Clase 3 - Pandas Tranformaciones.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Transformaciones"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>birthplace</th>\n",
       "      <th>date_of_birth</th>\n",
       "      <th>race_ethnicity</th>\n",
       "      <th>religion</th>\n",
       "      <th>sexual_orientation</th>\n",
       "      <th>year_of_award</th>\n",
       "      <th>award</th>\n",
       "      <th>movie</th>\n",
       "      <th>person</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>age_at_award</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>London, England</td>\n",
       "      <td>1971-03-07</td>\n",
       "      <td>White</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2006</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>The Constant Gardener</td>\n",
       "      <td>Rachel Weisz</td>\n",
       "      <td>1971.0</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>Manchester, England</td>\n",
       "      <td>2056-10-20</td>\n",
       "      <td>White</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2009</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>Slumdog Millionaire</td>\n",
       "      <td>Danny Boyle</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>Chicago, Il</td>\n",
       "      <td>2022-07-26</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1977</td>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>All the President's Men</td>\n",
       "      <td>Jason Robards</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>Laurel, Ne</td>\n",
       "      <td>2028-08-31</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1999</td>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Affliction</td>\n",
       "      <td>James Coburn</td>\n",
       "      <td>1928.0</td>\n",
       "      <td>71.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>Nevada, Mo</td>\n",
       "      <td>2006-08-05</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1949</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>The Treasure of the Sierra Madre</td>\n",
       "      <td>John Huston</td>\n",
       "      <td>1906.0</td>\n",
       "      <td>43.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              birthplace date_of_birth race_ethnicity        religion  \\\n",
       "436      London, England    1971-03-07          White          Jewish   \n",
       "437  Manchester, England    2056-10-20          White  Roman Catholic   \n",
       "438          Chicago, Il    2022-07-26          White              Na   \n",
       "439           Laurel, Ne    2028-08-31          White              Na   \n",
       "440           Nevada, Mo    2006-08-05          White              Na   \n",
       "\n",
       "    sexual_orientation  year_of_award                    award  \\\n",
       "436           Straight           2006  Best Supporting Actress   \n",
       "437           Straight           2009            Best Director   \n",
       "438           Straight           1977    Best Supporting Actor   \n",
       "439           Straight           1999    Best Supporting Actor   \n",
       "440           Straight           1949            Best Director   \n",
       "\n",
       "                                movie         person  year_of_birth  \\\n",
       "436             The Constant Gardener   Rachel Weisz         1971.0   \n",
       "437               Slumdog Millionaire    Danny Boyle         1956.0   \n",
       "438           All the President's Men  Jason Robards         1922.0   \n",
       "439                        Affliction   James Coburn         1928.0   \n",
       "440  The Treasure of the Sierra Madre    John Huston         1906.0   \n",
       "\n",
       "     age_at_award  \n",
       "436          35.0  \n",
       "437          53.0  \n",
       "438          55.0  \n",
       "439          71.0  \n",
       "440          43.0  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "#Lectura del csv, tomo columnas que me interesan \n",
    "\n",
    "oscars = pd.read_csv('./Datasets/Oscars-demographics.csv', encoding='latin-1', usecols=['birthplace', 'date_of_birth',\\\n",
    "                                                                             'race_ethnicity', 'religion',\\\n",
    "                                                                             'sexual_orientation', 'year_of_award',\\\n",
    "                                                                             'award', 'movie', 'person'])\n",
    "\n",
    "#Correcion de columnas con informacion incorrecta\n",
    "\n",
    "oscars.loc[:, 'date_of_birth'] = pd.to_datetime(oscars['date_of_birth'], errors='coerce')\n",
    "oscars['year_of_birth'] = oscars.loc[:, 'date_of_birth'].dt.year\n",
    "oscars['age_at_award'] = oscars['year_of_award'] - (oscars['date_of_birth'].dt.year)\n",
    "oscars.loc[oscars['age_at_award'] < 1, 'year_of_birth'] = oscars.loc[oscars['age_at_award'] < 1, 'year_of_birth'] - 100\n",
    "oscars['age_at_award'] = oscars['year_of_award'] - oscars['year_of_birth']\n",
    "oscars.tail(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "oscars_best_actress = oscars.loc[oscars['award'].str.contains('Best Actress'),:]\n",
    "oscars_best_actor = oscars.loc[oscars['award'].str.contains('Best Actor'),:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
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       "      <th></th>\n",
       "      <th>birthplace</th>\n",
       "      <th>date_of_birth</th>\n",
       "      <th>race_ethnicity</th>\n",
       "      <th>religion</th>\n",
       "      <th>sexual_orientation</th>\n",
       "      <th>year_of_award</th>\n",
       "      <th>award</th>\n",
       "      <th>movie</th>\n",
       "      <th>person</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>age_at_award</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>251</th>\n",
       "      <td>Philadelphia, Pa</td>\n",
       "      <td>2006-10-06</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1929</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>7th Heaven</td>\n",
       "      <td>Janet Gaynor</td>\n",
       "      <td>1906.0</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>252</th>\n",
       "      <td>Toronto, Ontario, Canada</td>\n",
       "      <td>1892-04-08</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1930</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Coquette</td>\n",
       "      <td>Mary Pickford</td>\n",
       "      <td>1892.0</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253</th>\n",
       "      <td>Montreal, Quebec, Canada</td>\n",
       "      <td>1902-08-10</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1930</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>The Divorcee</td>\n",
       "      <td>Norma Shearer</td>\n",
       "      <td>1902.0</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>254</th>\n",
       "      <td>Cobourg, Ontario, Canada</td>\n",
       "      <td>1868-11-02</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1931</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Min and Bill</td>\n",
       "      <td>Marie Dressler</td>\n",
       "      <td>1868.0</td>\n",
       "      <td>63.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>Washington, Dc</td>\n",
       "      <td>1900-10-10</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1932</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>The Sin of Madelon Claudet</td>\n",
       "      <td>Helen Hayes</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   birthplace date_of_birth race_ethnicity religion  \\\n",
       "251          Philadelphia, Pa    2006-10-06          White       Na   \n",
       "252  Toronto, Ontario, Canada    1892-04-08          White       Na   \n",
       "253  Montreal, Quebec, Canada    1902-08-10          White       Na   \n",
       "254  Cobourg, Ontario, Canada    1868-11-02          White       Na   \n",
       "255            Washington, Dc    1900-10-10          White       Na   \n",
       "\n",
       "    sexual_orientation  year_of_award         award  \\\n",
       "251           Straight           1929  Best Actress   \n",
       "252           Straight           1930  Best Actress   \n",
       "253           Straight           1930  Best Actress   \n",
       "254           Straight           1931  Best Actress   \n",
       "255           Straight           1932  Best Actress   \n",
       "\n",
       "                          movie          person  year_of_birth  age_at_award  \n",
       "251                  7th Heaven    Janet Gaynor         1906.0          23.0  \n",
       "252                    Coquette   Mary Pickford         1892.0          38.0  \n",
       "253                The Divorcee   Norma Shearer         1902.0          28.0  \n",
       "254                Min and Bill  Marie Dressler         1868.0          63.0  \n",
       "255  The Sin of Madelon Claudet     Helen Hayes         1900.0          32.0  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oscars_best_actress.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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       "      <th>birthplace</th>\n",
       "      <th>date_of_birth</th>\n",
       "      <th>race_ethnicity</th>\n",
       "      <th>religion</th>\n",
       "      <th>sexual_orientation</th>\n",
       "      <th>year_of_award</th>\n",
       "      <th>award</th>\n",
       "      <th>movie</th>\n",
       "      <th>person</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>age_at_award</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>Rorschach, Switzerland</td>\n",
       "      <td>1884-07-23</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Bisexual</td>\n",
       "      <td>1929</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>The Last Command</td>\n",
       "      <td>Emil Jannings</td>\n",
       "      <td>1884.0</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>Columbus, Oh</td>\n",
       "      <td>1889-03-29</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1930</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>In Old Arizona</td>\n",
       "      <td>Warner Baxter</td>\n",
       "      <td>1889.0</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>London, England</td>\n",
       "      <td>1868-04-10</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1930</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Desraeli</td>\n",
       "      <td>George Arliss</td>\n",
       "      <td>1868.0</td>\n",
       "      <td>62.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>Philadelphia, Pa</td>\n",
       "      <td>1878-04-28</td>\n",
       "      <td>White</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1931</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>A Free Soul</td>\n",
       "      <td>Lionel Barrymore</td>\n",
       "      <td>1878.0</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>Kansas City, Mo</td>\n",
       "      <td>1885-04-01</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1932</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>The Champ</td>\n",
       "      <td>Wallace Beery</td>\n",
       "      <td>1885.0</td>\n",
       "      <td>47.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                birthplace date_of_birth race_ethnicity        religion  \\\n",
       "87  Rorschach, Switzerland    1884-07-23          White              Na   \n",
       "88            Columbus, Oh    1889-03-29          White              Na   \n",
       "89         London, England    1868-04-10          White              Na   \n",
       "90        Philadelphia, Pa    1878-04-28          White  Roman Catholic   \n",
       "91         Kansas City, Mo    1885-04-01          White              Na   \n",
       "\n",
       "   sexual_orientation  year_of_award       award             movie  \\\n",
       "87           Bisexual           1929  Best Actor  The Last Command   \n",
       "88           Straight           1930  Best Actor    In Old Arizona   \n",
       "89           Straight           1930  Best Actor          Desraeli   \n",
       "90           Straight           1931  Best Actor       A Free Soul   \n",
       "91           Straight           1932  Best Actor         The Champ   \n",
       "\n",
       "              person  year_of_birth  age_at_award  \n",
       "87     Emil Jannings         1884.0          45.0  \n",
       "88     Warner Baxter         1889.0          41.0  \n",
       "89     George Arliss         1868.0          62.0  \n",
       "90  Lionel Barrymore         1878.0          53.0  \n",
       "91     Wallace Beery         1885.0          47.0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oscars_best_actor.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Append"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>Rorschach, Switzerland</td>\n",
       "      <td>1884-07-23</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Bisexual</td>\n",
       "      <td>1929</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>The Last Command</td>\n",
       "      <td>Emil Jannings</td>\n",
       "      <td>1884.0</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>Columbus, Oh</td>\n",
       "      <td>1889-03-29</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1930</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>In Old Arizona</td>\n",
       "      <td>Warner Baxter</td>\n",
       "      <td>1889.0</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>London, England</td>\n",
       "      <td>1868-04-10</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1930</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Desraeli</td>\n",
       "      <td>George Arliss</td>\n",
       "      <td>1868.0</td>\n",
       "      <td>62.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>Philadelphia, Pa</td>\n",
       "      <td>1878-04-28</td>\n",
       "      <td>White</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1931</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>A Free Soul</td>\n",
       "      <td>Lionel Barrymore</td>\n",
       "      <td>1878.0</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>Kansas City, Mo</td>\n",
       "      <td>1885-04-01</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1932</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>The Champ</td>\n",
       "      <td>Wallace Beery</td>\n",
       "      <td>1885.0</td>\n",
       "      <td>47.0</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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>London, England</td>\n",
       "      <td>2032-02-27</td>\n",
       "      <td>White</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1967</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Who's Afraid of Virginia Woolf?</td>\n",
       "      <td>Elizabeth Taylor</td>\n",
       "      <td>1932.0</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>Lincoln, Ne</td>\n",
       "      <td>1974-07-30</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2005</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Million Dollar Baby</td>\n",
       "      <td>Hilary Swank</td>\n",
       "      <td>1974.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>Lincoln, Ne</td>\n",
       "      <td>1974-07-30</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2005</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Million Dollar Baby</td>\n",
       "      <td>Hilary Swank</td>\n",
       "      <td>1974.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>Los Angeles, Ca</td>\n",
       "      <td>1972-09-27</td>\n",
       "      <td>White</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1999</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Shakespeare in Love</td>\n",
       "      <td>Gwyneth Paltrow</td>\n",
       "      <td>1972.0</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>435</th>\n",
       "      <td>Ilford, Essex, England</td>\n",
       "      <td>2034-12-28</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1970</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>The Prime of Miss Jean Brodie</td>\n",
       "      <td>Maggie Smith</td>\n",
       "      <td>1934.0</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>183 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 birthplace date_of_birth race_ethnicity        religion  \\\n",
       "87   Rorschach, Switzerland    1884-07-23          White              Na   \n",
       "88             Columbus, Oh    1889-03-29          White              Na   \n",
       "89          London, England    1868-04-10          White              Na   \n",
       "90         Philadelphia, Pa    1878-04-28          White  Roman Catholic   \n",
       "91          Kansas City, Mo    1885-04-01          White              Na   \n",
       "..                      ...           ...            ...             ...   \n",
       "428         London, England    2032-02-27          White          Jewish   \n",
