)</td>\n",
       "      <td>Dublin, Ireland</td>\n",
       "      <td>1992</td>\n",
       "      <td>173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Serinda Swan</td>\n",
       "      <td>July 11, 1984</td>\n",
       "      <td>5′ 7″ (1.70 m)</td>\n",
       "      <td>['Actress', 'Producer', 'Director']</td>\n",
       "      <td>2 nominations</td>\n",
       "      <td>Coroner (2019–2022)</td>\n",
       "      <td>West Vancouver, British Columbia, Canada</td>\n",
       "      <td>1984</td>\n",
       "      <td>170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Alan Ritchson</td>\n",
       "      <td>November 28, 1982</td>\n",
       "      <td>6′ 3″ (1.91 m)</td>\n",
       "      <td>['Actor', 'Producer', 'Director']</td>\n",
       "      <td>3 wins &amp; 3 nominations</td>\n",
       "      <td>Teenage Mutant Ninja Turtles (2014)</td>\n",
       "      <td>Grand Forks, North Dakota, USA</td>\n",
       "      <td>1982</td>\n",
       "      <td>191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>96</td>\n",
       "      <td>Kristin Minter</td>\n",
       "      <td>November 22, 1965</td>\n",
       "      <td>5′ 8″ (1.73 m)</td>\n",
       "      <td>['Actress']</td>\n",
       "      <td>1 nomination</td>\n",
       "      <td>ER (1995–2003)</td>\n",
       "      <td>Miami, Florida, USA</td>\n",
       "      <td>1965</td>\n",
       "      <td>173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>97</td>\n",
       "      <td>Zac Efron</td>\n",
       "      <td>October 18, 1987</td>\n",
       "      <td>5′ 8″ (1.73 m)</td>\n",
       "      <td>['Actor', 'Producer', 'Soundtrack']</td>\n",
       "      <td>35 wins &amp; 44 nominations</td>\n",
       "      <td>17 Again (2009)</td>\n",
       "      <td>San Luis Obispo, California, USA</td>\n",
       "      <td>1987</td>\n",
       "      <td>173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>98</td>\n",
       "      <td>Emma Corrin</td>\n",
       "      <td>December 13, 1995</td>\n",
       "      <td>5′ 8″ (1.73 m)</td>\n",
       "      <td>['Actress', 'Music Department', 'Soundtrack']</td>\n",
       "      <td>10 wins &amp; 10 nominations total</td>\n",
       "      <td>Lady Chatterley's Lover (2022)</td>\n",
       "      <td>Royal Tunbridge Wells, Kent, England, UK</td>\n",
       "      <td>1995</td>\n",
       "      <td>173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>99</td>\n",
       "      <td>Kelly Reilly</td>\n",
       "      <td>July 18, 1977</td>\n",
       "      <td>5′ 6″ (1.68 m)</td>\n",
       "      <td>['Actress', 'Producer']</td>\n",
       "      <td>7 wins &amp; 12 nominations</td>\n",
       "      <td>Pride &amp; Prejudice (2005)</td>\n",
       "      <td>Surrey, England, UK</td>\n",
       "      <td>1977</td>\n",
       "      <td>168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>100</td>\n",
       "      <td>Kamar de los Reyes</td>\n",
       "      <td>November 8, 1967</td>\n",
       "      <td>5′ 10″ (1.78 m)</td>\n",
       "      <td>['Actor', 'Writer', 'Producer']</td>\n",
       "      <td>1 win &amp; 6 nominations</td>\n",
       "      <td>Sleepy Hollow (2017– )</td>\n",
       "      <td>San Juan, Puerto Rico</td>\n",
       "      <td>1967</td>\n",
       "      <td>178</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Rank                Name      Date_of_birth           height  \\\n",
       "0      1      Sofia Boutella      April 3, 1982   5′ 5″ (1.65 m)   \n",
       "1      2           Ed Skrein     March 29, 1983   6′ 1″ (1.85 m)   \n",
       "2      3       Barry Keoghan   October 18, 1992   5′ 8″ (1.73 m)   \n",
       "3      4        Serinda Swan      July 11, 1984   5′ 7″ (1.70 m)   \n",
       "4      5       Alan Ritchson  November 28, 1982   6′ 3″ (1.91 m)   \n",
       "..   ...                 ...                ...              ...   \n",
       "95    96      Kristin Minter  November 22, 1965   5′ 8″ (1.73 m)   \n",
       "96    97           Zac Efron   October 18, 1987   5′ 8″ (1.73 m)   \n",
       "97    98         Emma Corrin  December 13, 1995   5′ 8″ (1.73 m)   \n",
       "98    99        Kelly Reilly      July 18, 1977   5′ 6″ (1.68 m)   \n",
       "99   100  Kamar de los Reyes   November 8, 1967  5′ 10″ (1.78 m)   \n",
       "\n",
       "                                             Role  \\\n",
       "0                       ['Actress', 'Soundtrack']   \n",