       "429             Lincoln, Ne    1974-07-30          White              Na   \n",
       "430             Lincoln, Ne    1974-07-30          White              Na   \n",
       "431         Los Angeles, Ca    1972-09-27          White          Jewish   \n",
       "435  Ilford, Essex, England    2034-12-28          White              Na   \n",
       "\n",
       "    sexual_orientation  year_of_award         award  \\\n",
       "87            Bisexual           1929    Best Actor   \n",
       "88            Straight           1930    Best Actor   \n",
       "89            Straight           1930    Best Actor   \n",
       "90            Straight           1931    Best Actor   \n",
       "91            Straight           1932    Best Actor   \n",
       "..                 ...            ...           ...   \n",
       "428           Straight           1967  Best Actress   \n",
       "429           Straight           2005  Best Actress   \n",
       "430           Straight           2005  Best Actress   \n",
       "431           Straight           1999  Best Actress   \n",
       "435           Straight           1970  Best Actress   \n",
       "\n",
       "                               movie            person  year_of_birth  \\\n",
       "87                  The Last Command     Emil Jannings         1884.0   \n",
       "88                    In Old Arizona     Warner Baxter         1889.0   \n",
       "89                          Desraeli     George Arliss         1868.0   \n",
       "90                       A Free Soul  Lionel Barrymore         1878.0   \n",
       "91                         The Champ     Wallace Beery         1885.0   \n",
       "..                               ...               ...            ...   \n",
       "428  Who's Afraid of Virginia Woolf?  Elizabeth Taylor         1932.0   \n",
       "429              Million Dollar Baby      Hilary Swank         1974.0   \n",
       "430              Million Dollar Baby      Hilary Swank         1974.0   \n",
       "431              Shakespeare in Love   Gwyneth Paltrow         1972.0   \n",
       "435    The Prime of Miss Jean Brodie      Maggie Smith         1934.0   \n",
       "\n",
       "     age_at_award  \n",
       "87           45.0  \n",
       "88           41.0  \n",
       "89           62.0  \n",
       "90           53.0  \n",
       "91           47.0  \n",
       "..            ...  \n",
       "428          35.0  \n",
       "429          31.0  \n",
       "430          31.0  \n",
       "431          27.0  \n",
       "435          36.0  \n",
       "\n",
       "[183 rows x 11 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Combina best actor con best actress\n",
    "oscars_best_actor_actress = oscars_best_actor.append(oscars_best_actress)\n",
    "oscars_best_actor_actress"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "88"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(oscars_best_actor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "95"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(oscars_best_actress)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "183"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Se suma la cantidad de filas, 88 + 95 = 183\n",
    "len(oscars_best_actor_actress)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Concat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\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>birthplace</th>\n",
       "      <th>date_of_birth</th>\n",
       "      <th>race_ethnicity</th>\n",
       "      <th>religion</th>\n",
       "      <th>sexual_orientation</th>\n",
       "      <th>year_of_award</th>\n",
       "      <th>award</th>\n",
       "      <th>movie</th>\n",
       "      <th>person</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>age_at_award</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>Rorschach, Switzerland</td>\n",
       "      <td>1884-07-23</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Bisexual</td>\n",
       "      <td>1929</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>The Last Command</td>\n",
       "      <td>Emil Jannings</td>\n",
       "      <td>1884.0</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>Columbus, Oh</td>\n",
       "      <td>1889-03-29</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1930</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>In Old Arizona</td>\n",
       "      <td>Warner Baxter</td>\n",
       "      <td>1889.0</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>London, England</td>\n",
       "      <td>1868-04-10</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1930</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Desraeli</td>\n",
       "      <td>George Arliss</td>\n",
       "      <td>1868.0</td>\n",
       "      <td>62.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>Philadelphia, Pa</td>\n",
       "      <td>1878-04-28</td>\n",
       "      <td>White</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1931</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>A Free Soul</td>\n",
       "      <td>Lionel Barrymore</td>\n",
       "      <td>1878.0</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>Kansas City, Mo</td>\n",
       "      <td>1885-04-01</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1932</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>The Champ</td>\n",
       "      <td>Wallace Beery</td>\n",
       "      <td>1885.0</td>\n",
       "      <td>47.0</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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>London, England</td>\n",
       "      <td>2032-02-27</td>\n",
       "      <td>White</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1967</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Who's Afraid of Virginia Woolf?</td>\n",
       "      <td>Elizabeth Taylor</td>\n",
       "      <td>1932.0</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>Lincoln, Ne</td>\n",
       "      <td>1974-07-30</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2005</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Million Dollar Baby</td>\n",
       "      <td>Hilary Swank</td>\n",
       "      <td>1974.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>Lincoln, Ne</td>\n",
       "      <td>1974-07-30</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2005</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Million Dollar Baby</td>\n",
       "      <td>Hilary Swank</td>\n",
       "      <td>1974.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>Los Angeles, Ca</td>\n",
       "      <td>1972-09-27</td>\n",
       "      <td>White</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1999</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Shakespeare in Love</td>\n",
       "      <td>Gwyneth Paltrow</td>\n",
       "      <td>1972.0</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>435</th>\n",
       "      <td>Ilford, Essex, England</td>\n",
       "      <td>2034-12-28</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1970</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>The Prime of Miss Jean Brodie</td>\n",
       "      <td>Maggie Smith</td>\n",
       "      <td>1934.0</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>183 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 birthplace date_of_birth race_ethnicity        religion  \\\n",
       "87   Rorschach, Switzerland    1884-07-23          White              Na   \n",
       "88             Columbus, Oh    1889-03-29          White              Na   \n",
       "89          London, England    1868-04-10          White              Na   \n",
       "90         Philadelphia, Pa    1878-04-28          White  Roman Catholic   \n",
       "91          Kansas City, Mo    1885-04-01          White              Na   \n",
       "..                      ...           ...            ...             ...   \n",
       "428         London, England    2032-02-27          White          Jewish   \n",
       "429             Lincoln, Ne    1974-07-30          White              Na   \n",
       "430             Lincoln, Ne    1974-07-30          White              Na   \n",
       "431         Los Angeles, Ca    1972-09-27          White          Jewish   \n",
       "435  Ilford, Essex, England    2034-12-28          White              Na   \n",
       "\n",
       "    sexual_orientation  year_of_award         award  \\\n",
       "87            Bisexual           1929    Best Actor   \n",
       "88            Straight           1930    Best Actor   \n",
       "89            Straight           1930    Best Actor   \n",
       "90            Straight           1931    Best Actor   \n",
       "91            Straight           1932    Best Actor   \n",
       "..                 ...            ...           ...   \n",
       "428           Straight           1967  Best Actress   \n",
       "429           Straight           2005  Best Actress   \n",
       "430           Straight           2005  Best Actress   \n",
       "431           Straight           1999  Best Actress   \n",
       "435           Straight           1970  Best Actress   \n",
       "\n",
       "                               movie            person  year_of_birth  \\\n",
       "87                  The Last Command     Emil Jannings         1884.0   \n",
       "88                    In Old Arizona     Warner Baxter         1889.0   \n",
       "89                          Desraeli     George Arliss         1868.0   \n",
       "90                       A Free Soul  Lionel Barrymore         1878.0   \n",
       "91                         The Champ     Wallace Beery         1885.0   \n",
       "..                               ...               ...            ...   \n",
       "428  Who's Afraid of Virginia Woolf?  Elizabeth Taylor         1932.0   \n",
       "429              Million Dollar Baby      Hilary Swank         1974.0   \n",
       "430              Million Dollar Baby      Hilary Swank         1974.0   \n",
       "431              Shakespeare in Love   Gwyneth Paltrow         1972.0   \n",
       "435    The Prime of Miss Jean Brodie      Maggie Smith         1934.0   \n",
       "\n",
       "     age_at_award  \n",
       "87           45.0  \n",
       "88           41.0  \n",
       "89           62.0  \n",
       "90           53.0  \n",
       "91           47.0  \n",
       "..            ...  \n",
       "428          35.0  \n",
       "429          31.0  \n",
       "430          31.0  \n",
       "431          27.0  \n",
       "435          36.0  \n",
       "\n",
       "[183 rows x 11 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oscars_best_actor_actress_concat = pd.concat([oscars_best_actor, oscars_best_actress])\n",
    "oscars_best_actor_actress_concat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Merge/Join\n",
    "\n",
    "\n",
    "Tipos:\n",
    "- \"inner\": Intersección de x e y.\n",
    "\n",
    "- \"outer\": Unión de x e y.\n",
    "\n",
    "- \"left\": Claves que estan en x junto con las claves de y, algunas claves de y pueden no tener dato.\n",
    "\n",
    "- \"right\": Análogo a left pero con y. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">age_at_award</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year_of_award</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>49.4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>41.6</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>54.2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>45.2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>41.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              age_at_award      \n",
       "                      mean count\n",
       "year_of_award                   \n",
       "2010                  49.4     5\n",
       "2011                  41.6     5\n",
       "2012                  54.2     5\n",
       "2013                  45.2     5\n",
       "2014                  41.0     4"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped = oscars.groupby(['year_of_award']).agg({'age_at_award':['mean', 'count']})\n",
    "grouped.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year_of_award</th>\n",
       "      <th>age_at_award_mean</th>\n",
       "      <th>age_at_award_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>2010</td>\n",
       "      <td>49.4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>2011</td>\n",
       "      <td>41.6</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>2012</td>\n",
       "      <td>54.2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>2013</td>\n",
       "      <td>45.2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>2014</td>\n",
       "      <td>41.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    year_of_award  age_at_award_mean  age_at_award_count\n",
       "82           2010               49.4                   5\n",
       "83           2011               41.6                   5\n",
       "84           2012               54.2                   5\n",
       "85           2013               45.2                   5\n",
       "86           2014               41.0                   4"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Como hay dos niveles de claves las concatenamos\n",
    "level_0 = grouped.columns.get_level_values(0)\n",
    "level_1 = grouped.columns.get_level_values(1)\n",
    "#Suma columna a columna los nombres de los niveles\n",
    "grouped.columns = level_0 + '_' + level_1\n",
    "#Cambiamos el índice al default, previamente estaba year_of_award\n",
    "grouped.reset_index(inplace=True)\n",
    "grouped.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>birthplace</th>\n",
       "      <th>date_of_birth</th>\n",
       "      <th>race_ethnicity</th>\n",
       "      <th>religion</th>\n",
       "      <th>sexual_orientation</th>\n",
       "      <th>year_of_award</th>\n",
       "      <th>award</th>\n",
       "      <th>movie</th>\n",
       "      <th>person</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>age_at_award</th>\n",
       "      <th>age_at_award_mean</th>\n",
       "      <th>age_at_award_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>Woodlawn, Md</td>\n",
       "      <td>2067-12-11</td>\n",
       "      <td>Black</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2010</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Precious</td>\n",
       "      <td>Mo'Nique</td>\n",
       "      <td>1967.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>49.4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>Uvalde, Tx</td>\n",
       "      <td>2069-11-04</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2014</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Dallas Buyers Club</td>\n",
       "      <td>Matthew McConaughey</td>\n",
       "      <td>1969.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>Bossier City, La</td>\n",
       "      <td>1971-12-26</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2014</td>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Dallas Buyers Club</td>\n",
       "      <td>Jared Leto</td>\n",
       "      <td>1971.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>Melbourne, Victoria, Australia</td>\n",
       "      <td>2069-05-14</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2014</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Blue Jasmine</td>\n",
       "      <td>Cate Blanchett</td>\n",
       "      <td>1969.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>Mexico City, Mexico</td>\n",
       "      <td>1983-03-01</td>\n",
       "      <td>Black</td>\n",
       "      <td>Na</td>\n",
       "      <td>Na</td>\n",
       "      <td>2014</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>12 Years a Slave</td>\n",
       "      <td>Lupita Nyong'o</td>\n",
       "      <td>1983.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         birthplace date_of_birth race_ethnicity religion  \\\n",
       "436                    Woodlawn, Md    2067-12-11          Black       Na   \n",
       "437                      Uvalde, Tx    2069-11-04          White       Na   \n",
       "438                Bossier City, La    1971-12-26          White       Na   \n",
       "439  Melbourne, Victoria, Australia    2069-05-14          White       Na   \n",
       "440             Mexico City, Mexico    1983-03-01          Black       Na   \n",
       "\n",
       "    sexual_orientation  year_of_award                    award  \\\n",
       "436           Straight           2010  Best Supporting Actress   \n",
       "437           Straight           2014               Best Actor   \n",
       "438           Straight           2014    Best Supporting Actor   \n",
       "439           Straight           2014             Best Actress   \n",
       "440                 Na           2014  Best Supporting Actress   \n",
       "\n",
       "                  movie               person  year_of_birth  age_at_award  \\\n",
       "436            Precious             Mo'Nique         1967.0          43.0   \n",
       "437  Dallas Buyers Club  Matthew McConaughey         1969.0          45.0   \n",
       "438  Dallas Buyers Club           Jared Leto         1971.0          43.0   \n",
       "439        Blue Jasmine       Cate Blanchett         1969.0          45.0   \n",
       "440    12 Years a Slave       Lupita Nyong'o         1983.0          31.0   \n",
       "\n",
       "     age_at_award_mean  age_at_award_count  \n",
       "436               49.4                   5  \n",
       "437               41.0                   4  \n",
       "438               41.0                   4  \n",
       "439               41.0                   4  \n",
       "440               41.0                   4  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#left_on es la columna 'year_of_award' de oscars\n",
    "#right_on es la columna 'year_of_award' de grouped\n",
    "oscars_per_year = oscars.merge(grouped, left_on='year_of_award', right_on='year_of_award', how='outer')\n",
    "oscars_per_year.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\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>year_of_award</th>\n",
       "      <th>age_at_award_mean</th>\n",
       "      <th>age_at_award_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>1996</td>\n",
       "      <td>37.600000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>2000</td>\n",
       "      <td>36.500000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>2001</td>\n",
       "      <td>37.833333</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>2004</td>\n",
       "      <td>38.250000</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>2006</td>\n",
       "      <td>39.333333</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    year_of_award  age_at_award_mean  age_at_award_count\n",
       "68           1996          37.600000                   5\n",
       "72           2000          36.500000                   6\n",
       "73           2001          37.833333                   6\n",
       "76           2004          38.250000                   4\n",
       "78           2006          39.333333                   6"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "year_lt_40 = grouped.loc[grouped['age_at_award_mean'] < 40, :]\n",
    "year_lt_40.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>birthplace</th>\n",
       "      <th>date_of_birth</th>\n",
       "      <th>race_ethnicity</th>\n",
       "      <th>religion</th>\n",
       "      <th>sexual_orientation</th>\n",
       "      <th>year_of_award</th>\n",
       "      <th>award</th>\n",
       "      <th>movie</th>\n",
       "      <th>person</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>age_at_award</th>\n",
       "      <th>age_at_award_mean</th>\n",
       "      <th>age_at_award_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Chisinau, Moldova</td>\n",
       "      <td>1895-09-30</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1927</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>Two Arabian Knights</td>\n",
       "      <td>Lewis Milestone</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Chicago, Il</td>\n",
       "      <td>1899-02-23</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1932</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>Skippy</td>\n",
       "      <td>Norman Taurog</td>\n",
       "      <td>1899.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>37.333333</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Kansas City, Mo</td>\n",
       "      <td>1885-04-01</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1932</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>The Champ</td>\n",
       "      <td>Wallace Beery</td>\n",
       "      <td>1885.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>37.333333</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Washington, Dc</td>\n",
       "      <td>1900-10-10</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1932</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>The Sin of Madelon Claudet</td>\n",
       "      <td>Helen Hayes</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>37.333333</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Salt Lake City, Ut</td>\n",
       "      <td>1894-04-23</td>\n",
       "      <td>White</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1933</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>Bad Girl</td>\n",
       "      <td>Frank Borzage</td>\n",
       "      <td>1894.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>1</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>New Orleans, La</td>\n",
       "      <td>1976-03-22</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2006</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Walk the Line</td>\n",
       "      <td>Reese Witherspoon</td>\n",
       "      <td>1976.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>39.333333</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>London, England</td>\n",
       "      <td>1971-03-07</td>\n",
       "      <td>White</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2006</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>The Constant Gardener</td>\n",
       "      <td>Rachel Weisz</td>\n",
       "      <td>1971.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>39.333333</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>London, England</td>\n",
       "      <td>1971-03-07</td>\n",
       "      <td>White</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2006</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>The Constant Gardener</td>\n",
       "      <td>Rachel Weisz</td>\n",
       "      <td>1971.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>39.333333</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>Rorschach, Switzerland</td>\n",
       "      <td>1884-07-23</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Bisexual</td>\n",
       "      <td>1929</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>The Last Command</td>\n",
       "      <td>Emil Jannings</td>\n",
       "      <td>1884.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>Philadelphia, Pa</td>\n",
       "      <td>2006-10-06</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1929</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>7th Heaven</td>\n",
       "      <td>Janet Gaynor</td>\n",
       "      <td>1906.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>113 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 birthplace date_of_birth race_ethnicity        religion  \\\n",
       "0         Chisinau, Moldova    1895-09-30          White              Na   \n",
       "1               Chicago, Il    1899-02-23          White              Na   \n",
       "2           Kansas City, Mo    1885-04-01          White              Na   \n",
       "3            Washington, Dc    1900-10-10          White              Na   \n",
       "4        Salt Lake City, Ut    1894-04-23          White  Roman Catholic   \n",
       "..                      ...           ...            ...             ...   \n",
       "108         New Orleans, La    1976-03-22          White              Na   \n",
       "109         London, England    1971-03-07          White          Jewish   \n",
       "110         London, England    1971-03-07          White          Jewish   \n",
       "111  Rorschach, Switzerland    1884-07-23          White              Na   \n",
       "112        Philadelphia, Pa    2006-10-06          White              Na   \n",
       "\n",
       "    sexual_orientation  year_of_award                    award  \\\n",
       "0             Straight           1927            Best Director   \n",
       "1             Straight           1932            Best Director   \n",
       "2             Straight           1932               Best Actor   \n",
       "3             Straight           1932             Best Actress   \n",
       "4             Straight           1933            Best Director   \n",
       "..                 ...            ...                      ...   \n",
       "108           Straight           2006             Best Actress   \n",
       "109           Straight           2006  Best Supporting Actress   \n",
       "110           Straight           2006  Best Supporting Actress   \n",
       "111           Bisexual           1929               Best Actor   \n",
       "112           Straight           1929             Best Actress   \n",
       "\n",
       "                          movie             person  year_of_birth  \\\n",
       "0           Two Arabian Knights    Lewis Milestone         1895.0   \n",
       "1                        Skippy      Norman Taurog         1899.0   \n",
       "2                     The Champ      Wallace Beery         1885.0   \n",
       "3    The Sin of Madelon Claudet        Helen Hayes         1900.0   \n",
       "4                      Bad Girl      Frank Borzage         1894.0   \n",
       "..                          ...                ...            ...   \n",
       "108               Walk the Line  Reese Witherspoon         1976.0   \n",
       "109       The Constant Gardener       Rachel Weisz         1971.0   \n",
       "110       The Constant Gardener       Rachel Weisz         1971.0   \n",
       "111            The Last Command      Emil Jannings         1884.0   \n",
       "112                  7th Heaven       Janet Gaynor         1906.0   \n",
       "\n",
       "     age_at_award  age_at_award_mean  age_at_award_count  \n",
       "0            32.0          32.000000                   1  \n",
       "1            33.0          37.333333                   3  \n",
       "2            47.0          37.333333                   3  \n",
       "3            32.0          37.333333                   3  \n",
       "4            39.0          39.000000                   1  \n",
       "..            ...                ...                 ...  \n",
       "108          30.0          39.333333                   6  \n",
       "109          35.0          39.333333                   6  \n",
       "110          35.0          39.333333                   6  \n",
       "111          45.0          34.000000                   2  \n",
       "112          23.0          34.000000                   2  \n",
       "\n",
       "[113 rows x 13 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Por default merge aplica \"inner\"\n",
    "oscars.merge(year_lt_40, left_on='year_of_award', right_on='year_of_award')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Grouping ####\n",
    "\n",
    "Trabajar con datos de distintas filas al mismo tiempo. Split, apply, combine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">age_at_award</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>award</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Best Actor</th>\n",
       "      <td>45.045455</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Best Actress</th>\n",
       "      <td>36.421053</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Best Director</th>\n",
       "      <td>47.300000</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Best Supporting Actor</th>\n",
       "      <td>50.890244</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Best Supporting Actress</th>\n",
       "      <td>40.505882</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        age_at_award      \n",
       "                                mean count\n",
       "award                                     \n",
       "Best Actor                 45.045455    88\n",
       "Best Actress               36.421053    95\n",
       "Best Director              47.300000    90\n",
       "Best Supporting Actor      50.890244    82\n",
       "Best Supporting Actress    40.505882    85"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped = oscars.groupby(['award']).agg({'age_at_award':['mean', 'count']})\n",
    "grouped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">age_at_award</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year_of_award</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>49.4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>41.6</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>54.2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>45.2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>41.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              age_at_award      \n",
       "                      mean count\n",
       "year_of_award                   \n",
       "2010                  49.4     5\n",
       "2011                  41.6     5\n",
       "2012                  54.2     5\n",
       "2013                  45.2     5\n",
       "2014                  41.0     4"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped = oscars.groupby(['year_of_award']).agg({'age_at_award':['mean', 'count']})\n",
    "grouped.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">age_at_award</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year_of_award</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1969</th>\n",
       "      <td>54.750000</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>53.166667</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>51.571429</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1977</th>\n",
       "      <td>51.000000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1976</th>\n",
       "      <td>49.142857</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1953</th>\n",
       "      <td>47.666667</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990</th>\n",
       "      <td>47.166667</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1973</th>\n",
       "      <td>44.833333</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>44.571429</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1970</th>\n",
       "      <td>44.500000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              age_at_award      \n",
       "                      mean count\n",
       "year_of_award                   \n",
       "1969             54.750000     8\n",
       "2007             53.166667     6\n",
       "1999             51.571429     7\n",
       "1977             51.000000     6\n",
       "1976             49.142857     7\n",
       "1953             47.666667     6\n",
       "1990             47.166667     6\n",
       "1973             44.833333     6\n",
       "2009             44.571429     7\n",
       "1970             44.500000     6"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#La columna age_at_award, count es una tupla y se accede de la siguiente forma\n",
    "grouped.loc[grouped[('age_at_award', 'count')] > 5, :].sort_values(('age_at_award','mean'), ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Category')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "oscars.groupby('award').mean().loc[:, 'age_at_award'].plot(kind='bar', title='Average age by Award category', linewidth=2, figsize=(10, 6), color='lightpink')\n",
    "ax = plt.gca()\n",
    "ax.set_ylabel('Average Age')\n",
    "ax.set_xlabel('Category')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Acceder a valores agrupados con `get_group()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>birthplace</th>\n",
       "      <th>date_of_birth</th>\n",
       "      <th>race_ethnicity</th>\n",
       "      <th>religion</th>\n",
       "      <th>sexual_orientation</th>\n",
       "      <th>year_of_award</th>\n",
       "      <th>award</th>\n",
       "      <th>movie</th>\n",
       "      <th>person</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>age_at_award</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Chisinau, Moldova</td>\n",
       "      <td>1895-09-30</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1927</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>Two Arabian Knights</td>\n",
       "      <td>Lewis Milestone</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Glasgow, Scotland</td>\n",
       "      <td>1886-02-02</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1930</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>The Divine Lady</td>\n",
       "      <td>Frank Lloyd</td>\n",
       "      <td>1886.0</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Chisinau, Moldova</td>\n",
       "      <td>1895-09-30</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1931</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>All Quiet on the Western Front</td>\n",
       "      <td>Lewis Milestone</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Chicago, Il</td>\n",
       "      <td>1899-02-23</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1932</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>Skippy</td>\n",
       "      <td>Norman Taurog</td>\n",
       "      <td>1899.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Salt Lake City, Ut</td>\n",