       "1                 ['Actor', 'Director', 'Writer']   \n",
       "2                                       ['Actor']   \n",
       "3             ['Actress', 'Producer', 'Director']   \n",
       "4               ['Actor', 'Producer', 'Director']   \n",
       "..                                            ...   \n",
       "95                                    ['Actress']   \n",
       "96            ['Actor', 'Producer', 'Soundtrack']   \n",
       "97  ['Actress', 'Music Department', 'Soundtrack']   \n",
       "98                        ['Actress', 'Producer']   \n",
       "99                ['Actor', 'Writer', 'Producer']   \n",
       "\n",
       "                            Awards                           Famous_for  \\\n",
       "0            1 win & 2 nominations  Kingsman: The Secret Service (2014)   \n",
       "1           2 wins & 2 nominations                      Deadpool (2016)   \n",
       "2   11 wins & 76 nominations total  The Killing of a Sacred Deer (2017)   \n",
       "3                    2 nominations                  Coroner (2019–2022)   \n",
       "4           3 wins & 3 nominations  Teenage Mutant Ninja Turtles (2014)   \n",
       "..                             ...                                  ...   \n",
       "95                    1 nomination                       ER (1995–2003)   \n",
       "96        35 wins & 44 nominations                      17 Again (2009)   \n",
       "97  10 wins & 10 nominations total       Lady Chatterley's Lover (2022)   \n",
       "98         7 wins & 12 nominations             Pride & Prejudice (2005)   \n",
       "99           1 win & 6 nominations               Sleepy Hollow (2017– )   \n",
       "\n",
       "                                 Birth_place  year_of_birth height_in_m  \n",
       "0                       Bab El Oued, Algeria           1982         165  \n",
       "1                Camden, London, England, UK           1983         185  \n",
       "2                            Dublin, Ireland           1992         173  \n",
       "3   West Vancouver, British Columbia, Canada           1984         170  \n",
       "4             Grand Forks, North Dakota, USA           1982         191  \n",
       "..                                       ...            ...         ...  \n",
       "95                       Miami, Florida, USA           1965         173  \n",
       "96          San Luis Obispo, California, USA           1987         173  \n",
       "97  Royal Tunbridge Wells, Kent, England, UK           1995         173  \n",
       "98                       Surrey, England, UK           1977         168  \n",
       "99                     San Juan, Puerto Rico           1967         178  \n",
       "\n",
       "[100 rows x 10 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"height_in_m\"] = data[\"height\"].apply(height_in_cm)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "35601063",
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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Assuming data[\"height_in_m\"] contains the heights in meters\n",
    "\n",
    "# Plotting the heights\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.hist(data[\"height_in_m\"].dropna(), bins=20, color='skyblue', edgecolor='black')\n",
    "plt.title('Distribution of Heights in Meters')\n",
    "plt.xlabel('Height (m)')\n",
    "plt.ylabel('Frequency')\n",
    "plt.grid(True)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4e0d9b66",
   "metadata": {
    "papermill": {
     "duration": 0.007464,
     "end_time": "2024-03-22T17:50:20.354272",
     "exception": false,
     "start_time": "2024-03-22T17:50:20.346808",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kaggle": {
   "accelerator": "none",
   "dataSources": [
    {
     "datasetId": 3535700,
     "sourceId": 7328620,
     "sourceType": "datasetVersion"
    }
   ],
   "dockerImageVersionId": 30673,
   "isGpuEnabled": false,
   "isInternetEnabled": true,
   "language": "python",
   "sourceType": "notebook"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.13"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 4.336047,
   "end_time": "2024-03-22T17:50:20.681818",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2024-03-22T17:50:16.345771",
   "version": "2.5.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}