       "      <td>1894-04-23</td>\n",
       "      <td>White</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1933</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>Bad Girl</td>\n",
       "      <td>Frank Borzage</td>\n",
       "      <td>1894.0</td>\n",
       "      <td>39.0</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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>London, England</td>\n",
       "      <td>1971-03-07</td>\n",
       "      <td>White</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2006</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>The Constant Gardener</td>\n",
       "      <td>Rachel Weisz</td>\n",
       "      <td>1971.0</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>Manchester, England</td>\n",
       "      <td>2056-10-20</td>\n",
       "      <td>White</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2009</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>Slumdog Millionaire</td>\n",
       "      <td>Danny Boyle</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>Chicago, Il</td>\n",
       "      <td>2022-07-26</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1977</td>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>All the President's Men</td>\n",
       "      <td>Jason Robards</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>Laurel, Ne</td>\n",
       "      <td>2028-08-31</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1999</td>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Affliction</td>\n",
       "      <td>James Coburn</td>\n",
       "      <td>1928.0</td>\n",
       "      <td>71.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>Nevada, Mo</td>\n",
       "      <td>2006-08-05</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1949</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>The Treasure of the Sierra Madre</td>\n",
       "      <td>John Huston</td>\n",
       "      <td>1906.0</td>\n",
       "      <td>43.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>441 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              birthplace date_of_birth race_ethnicity        religion  \\\n",
       "0      Chisinau, Moldova    1895-09-30          White              Na   \n",
       "1      Glasgow, Scotland    1886-02-02          White              Na   \n",
       "2      Chisinau, Moldova    1895-09-30          White              Na   \n",
       "3            Chicago, Il    1899-02-23          White              Na   \n",
       "4     Salt Lake City, Ut    1894-04-23          White  Roman Catholic   \n",
       "..                   ...           ...            ...             ...   \n",
       "436      London, England    1971-03-07          White          Jewish   \n",
       "437  Manchester, England    2056-10-20          White  Roman Catholic   \n",
       "438          Chicago, Il    2022-07-26          White              Na   \n",
       "439           Laurel, Ne    2028-08-31          White              Na   \n",
       "440           Nevada, Mo    2006-08-05          White              Na   \n",
       "\n",
       "    sexual_orientation  year_of_award                    award  \\\n",
       "0             Straight           1927            Best Director   \n",
       "1             Straight           1930            Best Director   \n",
       "2             Straight           1931            Best Director   \n",
       "3             Straight           1932            Best Director   \n",
       "4             Straight           1933            Best Director   \n",
       "..                 ...            ...                      ...   \n",
       "436           Straight           2006  Best Supporting Actress   \n",
       "437           Straight           2009            Best Director   \n",
       "438           Straight           1977    Best Supporting Actor   \n",
       "439           Straight           1999    Best Supporting Actor   \n",
       "440           Straight           1949            Best Director   \n",
       "\n",
       "                                movie           person  year_of_birth  \\\n",
       "0                 Two Arabian Knights  Lewis Milestone         1895.0   \n",
       "1                     The Divine Lady      Frank Lloyd         1886.0   \n",
       "2      All Quiet on the Western Front  Lewis Milestone         1895.0   \n",
       "3                              Skippy    Norman Taurog         1899.0   \n",
       "4                            Bad Girl    Frank Borzage         1894.0   \n",
       "..                                ...              ...            ...   \n",
       "436             The Constant Gardener     Rachel Weisz         1971.0   \n",
       "437               Slumdog Millionaire      Danny Boyle         1956.0   \n",
       "438           All the President's Men    Jason Robards         1922.0   \n",
       "439                        Affliction     James Coburn         1928.0   \n",
       "440  The Treasure of the Sierra Madre      John Huston         1906.0   \n",
       "\n",
       "     age_at_award  \n",
       "0            32.0  \n",
       "1            44.0  \n",
       "2            36.0  \n",
       "3            33.0  \n",
       "4            39.0  \n",
       "..            ...  \n",
       "436          35.0  \n",
       "437          53.0  \n",
       "438          55.0  \n",
       "439          71.0  \n",
       "440          43.0  \n",
       "\n",
       "[441 rows x 11 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped = oscars.groupby(['movie'])\n",
    "grouped.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "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>birthplace</th>\n",
       "      <th>date_of_birth</th>\n",
       "      <th>race_ethnicity</th>\n",
       "      <th>religion</th>\n",
       "      <th>sexual_orientation</th>\n",
       "      <th>year_of_award</th>\n",
       "      <th>award</th>\n",
       "      <th>movie</th>\n",
       "      <th>person</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>age_at_award</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Chicago, Il</td>\n",
       "      <td>2027-06-23</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1973</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>Cabaret</td>\n",
       "      <td>Bob Fosse</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>Cleveland, Oh</td>\n",
       "      <td>2032-04-11</td>\n",
       "      <td>White</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>Gay</td>\n",
       "      <td>1973</td>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Cabaret</td>\n",
       "      <td>Joel Grey</td>\n",
       "      <td>1932.0</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>296</th>\n",
       "      <td>Los Angeles, Ca</td>\n",
       "      <td>2046-03-12</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Na</td>\n",
       "      <td>1973</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Cabaret</td>\n",
       "      <td>Liza Minnelli</td>\n",
       "      <td>1946.0</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          birthplace date_of_birth race_ethnicity religion sexual_orientation  \\\n",
       "46       Chicago, Il    2027-06-23          White       Na           Straight   \n",
       "209    Cleveland, Oh    2032-04-11          White   Jewish                Gay   \n",
       "296  Los Angeles, Ca    2046-03-12          White       Na                 Na   \n",
       "\n",
       "     year_of_award                  award    movie         person  \\\n",
       "46            1973          Best Director  Cabaret      Bob Fosse   \n",
       "209           1973  Best Supporting Actor  Cabaret      Joel Grey   \n",
       "296           1973           Best Actress  Cabaret  Liza Minnelli   \n",
       "\n",
       "     year_of_birth  age_at_award  \n",
       "46          1927.0          46.0  \n",
       "209         1932.0          41.0  \n",
       "296         1946.0          27.0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped.get_group('Cabaret')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Si agrupamos por múltiples columnas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "person         award                  \n",
       "Adrien Brody   Best Actor                 1\n",
       "Al Pacino      Best Actor                 1\n",
       "Alan Arkin     Best Supporting Actor      1\n",
       "Alec Guinness  Best Actor                 1\n",
       "Alice Brady    Best Supporting Actress    1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped = oscars.groupby(['person', 'award']).size()\n",
    "grouped.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "person               award                  \n",
       "Katharine Hepburn    Best Actress               4\n",
       "John Ford            Best Director              4\n",
       "Hilary Swank         Best Actress               4\n",
       "Tom Hanks            Best Actor                 3\n",
       "Elizabeth Taylor     Best Actress               3\n",
       "                                               ..\n",
       "Lupita Nyong'o       Best Supporting Actress    1\n",
       "Maggie Smith         Best Supporting Actress    1\n",
       "Margaret Rutherford  Best Supporting Actress    1\n",
       "Marie Dressler       Best Actress               1\n",
       "Adrien Brody         Best Actor                 1\n",
       "Length: 360, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped = oscars.groupby(['person', 'award']).size().sort_values(ascending=False)\n",
    "grouped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "person             award                \n",
       "Hilary Swank       Best Actress             4\n",
       "John Ford          Best Director            4\n",
       "Katharine Hepburn  Best Actress             4\n",
       "Billy Wilder       Best Director            3\n",
       "Daniel Day-Lewis   Best Actor               3\n",
       "Elizabeth Taylor   Best Actress             3\n",
       "Frank Capra        Best Director            3\n",
       "Gary Cooper        Best Actor               3\n",
       "Jason Robards      Best Supporting Actor    3\n",
       "Tom Hanks          Best Actor               3\n",
       "dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped = oscars.groupby(['person', 'award']).size().nlargest(10)\n",
    "grouped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "John Ford            4\n",
       "Katharine Hepburn    4\n",
       "Hilary Swank         4\n",
       "Jack Nicholson       3\n",
       "Maggie Smith         3\n",
       "Frank Capra          3\n",
       "William Wyler        3\n",
       "Tom Hanks            3\n",
       "Gary Cooper          3\n",
       "Jason Robards        3\n",
       "Name: person, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oscars['person'].value_counts().nlargest(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Richard Attenborough    1\n",
       "Jennifer Hudson         1\n",
       "Javier Bardem           1\n",
       "Kevin Kline             1\n",
       "Estelle Parsons         1\n",
       "Richard Dreyfuss        1\n",
       "Dean Jagger             1\n",
       "Mary Steenburgen        1\n",
       "Kevin Costner           1\n",
       "Warner Baxter           1\n",
       "Name: person, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oscars['person'].value_counts().nsmallest(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Armar un dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>award</th>\n",
       "      <th>religion</th>\n",
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       "      <td>1</td>\n",
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       "    <tr>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Best Actor</td>\n",
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       "    <tr>\n",
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       "      <th>8</th>\n",
       "      <td>Best Actor</td>\n",
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       "      <th>9</th>\n",
       "      <td>Best Actor</td>\n",
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       "      <td>3</td>\n",
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       "    <tr>\n",
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       "      <td>Best Actor</td>\n",
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       "      <td>Best Actress</td>\n",
       "      <td>Born-Again Christian</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Christian Science</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Disciples of Christ</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Hindu</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Best Actress</td>\n",
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       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Na</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Sufism</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Best Director</td>\n",
       "      <td>Atheist</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Best Director</td>\n",
       "      <td>Baptist</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Best Director</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Best Director</td>\n",
       "      <td>Na</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Best Director</td>\n",
       "      <td>Presbyterian</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Best Director</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Best Director</td>\n",
       "      <td>See Note</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Anglican/episcopalian</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Atheist</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Buddhist</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Na</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Protestant</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Agnostic</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Atheist</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Baptist</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Buddhist</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Christian</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Congregationalist</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Methodist</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Na</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Quaker</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      award               religion   0\n",
       "0                Best Actor  Anglican/episcopalian   1\n",
       "1                Best Actor                Atheist   2\n",
       "2                Best Actor                Baptist   1\n",
       "3                Best Actor   Born-Again Christian   3\n",
       "4                Best Actor                  Deist   3\n",
       "5                Best Actor                 Jewish   7\n",
       "6                Best Actor               Lutheran   3\n",
       "7                Best Actor                     Na  44\n",
       "8                Best Actor           Presbyterian   1\n",
       "9                Best Actor             Protestant   3\n",
       "10               Best Actor                 Quaker   1\n",
       "11               Best Actor         Roman Catholic  19\n",
       "12             Best Actress                Atheist   7\n",
       "13             Best Actress                Baptist   1\n",
       "14             Best Actress   Born-Again Christian   2\n",
       "15             Best Actress      Christian Science   4\n",
       "16             Best Actress    Disciples of Christ   1\n",
       "17             Best Actress                  Hindu   1\n",
       "18             Best Actress                 Jewish  10\n",
       "19             Best Actress                     Na  54\n",
       "20             Best Actress         Roman Catholic  14\n",
       "21             Best Actress                 Sufism   1\n",
       "22            Best Director                Atheist   4\n",
       "23            Best Director                Baptist   2\n",
       "24            Best Director                 Jewish  18\n",
       "25            Best Director                     Na  52\n",
       "26            Best Director           Presbyterian   1\n",
       "27            Best Director         Roman Catholic  13\n",
       "28            Best Director               See Note   1\n",
       "29    Best Supporting Actor  Anglican/episcopalian   1\n",
       "30    Best Supporting Actor                Atheist   1\n",
       "31    Best Supporting Actor               Buddhist   1\n",
       "32    Best Supporting Actor                 Jewish   8\n",
       "33    Best Supporting Actor                     Na  62\n",
       "34    Best Supporting Actor             Protestant   2\n",
       "35    Best Supporting Actor         Roman Catholic   7\n",
       "36  Best Supporting Actress               Agnostic   1\n",
       "37  Best Supporting Actress                Atheist   2\n",
       "38  Best Supporting Actress                Baptist   1\n",
       "39  Best Supporting Actress               Buddhist   4\n",
       "40  Best Supporting Actress              Christian   2\n",
       "41  Best Supporting Actress      Congregationalist   1\n",
       "42  Best Supporting Actress                 Jewish   7\n",
       "43  Best Supporting Actress              Methodist   1\n",
       "44  Best Supporting Actress                     Na  57\n",
       "45  Best Supporting Actress                 Quaker   1\n",
       "46  Best Supporting Actress         Roman Catholic   8"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oscars_by_religion = oscars.groupby(['award', 'religion']).size()\n",
    "oscars_by_religion = oscars_by_religion.reset_index()\n",
    "oscars_by_religion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\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>award</th>\n",
       "      <th>religion</th>\n",
       "      <th>count_religion</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Anglican/episcopalian</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Atheist</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Baptist</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Born-Again Christian</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Deist</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Lutheran</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Na</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Presbyterian</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Protestant</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Quaker</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Atheist</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Baptist</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Born-Again Christian</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Christian Science</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Disciples of Christ</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Hindu</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Na</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Sufism</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Best Director</td>\n",
       "      <td>Atheist</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Best Director</td>\n",
       "      <td>Baptist</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Best Director</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Best Director</td>\n",
       "      <td>Na</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Best Director</td>\n",
       "      <td>Presbyterian</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Best Director</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Best Director</td>\n",
       "      <td>See Note</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Anglican/episcopalian</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Atheist</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Buddhist</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Na</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Protestant</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Agnostic</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Atheist</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Baptist</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Buddhist</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Christian</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Congregationalist</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Methodist</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Na</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Quaker</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      award               religion  count_religion\n",
       "0                Best Actor  Anglican/episcopalian               1\n",
       "1                Best Actor                Atheist               2\n",
       "2                Best Actor                Baptist               1\n",
       "3                Best Actor   Born-Again Christian               3\n",
       "4                Best Actor                  Deist               3\n",
       "5                Best Actor                 Jewish               7\n",
       "6                Best Actor               Lutheran               3\n",
       "7                Best Actor                     Na              44\n",
       "8                Best Actor           Presbyterian               1\n",
       "9                Best Actor             Protestant               3\n",
       "10               Best Actor                 Quaker               1\n",
       "11               Best Actor         Roman Catholic              19\n",
       "12             Best Actress                Atheist               7\n",
       "13             Best Actress                Baptist               1\n",
       "14             Best Actress   Born-Again Christian               2\n",
       "15             Best Actress      Christian Science               4\n",
       "16             Best Actress    Disciples of Christ               1\n",
       "17             Best Actress                  Hindu               1\n",
       "18             Best Actress                 Jewish              10\n",
       "19             Best Actress                     Na              54\n",
       "20             Best Actress         Roman Catholic              14\n",
       "21             Best Actress                 Sufism               1\n",
       "22            Best Director                Atheist               4\n",
       "23            Best Director                Baptist               2\n",
       "24            Best Director                 Jewish              18\n",
       "25            Best Director                     Na              52\n",
       "26            Best Director           Presbyterian               1\n",
       "27            Best Director         Roman Catholic              13\n",
       "28            Best Director               See Note               1\n",
       "29    Best Supporting Actor  Anglican/episcopalian               1\n",
       "30    Best Supporting Actor                Atheist               1\n",
       "31    Best Supporting Actor               Buddhist               1\n",
       "32    Best Supporting Actor                 Jewish               8\n",
       "33    Best Supporting Actor                     Na              62\n",
       "34    Best Supporting Actor             Protestant               2\n",
       "35    Best Supporting Actor         Roman Catholic               7\n",
       "36  Best Supporting Actress               Agnostic               1\n",
       "37  Best Supporting Actress                Atheist               2\n",
       "38  Best Supporting Actress                Baptist               1\n",
       "39  Best Supporting Actress               Buddhist               4\n",
       "40  Best Supporting Actress              Christian               2\n",
       "41  Best Supporting Actress      Congregationalist               1\n",
       "42  Best Supporting Actress                 Jewish               7\n",
       "43  Best Supporting Actress              Methodist               1\n",
       "44  Best Supporting Actress                     Na              57\n",
       "45  Best Supporting Actress                 Quaker               1\n",
       "46  Best Supporting Actress         Roman Catholic               8"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col_rename = {0: 'count_religion'}\n",
    "oscars_by_religion = oscars_by_religion.rename(columns=col_rename)\n",
    "oscars_by_religion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Aplicar varias operaciones con `agg()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
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       "      <th colspan=\"2\" halign=\"left\">age_at_award</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year_of_award</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1927</th>\n",
       "      <td>32.000000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1929</th>\n",
       "      <td>34.000000</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1930</th>\n",
       "      <td>42.600000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1931</th>\n",
       "      <td>50.666667</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1932</th>\n",
       "      <td>37.333333</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              age_at_award      \n",
       "                      mean count\n",
       "year_of_award                   \n",
       "1927             32.000000     1\n",
       "1929             34.000000     2\n",
       "1930             42.600000     5\n",
       "1931             50.666667     3\n",
       "1932             37.333333     3"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped = oscars.groupby(['year_of_award']).agg({'age_at_award':['mean', 'count']})\n",
    "grouped.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Aplicar multiples operaciones a columnas diferentes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe thead tr:last-of-type th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">age_at_award</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th colspan=\"2\" halign=\"left\">religion</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>count</th>\n",
       "      <th>min</th>\n",
       "      <th>max</th>\n",
       "      <th>min</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year_of_award</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1927</th>\n",
       "      <td>32.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>Na</td>\n",
       "      <td>Na</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1929</th>\n",
       "      <td>34.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>1884.0</td>\n",
       "      <td>Na</td>\n",
       "      <td>Na</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1930</th>\n",
       "      <td>42.600000</td>\n",
       "      <td>5</td>\n",
       "      <td>1868.0</td>\n",
       "      <td>Na</td>\n",
       "      <td>Na</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1931</th>\n",
       "      <td>50.666667</td>\n",
       "      <td>3</td>\n",
       "      <td>1868.0</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>Na</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1932</th>\n",
       "      <td>37.333333</td>\n",
       "      <td>3</td>\n",
       "      <td>1885.0</td>\n",
       "      <td>Na</td>\n",
       "      <td>Na</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              age_at_award       year_of_birth        religion    \n",
       "                      mean count           min             max min\n",
       "year_of_award                                                     \n",
       "1927             32.000000     1        1895.0              Na  Na\n",
       "1929             34.000000     2        1884.0              Na  Na\n",
       "1930             42.600000     5        1868.0              Na  Na\n",
       "1931             50.666667     3        1868.0  Roman Catholic  Na\n",
       "1932             37.333333     3        1885.0              Na  Na"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped = oscars.groupby(['year_of_award']).agg({'age_at_award':['mean', 'count'], 'year_of_birth':'min', 'religion':['max', 'min']})\n",
    "grouped.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['age_at_award', 'age_at_award', 'year_of_birth', 'religion',\n",
       "       'religion'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "level_0 = grouped.columns.get_level_values(0)\n",
    "level_0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['mean', 'count', 'min', 'max', 'min'], dtype='object')"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "level_1 = grouped.columns.get_level_values(1)\n",
    "level_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\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>age_at_award_mean</th>\n",
       "      <th>age_at_award_count</th>\n",
       "      <th>year_of_birth_min</th>\n",
       "      <th>religion_max</th>\n",
       "      <th>religion_min</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year_of_award</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>49.4</td>\n",
       "      <td>5</td>\n",
       "      <td>1949.0</td>\n",
       "      <td>Na</td>\n",
       "      <td>Lutheran</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>41.6</td>\n",
       "      <td>5</td>\n",
       "      <td>1960.0</td>\n",
       "      <td>Na</td>\n",
       "      <td>Jewish</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>54.2</td>\n",
       "      <td>5</td>\n",
       "      <td>1929.0</td>\n",
       "      <td>Na</td>\n",
       "      <td>Jewish</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>45.2</td>\n",
       "      <td>5</td>\n",
       "      <td>1954.0</td>\n",
       "      <td>Na</td>\n",
       "      <td>Christian</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>41.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1969.0</td>\n",
       "      <td>Na</td>\n",
       "      <td>Na</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               age_at_award_mean  age_at_award_count  year_of_birth_min  \\\n",
       "year_of_award                                                             \n",
       "2010                        49.4                   5             1949.0   \n",
       "2011                        41.6                   5             1960.0   \n",
       "2012                        54.2                   5             1929.0   \n",
       "2013                        45.2                   5             1954.0   \n",
       "2014                        41.0                   4             1969.0   \n",
       "\n",
       "              religion_max religion_min  \n",
       "year_of_award                            \n",
       "2010                    Na     Lutheran  \n",
       "2011                    Na       Jewish  \n",
       "2012                    Na       Jewish  \n",
       "2013                    Na    Christian  \n",
       "2014                    Na           Na  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Sumamos las columnas\n",
    "grouped.columns = level_0 + '_' + level_1\n",
    "grouped.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year_of_award</th>\n",
       "      <th>age_at_award_mean</th>\n",
       "      <th>age_at_award_count</th>\n",
       "      <th>year_of_birth_min</th>\n",
       "      <th>religion_max</th>\n",
       "      <th>religion_min</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>2010</td>\n",
       "      <td>49.4</td>\n",
       "      <td>5</td>\n",
       "      <td>1949.0</td>\n",
       "      <td>Na</td>\n",
       "      <td>Lutheran</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>2011</td>\n",
       "      <td>41.6</td>\n",
       "      <td>5</td>\n",
       "      <td>1960.0</td>\n",
       "      <td>Na</td>\n",
       "      <td>Jewish</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>2012</td>\n",
       "      <td>54.2</td>\n",
       "      <td>5</td>\n",
       "      <td>1929.0</td>\n",
       "      <td>Na</td>\n",
       "      <td>Jewish</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>2013</td>\n",
       "      <td>45.2</td>\n",
       "      <td>5</td>\n",
       "      <td>1954.0</td>\n",
       "      <td>Na</td>\n",
       "      <td>Christian</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>2014</td>\n",
       "      <td>41.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1969.0</td>\n",
       "      <td>Na</td>\n",
       "      <td>Na</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    year_of_award  age_at_award_mean  age_at_award_count  year_of_birth_min  \\\n",
       "82           2010               49.4                   5             1949.0   \n",
       "83           2011               41.6                   5             1960.0   \n",
       "84           2012               54.2                   5             1929.0   \n",
       "85           2013               45.2                   5             1954.0   \n",
       "86           2014               41.0                   4             1969.0   \n",
       "\n",
       "   religion_max religion_min  \n",
       "82           Na     Lutheran  \n",
       "83           Na       Jewish  \n",
       "84           Na       Jewish  \n",
       "85           Na    Christian  \n",
       "86           Na           Na  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped.reset_index(inplace=True)\n",
    "grouped.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Es posible definir funciones propias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">age_at_award</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>add_one</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>award</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Best Actor</th>\n",
       "      <td>45.045455</td>\n",
       "      <td>46.045455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Best Actress</th>\n",
       "      <td>36.421053</td>\n",
       "      <td>37.421053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Best Director</th>\n",
       "      <td>47.300000</td>\n",
       "      <td>48.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Best Supporting Actor</th>\n",
       "      <td>50.890244</td>\n",
       "      <td>51.890244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Best Supporting Actress</th>\n",
       "      <td>40.505882</td>\n",
       "      <td>41.505882</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        age_at_award           \n",
       "                                mean    add_one\n",
       "award                                          \n",
       "Best Actor                 45.045455  46.045455\n",
       "Best Actress               36.421053  37.421053\n",
       "Best Director              47.300000  48.300000\n",
       "Best Supporting Actor      50.890244  51.890244\n",
       "Best Supporting Actress    40.505882  41.505882"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def add_one(x):\n",
    "    return x.mean() + 1\n",
    "\n",
    "grouped = oscars.groupby('award').agg({'age_at_award': ['mean', add_one]})\n",
    "grouped.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Podemos definir el nombre que lleva la columna de nuestra función"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": true
   },
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">age_at_award</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>PlusOne</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>award</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Best Actor</th>\n",
       "      <td>45.045455</td>\n",
       "      <td>46.045455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Best Actress</th>\n",
       "      <td>36.421053</td>\n",
       "      <td>37.421053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Best Director</th>\n",
       "      <td>47.300000</td>\n",
       "      <td>48.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Best Supporting Actor</th>\n",
       "      <td>50.890244</td>\n",
       "      <td>51.890244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Best Supporting Actress</th>\n",
       "      <td>40.505882</td>\n",
       "      <td>41.505882</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        age_at_award           \n",
       "                                mean    PlusOne\n",
       "award                                          \n",
       "Best Actor                 45.045455  46.045455\n",
       "Best Actress               36.421053  37.421053\n",
       "Best Director              47.300000  48.300000\n",
       "Best Supporting Actor      50.890244  51.890244\n",
       "Best Supporting Actress    40.505882  41.505882"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "add_one.__name__ = 'PlusOne'\n",
    "grouped = oscars.groupby('award').agg({'age_at_award': ['mean', add_one]})\n",
    "grouped.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Información sobre el output de `groupby()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.groupby.generic.DataFrameGroupBy'>\n"
     ]
    }
   ],
   "source": [
    "grouped = oscars.groupby('award')\n",
    "print(type(grouped))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped.ngroups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>birthplace</th>\n",
       "      <th>date_of_birth</th>\n",
       "      <th>race_ethnicity</th>\n",
       "      <th>religion</th>\n",
       "      <th>sexual_orientation</th>\n",
       "      <th>year_of_award</th>\n",
       "      <th>award</th>\n",
       "      <th>movie</th>\n",
       "      <th>person</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>age_at_award</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>Rorschach, Switzerland</td>\n",
       "      <td>1884-07-23</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Bisexual</td>\n",
       "      <td>1929</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>The Last Command</td>\n",
       "      <td>Emil Jannings</td>\n",
       "      <td>1884.0</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>Columbus, Oh</td>\n",
       "      <td>1889-03-29</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1930</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>In Old Arizona</td>\n",
       "      <td>Warner Baxter</td>\n",
       "      <td>1889.0</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>London, England</td>\n",
       "      <td>1868-04-10</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1930</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Desraeli</td>\n",
       "      <td>George Arliss</td>\n",
       "      <td>1868.0</td>\n",
       "      <td>62.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>Philadelphia, Pa</td>\n",
       "      <td>1878-04-28</td>\n",
       "      <td>White</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1931</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>A Free Soul</td>\n",
       "      <td>Lionel Barrymore</td>\n",
       "      <td>1878.0</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>Kansas City, Mo</td>\n",
       "      <td>1885-04-01</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1932</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>The Champ</td>\n",
       "      <td>Wallace Beery</td>\n",
       "      <td>1885.0</td>\n",
       "      <td>47.0</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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>Rueil-Malmaison, Hauts-De-Seine, France</td>\n",
       "      <td>1972-06-19</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2012</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>The Artist</td>\n",
       "      <td>Jean Dujardin</td>\n",
       "      <td>1972.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>London, England</td>\n",
       "      <td>2057-04-29</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2013</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Lincoln</td>\n",
       "      <td>Daniel Day-Lewis</td>\n",
       "      <td>1957.0</td>\n",
       "      <td>56.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>Uvalde, Tx</td>\n",
       "      <td>2069-11-04</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2014</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Dallas Buyers Club</td>\n",
       "      <td>Matthew McConaughey</td>\n",
       "      <td>1969.0</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>Concord, Ca</td>\n",
       "      <td>2056-07-09</td>\n",
       "      <td>White</td>\n",
       "      <td>Born-Again Christian</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1994</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Tom Hanks</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>Helena, Mt</td>\n",
       "      <td>1901-05-07</td>\n",
       "      <td>White</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1953</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>High Noon</td>\n",
       "      <td>Gary Cooper</td>\n",
       "      <td>1901.0</td>\n",
       "      <td>52.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>88 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  birthplace date_of_birth race_ethnicity  \\\n",
       "87                    Rorschach, Switzerland    1884-07-23          White   \n",
       "88                              Columbus, Oh    1889-03-29          White   \n",
       "89                           London, England    1868-04-10          White   \n",
       "90                          Philadelphia, Pa    1878-04-28          White   \n",
       "91                           Kansas City, Mo    1885-04-01          White   \n",
       "..                                       ...           ...            ...   \n",
       "170  Rueil-Malmaison, Hauts-De-Seine, France    1972-06-19          White   \n",
       "171                          London, England    2057-04-29          White   \n",
       "172                               Uvalde, Tx    2069-11-04          White   \n",
       "418                              Concord, Ca    2056-07-09          White   \n",
       "427                               Helena, Mt    1901-05-07          White   \n",
       "\n",
       "                 religion sexual_orientation  year_of_award       award  \\\n",
       "87                     Na           Bisexual           1929  Best Actor   \n",
       "88                     Na           Straight           1930  Best Actor   \n",
       "89                     Na           Straight           1930  Best Actor   \n",
       "90         Roman Catholic           Straight           1931  Best Actor   \n",
       "91                     Na           Straight           1932  Best Actor   \n",
       "..                    ...                ...            ...         ...   \n",
       "170                    Na           Straight           2012  Best Actor   \n",
       "171                    Na           Straight           2013  Best Actor   \n",
       "172                    Na           Straight           2014  Best Actor   \n",
       "418  Born-Again Christian           Straight           1994  Best Actor   \n",
       "427        Roman Catholic           Straight           1953  Best Actor   \n",
       "\n",
       "                  movie               person  year_of_birth  age_at_award  \n",
       "87     The Last Command        Emil Jannings         1884.0          45.0  \n",
       "88       In Old Arizona        Warner Baxter         1889.0          41.0  \n",
       "89             Desraeli        George Arliss         1868.0          62.0  \n",
       "90          A Free Soul     Lionel Barrymore         1878.0          53.0  \n",
       "91            The Champ        Wallace Beery         1885.0          47.0  \n",
       "..                  ...                  ...            ...           ...  \n",
       "170          The Artist        Jean Dujardin         1972.0          40.0  \n",
       "171             Lincoln     Daniel Day-Lewis         1957.0          56.0  \n",
       "172  Dallas Buyers Club  Matthew McConaughey         1969.0          45.0  \n",
       "418        Philadelphia            Tom Hanks         1956.0          38.0  \n",
       "427           High Noon          Gary Cooper         1901.0          52.0  \n",
       "\n",
       "[88 rows x 11 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped.get_group('Best Actor')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Quiero ver los primeros elementos de cada grupo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
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      "Best Actor\n"
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       "                birthplace date_of_birth race_ethnicity religion  \\\n",
       "87  Rorschach, Switzerland    1884-07-23          White       Na   \n",
       "88            Columbus, Oh    1889-03-29          White       Na   \n",
       "89         London, England    1868-04-10          White       Na   \n",
       "\n",
       "   sexual_orientation  year_of_award       award             movie  \\\n",
       "87           Bisexual           1929  Best Actor  The Last Command   \n",
       "88           Straight           1930  Best Actor    In Old Arizona   \n",
       "89           Straight           1930  Best Actor          Desraeli   \n",
       "\n",
       "           person  year_of_birth  age_at_award  \n",
       "87  Emil Jannings         1884.0          45.0  \n",
       "88  Warner Baxter         1889.0          41.0  \n",
       "89  George Arliss         1868.0          62.0  "
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      "Best Actress\n"
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       "      <td>1892-04-08</td>\n",
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       "      <th>253</th>\n",
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       "                   birthplace date_of_birth race_ethnicity religion  \\\n",
       "251          Philadelphia, Pa    2006-10-06          White       Na   \n",
       "252  Toronto, Ontario, Canada    1892-04-08          White       Na   \n",
       "253  Montreal, Quebec, Canada    1902-08-10          White       Na   \n",
       "\n",
       "    sexual_orientation  year_of_award         award         movie  \\\n",
       "251           Straight           1929  Best Actress    7th Heaven   \n",
       "252           Straight           1930  Best Actress      Coquette   \n",
       "253           Straight           1930  Best Actress  The Divorcee   \n",
       "\n",
       "            person  year_of_birth  age_at_award  \n",
       "251   Janet Gaynor         1906.0          23.0  \n",
       "252  Mary Pickford         1892.0          38.0  \n",
       "253  Norma Shearer         1902.0          28.0  "
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      "Best Director\n"
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       "          birthplace date_of_birth race_ethnicity religion sexual_orientation  \\\n",
       "0  Chisinau, Moldova    1895-09-30          White       Na           Straight   \n",
       "1  Glasgow, Scotland    1886-02-02          White       Na           Straight   \n",
       "2  Chisinau, Moldova    1895-09-30          White       Na           Straight   \n",
       "\n",
       "   year_of_award          award                           movie  \\\n",
       "0           1927  Best Director             Two Arabian Knights   \n",
       "1           1930  Best Director                 The Divine Lady   \n",
       "2           1931  Best Director  All Quiet on the Western Front   \n",
       "\n",
       "            person  year_of_birth  age_at_award  \n",
       "0  Lewis Milestone         1895.0          32.0  \n",
       "1      Frank Lloyd         1886.0          44.0  \n",
       "2  Lewis Milestone         1895.0          36.0  "
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      "Best Supporting Actor\n"
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       "      <th>174</th>\n",
       "      <td>Vienna, Austria</td>\n",
       "      <td>1896-03-22</td>\n",
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       "      <td>Na</td>\n",
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       "      <td>Best Supporting Actor</td>\n",
       "      <td>The Life of Emile Zola</td>\n",
       "      <td>Joseph Schildkraut</td>\n",
       "      <td>1896.0</td>\n",
       "      <td>42.0</td>\n",
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       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>Swampscott, Ma</td>\n",
       "      <td>1894-07-25</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1939</td>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>Walter Brennan</td>\n",
       "      <td>1894.0</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          birthplace date_of_birth race_ethnicity religion sexual_orientation  \\\n",
       "173   Swampscott, Ma    1894-07-25          White       Na           Straight   \n",
       "174  Vienna, Austria    1896-03-22          White       Na           Straight   \n",
       "175   Swampscott, Ma    1894-07-25          White       Na           Straight   \n",
       "\n",
       "     year_of_award                  award                   movie  \\\n",
       "173           1938  Best Supporting Actor         Come and Get It   \n",
       "174           1938  Best Supporting Actor  The Life of Emile Zola   \n",
       "175           1939  Best Supporting Actor                Kentucky   \n",
       "\n",
       "                 person  year_of_birth  age_at_award  \n",
       "173      Walter Brennan         1894.0          44.0  \n",
       "174  Joseph Schildkraut         1896.0          42.0  \n",
       "175      Walter Brennan         1894.0          45.0  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best Supporting Actress\n"
     ]
    },
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <th>birthplace</th>\n",
       "      <th>date_of_birth</th>\n",
       "      <th>race_ethnicity</th>\n",
       "      <th>religion</th>\n",
       "      <th>sexual_orientation</th>\n",
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       "      <th>award</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>338</th>\n",
       "      <td>Litchfield, Mn</td>\n",
       "      <td>1899-02-15</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1937</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Anthony Adverse</td>\n",
       "      <td>Gale Sondergaard</td>\n",
       "      <td>1899.0</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>339</th>\n",
       "      <td>New York City</td>\n",
       "      <td>1892-11-02</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1938</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>In Old Chicago</td>\n",
       "      <td>Alice Brady</td>\n",
       "      <td>1892.0</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>340</th>\n",
       "      <td>Los Angeles, Ca</td>\n",
       "      <td>1891-12-07</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1939</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Jezebel</td>\n",
       "      <td>Fay Bainter</td>\n",
       "      <td>1891.0</td>\n",
       "      <td>48.0</td>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          birthplace date_of_birth race_ethnicity religion sexual_orientation  \\\n",
       "338   Litchfield, Mn    1899-02-15          White       Na           Straight   \n",
       "339    New York City    1892-11-02          White       Na           Straight   \n",
       "340  Los Angeles, Ca    1891-12-07          White       Na           Straight   \n",
       "\n",
       "     year_of_award                    award            movie  \\\n",
       "338           1937  Best Supporting Actress  Anthony Adverse   \n",
       "339           1938  Best Supporting Actress   In Old Chicago   \n",
       "340           1939  Best Supporting Actress          Jezebel   \n",
       "\n",
       "               person  year_of_birth  age_at_award  \n",
       "338  Gale Sondergaard         1899.0          38.0  \n",
       "339       Alice Brady         1892.0          46.0  \n",
       "340       Fay Bainter         1891.0          48.0  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import display\n",
    "\n",
    "for name, group in grouped:\n",
    "    print(name)\n",
    "    display(group.head(3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Estadísticas sobre algunos valores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "award\n",
       "Best Actor                 White\n",
       "Best Actress               White\n",
       "Best Director              White\n",
       "Best Supporting Actor      White\n",
       "Best Supporting Actress    White\n",
       "Name: race_ethnicity, dtype: object"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Máxima cantidad de ocurrencias de los valores de race_ethnicity en cada grupo de la categoria awards\n",
    "grouped['race_ethnicity'].max()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mostrar los 3 valores mas altos en cada categoría"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best Actor\n"
     ]
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       "      <th>140</th>\n",
       "      <td>Grand Island, Ne</td>\n",
       "      <td>2005-05-16</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1982</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>On Golden Pond</td>\n",
       "      <td>Henry Fonda</td>\n",
       "      <td>1905.0</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>Winterset, Ia</td>\n",
       "      <td>2007-05-26</td>\n",
       "      <td>White</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1970</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>True Grit</td>\n",
       "      <td>John Wayne</td>\n",
       "      <td>1907.0</td>\n",
       "      <td>63.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>London, England</td>\n",
       "      <td>1868-04-10</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1930</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>Desraeli</td>\n",
       "      <td>George Arliss</td>\n",
       "      <td>1868.0</td>\n",
       "      <td>62.0</td>\n",
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      "text/plain": [
       "           birthplace date_of_birth race_ethnicity        religion  \\\n",
       "140  Grand Island, Ne    2005-05-16          White              Na   \n",
       "128     Winterset, Ia    2007-05-26          White  Roman Catholic   \n",
       "89    London, England    1868-04-10          White              Na   \n",
       "\n",
       "    sexual_orientation  year_of_award       award           movie  \\\n",
       "140           Straight           1982  Best Actor  On Golden Pond   \n",
       "128           Straight           1970  Best Actor       True Grit   \n",
       "89            Straight           1930  Best Actor        Desraeli   \n",
       "\n",
       "            person  year_of_birth  age_at_award  \n",
       "140    Henry Fonda         1905.0          77.0  \n",
       "128     John Wayne         1907.0          63.0  \n",
       "89   George Arliss         1868.0          62.0  "
      ]
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      "Best Actress\n"
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       "      <th>313</th>\n",
       "      <td>London, England</td>\n",
       "      <td>2009-06-07</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1990</td>\n",
       "      <td>Best Actress</td>\n",
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       "      <td>1909.0</td>\n",
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       "      <th>305</th>\n",
       "      <td>Hartford, Ct</td>\n",
       "      <td>2007-05-12</td>\n",
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       "      <td>Atheist</td>\n",
       "      <td>Bisexual</td>\n",
       "      <td>1982</td>\n",
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       "      <td>1907.0</td>\n",
       "      <td>75.0</td>\n",
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       "    <tr>\n",
       "      <th>254</th>\n",
       "      <td>Cobourg, Ontario, Canada</td>\n",
       "      <td>1868-11-02</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
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       "      <td>1931</td>\n",
       "      <td>Best Actress</td>\n",
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       "                   birthplace date_of_birth race_ethnicity religion  \\\n",
       "313           London, England    2009-06-07          White       Na   \n",
       "305              Hartford, Ct    2007-05-12          White  Atheist   \n",
       "254  Cobourg, Ontario, Canada    1868-11-02          White       Na   \n",
       "\n",
       "    sexual_orientation  year_of_award         award               movie  \\\n",
       "313           Straight           1990  Best Actress  Driving Miss Daisy   \n",
       "305           Bisexual           1982  Best Actress      On Golden Pond   \n",
       "254           Straight           1931  Best Actress        Min and Bill   \n",
       "\n",
       "                person  year_of_birth  age_at_award  \n",
       "313      Jessica Tandy         1909.0          81.0  \n",
       "305  Katharine Hepburn         1907.0          75.0  \n",
       "254     Marie Dressler         1868.0          63.0  "
      ]
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      "Best Director\n"
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       "      <th>78</th>\n",
       "      <td>San Francisco, Ca</td>\n",
       "      <td>2030-05-31</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2005</td>\n",
       "      <td>Best Director</td>\n",
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       "      <td>Clint Eastwood</td>\n",
       "      <td>1930.0</td>\n",
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       "      <th>76</th>\n",
       "      <td>Paris, France</td>\n",
       "      <td>2033-08-18</td>\n",
       "      <td>White</td>\n",
       "      <td>See Note</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2003</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>The Pianist</td>\n",
       "      <td>Roman Polanski</td>\n",
       "      <td>1933.0</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>New York City</td>\n",
       "      <td>1899-07-07</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Gay</td>\n",
       "      <td>1965</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>My Fair Lady</td>\n",
       "      <td>George Cukor</td>\n",
       "      <td>1899.0</td>\n",
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      "text/plain": [
       "           birthplace date_of_birth race_ethnicity  religion  \\\n",
       "78  San Francisco, Ca    2030-05-31          White        Na   \n",
       "76      Paris, France    2033-08-18          White  See Note   \n",
       "37      New York City    1899-07-07          White        Na   \n",
       "\n",
       "   sexual_orientation  year_of_award          award                movie  \\\n",
       "78           Straight           2005  Best Director  Million Dollar Baby   \n",
       "76           Straight           2003  Best Director          The Pianist   \n",
       "37                Gay           1965  Best Director         My Fair Lady   \n",
       "\n",
       "            person  year_of_birth  age_at_award  \n",
       "78  Clint Eastwood         1930.0          75.0  \n",
       "76  Roman Polanski         1933.0          70.0  \n",
       "37    George Cukor         1899.0          66.0  "
      ]
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      "Best Supporting Actor\n"
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    },
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       "      <th>248</th>\n",
       "      <td>Toronto, Ontario, Canada</td>\n",
       "      <td>2029-12-13</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2012</td>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Beginning</td>\n",
       "      <td>Christopher Plummer</td>\n",
       "      <td>1929.0</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>Kenosha, Wi</td>\n",
       "      <td>2004-05-31</td>\n",
       "      <td>White</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1986</td>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Cocoon</td>\n",
       "      <td>Don Ameche</td>\n",
       "      <td>1904.0</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>New York City</td>\n",
       "      <td>1896-01-20</td>\n",
       "      <td>White</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1976</td>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>The Sunshine Boys</td>\n",
       "      <td>George Burns</td>\n",
       "      <td>1896.0</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   birthplace date_of_birth race_ethnicity        religion  \\\n",
       "248  Toronto, Ontario, Canada    2029-12-13          White              Na   \n",
       "222               Kenosha, Wi    2004-05-31          White  Roman Catholic   \n",
       "212             New York City    1896-01-20          White          Jewish   \n",
       "\n",
       "    sexual_orientation  year_of_award                  award  \\\n",
       "248           Straight           2012  Best Supporting Actor   \n",
       "222           Straight           1986  Best Supporting Actor   \n",
       "212           Straight           1976  Best Supporting Actor   \n",
       "\n",
       "                 movie               person  year_of_birth  age_at_award  \n",
       "248          Beginning  Christopher Plummer         1929.0          83.0  \n",
       "222             Cocoon           Don Ameche         1904.0          82.0  \n",
       "212  The Sunshine Boys         George Burns         1896.0          80.0  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best Supporting Actress\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>birthplace</th>\n",
       "      <th>date_of_birth</th>\n",
       "      <th>race_ethnicity</th>\n",
       "      <th>religion</th>\n",
       "      <th>sexual_orientation</th>\n",
       "      <th>year_of_award</th>\n",
       "      <th>award</th>\n",
       "      <th>movie</th>\n",
       "      <th>person</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>age_at_award</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>386</th>\n",
       "      <td>Croydon, Surrey, England</td>\n",
       "      <td>2007-12-22</td>\n",
       "      <td>White</td>\n",
       "      <td>Agnostic</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1985</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>A Passage to India</td>\n",
       "      <td>Peggy Ashcroft</td>\n",
       "      <td>1907.0</td>\n",
       "      <td>78.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>Quincy, Ma</td>\n",
       "      <td>1896-10-30</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1969</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Rosemary's Baby</td>\n",
       "      <td>Ruth Gordon</td>\n",
       "      <td>1896.0</td>\n",
       "      <td>73.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>London, England</td>\n",
       "      <td>1892-05-11</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1964</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>the V.I.P.s</td>\n",
       "      <td>Margaret Rutherford</td>\n",
       "      <td>1892.0</td>\n",
       "      <td>72.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   birthplace date_of_birth race_ethnicity  religion  \\\n",
       "386  Croydon, Surrey, England    2007-12-22          White  Agnostic   \n",
       "370                Quincy, Ma    1896-10-30          White        Na   \n",
       "365           London, England    1892-05-11          White        Na   \n",
       "\n",
       "    sexual_orientation  year_of_award                    award  \\\n",
       "386           Straight           1985  Best Supporting Actress   \n",
       "370           Straight           1969  Best Supporting Actress   \n",
       "365           Straight           1964  Best Supporting Actress   \n",
       "\n",
       "                  movie               person  year_of_birth  age_at_award  \n",
       "386  A Passage to India       Peggy Ashcroft         1907.0          78.0  \n",
       "370     Rosemary's Baby          Ruth Gordon         1896.0          73.0  \n",
       "365         the V.I.P.s  Margaret Rutherford         1892.0          72.0  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for award, group in grouped:\n",
    "    print(award)\n",
    "    display(group.sort_values('age_at_award', ascending=False).head(3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Transform\n",
    "\n",
    "Devuelve un elemento por cada una de las filas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\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>birthplace</th>\n",
       "      <th>date_of_birth</th>\n",
       "      <th>race_ethnicity</th>\n",
       "      <th>religion</th>\n",
       "      <th>sexual_orientation</th>\n",
       "      <th>year_of_award</th>\n",
       "      <th>award</th>\n",
       "      <th>movie</th>\n",
       "      <th>person</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>age_at_award</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Chisinau, Moldova</td>\n",
       "      <td>1895-09-30</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1927</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>Two Arabian Knights</td>\n",
       "      <td>Lewis Milestone</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Glasgow, Scotland</td>\n",
       "      <td>1886-02-02</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1930</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>The Divine Lady</td>\n",
       "      <td>Frank Lloyd</td>\n",
       "      <td>1886.0</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Chisinau, Moldova</td>\n",
       "      <td>1895-09-30</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1931</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>All Quiet on the Western Front</td>\n",
       "      <td>Lewis Milestone</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          birthplace date_of_birth race_ethnicity religion sexual_orientation  \\\n",
       "0  Chisinau, Moldova    1895-09-30          White       Na           Straight   \n",
       "1  Glasgow, Scotland    1886-02-02          White       Na           Straight   \n",
       "2  Chisinau, Moldova    1895-09-30          White       Na           Straight   \n",
       "\n",
       "   year_of_award          award                           movie  \\\n",
       "0           1927  Best Director             Two Arabian Knights   \n",
       "1           1930  Best Director                 The Divine Lady   \n",
       "2           1931  Best Director  All Quiet on the Western Front   \n",
       "\n",
       "            person  year_of_birth  age_at_award  \n",
       "0  Lewis Milestone         1895.0          32.0  \n",
       "1      Frank Lloyd         1886.0          44.0  \n",
       "2  Lewis Milestone         1895.0          36.0  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oscars.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "award\n",
       "Best Actor                 45.045455\n",
       "Best Actress               36.421053\n",
       "Best Director              47.300000\n",
       "Best Supporting Actor      50.890244\n",
       "Best Supporting Actress    40.505882\n",
       "Name: age_at_award, dtype: float64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Promedio de edades para cada una de las categorías\n",
    "grouped = oscars.groupby('award')\n",
    "grouped['age_at_award'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "436    40.505882\n",
       "437    47.300000\n",
       "438    50.890244\n",
       "439    50.890244\n",
       "440    47.300000\n",
       "Name: age_at_award, dtype: float64"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped['age_at_award'].transform('mean').tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>birthplace</th>\n",
       "      <th>date_of_birth</th>\n",
       "      <th>race_ethnicity</th>\n",
       "      <th>religion</th>\n",
       "      <th>sexual_orientation</th>\n",
       "      <th>year_of_award</th>\n",
       "      <th>award</th>\n",
       "      <th>movie</th>\n",
       "      <th>person</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>age_at_award</th>\n",
       "      <th>avg_age_at_award</th>\n",
       "      <th>is_above_avg_age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>421</th>\n",
       "      <td>Los Angeles, Ca</td>\n",
       "      <td>1975-06-04</td>\n",
       "      <td>White</td>\n",
       "      <td>Buddhist</td>\n",
       "      <td>Bisexual</td>\n",
       "      <td>2000</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Girl, Interrupted</td>\n",
       "      <td>Angelina Jolie</td>\n",
       "      <td>1975.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>40.505882</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422</th>\n",
       "      <td>New York City</td>\n",
       "      <td>2027-10-31</td>\n",
       "      <td>White</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1976</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Shampoo</td>\n",
       "      <td>Lee Grant</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>40.505882</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>423</th>\n",
       "      <td>New York City</td>\n",
       "      <td>1903-06-25</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1946</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>National Velvet</td>\n",
       "      <td>Anne Revere</td>\n",
       "      <td>1903.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>40.505882</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>Bascom, Fl</td>\n",
       "      <td>2041-01-14</td>\n",
       "      <td>White</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1977</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Network</td>\n",
       "      <td>Faye Dunaway</td>\n",
       "      <td>1941.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>36.421053</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>425</th>\n",
       "      <td>Walters, Ok</td>\n",
       "      <td>2010-12-13</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1943</td>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Johnny Eager</td>\n",
       "      <td>Van Heflin</td>\n",
       "      <td>1910.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>50.890244</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>426</th>\n",
       "      <td>Thomasville, Ga</td>\n",
       "      <td>2030-02-27</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1958</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>The Three Faces of Eve</td>\n",
       "      <td>Joanne Woodward</td>\n",
       "      <td>1930.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>36.421053</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>Helena, Mt</td>\n",
       "      <td>1901-05-07</td>\n",
       "      <td>White</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1953</td>\n",
       "      <td>Best Actor</td>\n",
       "      <td>High Noon</td>\n",
       "      <td>Gary Cooper</td>\n",
       "      <td>1901.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>45.045455</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>London, England</td>\n",
       "      <td>2032-02-27</td>\n",
       "      <td>White</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1967</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Who's Afraid of Virginia Woolf?</td>\n",
       "      <td>Elizabeth Taylor</td>\n",
       "      <td>1932.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>36.421053</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>Lincoln, Ne</td>\n",
       "      <td>1974-07-30</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2005</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Million Dollar Baby</td>\n",
       "      <td>Hilary Swank</td>\n",
       "      <td>1974.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>36.421053</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>Lincoln, Ne</td>\n",
       "      <td>1974-07-30</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2005</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Million Dollar Baby</td>\n",
       "      <td>Hilary Swank</td>\n",
       "      <td>1974.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>36.421053</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>Los Angeles, Ca</td>\n",
       "      <td>1972-09-27</td>\n",
       "      <td>White</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1999</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>Shakespeare in Love</td>\n",
       "      <td>Gwyneth Paltrow</td>\n",
       "      <td>1972.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>36.421053</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>432</th>\n",
       "      <td>Malden, Ma</td>\n",
       "      <td>2007-06-16</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Na</td>\n",
       "      <td>1969</td>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>The Subject Was Roses</td>\n",
       "      <td>Jack Albertson</td>\n",
       "      <td>1907.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>50.890244</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>Woodlawn, Md</td>\n",
       "      <td>2067-12-11</td>\n",
       "      <td>Black</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2010</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Precious</td>\n",
       "      <td>Mo'Nique</td>\n",
       "      <td>1967.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>40.505882</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>La Jolla, Ca</td>\n",
       "      <td>2059-08-14</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2001</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>Pollock</td>\n",
       "      <td>Marcia Gay Harden</td>\n",
       "      <td>1959.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>40.505882</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>435</th>\n",
       "      <td>Ilford, Essex, England</td>\n",
       "      <td>2034-12-28</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1970</td>\n",
       "      <td>Best Actress</td>\n",
       "      <td>The Prime of Miss Jean Brodie</td>\n",
       "      <td>Maggie Smith</td>\n",
       "      <td>1934.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>36.421053</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>London, England</td>\n",
       "      <td>1971-03-07</td>\n",
       "      <td>White</td>\n",
       "      <td>Jewish</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2006</td>\n",
       "      <td>Best Supporting Actress</td>\n",
       "      <td>The Constant Gardener</td>\n",
       "      <td>Rachel Weisz</td>\n",
       "      <td>1971.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>40.505882</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>Manchester, England</td>\n",
       "      <td>2056-10-20</td>\n",
       "      <td>White</td>\n",
       "      <td>Roman Catholic</td>\n",
       "      <td>Straight</td>\n",
       "      <td>2009</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>Slumdog Millionaire</td>\n",
       "      <td>Danny Boyle</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>47.300000</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>Chicago, Il</td>\n",
       "      <td>2022-07-26</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1977</td>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>All the President's Men</td>\n",
       "      <td>Jason Robards</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>50.890244</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>Laurel, Ne</td>\n",
       "      <td>2028-08-31</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1999</td>\n",
       "      <td>Best Supporting Actor</td>\n",
       "      <td>Affliction</td>\n",
       "      <td>James Coburn</td>\n",
       "      <td>1928.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>50.890244</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>Nevada, Mo</td>\n",
       "      <td>2006-08-05</td>\n",
       "      <td>White</td>\n",
       "      <td>Na</td>\n",
       "      <td>Straight</td>\n",
       "      <td>1949</td>\n",
       "      <td>Best Director</td>\n",
       "      <td>The Treasure of the Sierra Madre</td>\n",
       "      <td>John Huston</td>\n",
       "      <td>1906.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>47.300000</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 birthplace date_of_birth race_ethnicity        religion  \\\n",
       "421         Los Angeles, Ca    1975-06-04          White        Buddhist   \n",
       "422           New York City    2027-10-31          White          Jewish   \n",
       "423           New York City    1903-06-25          White              Na   \n",
       "424              Bascom, Fl    2041-01-14          White  Roman Catholic   \n",
       "425             Walters, Ok    2010-12-13          White              Na   \n",
       "426         Thomasville, Ga    2030-02-27          White              Na   \n",
       "427              Helena, Mt    1901-05-07          White  Roman Catholic   \n",
       "428         London, England    2032-02-27          White          Jewish   \n",
       "429             Lincoln, Ne    1974-07-30          White              Na   \n",
       "430             Lincoln, Ne    1974-07-30          White              Na   \n",
       "431         Los Angeles, Ca    1972-09-27          White          Jewish   \n",
       "432              Malden, Ma    2007-06-16          White              Na   \n",
       "433            Woodlawn, Md    2067-12-11          Black              Na   \n",
       "434            La Jolla, Ca    2059-08-14          White              Na   \n",
       "435  Ilford, Essex, England    2034-12-28          White              Na   \n",
       "436         London, England    1971-03-07          White          Jewish   \n",
       "437     Manchester, England    2056-10-20          White  Roman Catholic   \n",
       "438             Chicago, Il    2022-07-26          White              Na   \n",
       "439              Laurel, Ne    2028-08-31          White              Na   \n",
       "440              Nevada, Mo    2006-08-05          White              Na   \n",
       "\n",
       "    sexual_orientation  year_of_award                    award  \\\n",
       "421           Bisexual           2000  Best Supporting Actress   \n",
       "422           Straight           1976  Best Supporting Actress   \n",
       "423           Straight           1946  Best Supporting Actress   \n",
       "424           Straight           1977             Best Actress   \n",
       "425           Straight           1943    Best Supporting Actor   \n",
       "426           Straight           1958             Best Actress   \n",
       "427           Straight           1953               Best Actor   \n",
       "428           Straight           1967             Best Actress   \n",
       "429           Straight           2005             Best Actress   \n",
       "430           Straight           2005             Best Actress   \n",
       "431           Straight           1999             Best Actress   \n",
       "432                 Na           1969    Best Supporting Actor   \n",
       "433           Straight           2010  Best Supporting Actress   \n",
       "434           Straight           2001  Best Supporting Actress   \n",
       "435           Straight           1970             Best Actress   \n",
       "436           Straight           2006  Best Supporting Actress   \n",
       "437           Straight           2009            Best Director   \n",
       "438           Straight           1977    Best Supporting Actor   \n",
       "439           Straight           1999    Best Supporting Actor   \n",
       "440           Straight           1949            Best Director   \n",
       "\n",
       "                                movie             person  year_of_birth  \\\n",
       "421                 Girl, Interrupted     Angelina Jolie         1975.0   \n",
       "422                           Shampoo          Lee Grant         1927.0   \n",
       "423                   National Velvet        Anne Revere         1903.0   \n",
       "424                           Network       Faye Dunaway         1941.0   \n",
       "425                      Johnny Eager         Van Heflin         1910.0   \n",
       "426            The Three Faces of Eve    Joanne Woodward         1930.0   \n",
       "427                         High Noon        Gary Cooper         1901.0   \n",
       "428   Who's Afraid of Virginia Woolf?   Elizabeth Taylor         1932.0   \n",
       "429               Million Dollar Baby       Hilary Swank         1974.0   \n",
       "430               Million Dollar Baby       Hilary Swank         1974.0   \n",
       "431               Shakespeare in Love    Gwyneth Paltrow         1972.0   \n",
       "432             The Subject Was Roses     Jack Albertson         1907.0   \n",
       "433                          Precious           Mo'Nique         1967.0   \n",
       "434                           Pollock  Marcia Gay Harden         1959.0   \n",
       "435     The Prime of Miss Jean Brodie       Maggie Smith         1934.0   \n",
       "436             The Constant Gardener       Rachel Weisz         1971.0   \n",
       "437               Slumdog Millionaire        Danny Boyle         1956.0   \n",
       "438           All the President's Men      Jason Robards         1922.0   \n",
       "439                        Affliction       James Coburn         1928.0   \n",
       "440  The Treasure of the Sierra Madre        John Huston         1906.0   \n",
       "\n",
       "     age_at_award  avg_age_at_award  is_above_avg_age  \n",
       "421          25.0         40.505882             False  \n",
       "422          49.0         40.505882              True  \n",
       "423          43.0         40.505882              True  \n",
       "424          36.0         36.421053             False  \n",
       "425          33.0         50.890244             False  \n",
       "426          28.0         36.421053             False  \n",
       "427          52.0         45.045455              True  \n",
       "428          35.0         36.421053             False  \n",
       "429          31.0         36.421053             False  \n",
       "430          31.0         36.421053             False  \n",
       "431          27.0         36.421053             False  \n",
       "432          62.0         50.890244              True  \n",
       "433          43.0         40.505882              True  \n",
       "434          42.0         40.505882              True  \n",
       "435          36.0         36.421053             False  \n",
       "436          35.0         40.505882             False  \n",
       "437          53.0         47.300000              True  \n",
       "438          55.0         50.890244              True  \n",
       "439          71.0         50.890244              True  \n",
       "440          43.0         47.300000             False  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oscars['avg_age_at_award'] = oscars.groupby('award')['age_at_award'].transform('mean')\n",
    "oscars['is_above_avg_age'] = oscars['avg_age_at_award'] < oscars['age_at_award']\n",
    "oscars.tail(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Funciones lambda"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      1896.0\n",
       "1      1887.0\n",
       "2      1896.0\n",
       "3      1900.0\n",
       "4      1895.0\n",
       "        ...  \n",
       "436    1972.0\n",
       "437    1957.0\n",
       "438    1923.0\n",
       "439    1929.0\n",
       "440    1907.0\n",
       "Name: year_of_birth, Length: 441, dtype: float64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oscars['year_of_birth'].transform(func = lambda x : x + 1)"
   ]
  }
 ],
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