Class Project #3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "fn = \"../input/forbes_celebrity_list.csv\"\n",
    "df = pd.read_csv(fn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "?pd.read_csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>rank</th>\n",
       "      <th>recipient</th>\n",
       "      <th>country</th>\n",
       "      <th>career</th>\n",
       "      <th>tied</th>\n",
       "      <th>title</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1999</td>\n",
       "      <td>1</td>\n",
       "      <td>Michael Jordan</td>\n",
       "      <td>United States</td>\n",
       "      <td>Sportsperson (Basketball)</td>\n",
       "      <td>0</td>\n",
       "      <td>Michael_Jordan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1999</td>\n",
       "      <td>2</td>\n",
       "      <td>Oprah Winfrey</td>\n",
       "      <td>United States</td>\n",
       "      <td>Television Personality</td>\n",
       "      <td>0</td>\n",
       "      <td>Oprah_Winfrey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1999</td>\n",
       "      <td>3</td>\n",
       "      <td>Leonardo DiCaprio</td>\n",
       "      <td>United States</td>\n",
       "      <td>Actor</td>\n",
       "      <td>0</td>\n",
       "      <td>Leonardo_DiCaprio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1999</td>\n",
       "      <td>4</td>\n",
       "      <td>Jerry Seinfeld</td>\n",
       "      <td>United States</td>\n",
       "      <td>Actor</td>\n",
       "      <td>0</td>\n",
       "      <td>Jerry_Seinfeld</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1999</td>\n",
       "      <td>5</td>\n",
       "      <td>Steven Spielberg</td>\n",
       "      <td>United States</td>\n",
       "      <td>Filmmaker</td>\n",
       "      <td>0</td>\n",
       "      <td>Steven_Spielberg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>197</td>\n",
       "      <td>2018</td>\n",
       "      <td>6</td>\n",
       "      <td>U2</td>\n",
       "      <td>Republic of Ireland</td>\n",
       "      <td>Musicians</td>\n",
       "      <td>0</td>\n",
       "      <td>U2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>198</td>\n",
       "      <td>2018</td>\n",
       "      <td>7</td>\n",
       "      <td>Coldplay</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Musicians</td>\n",
       "      <td>0</td>\n",
       "      <td>Coldplay</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>199</td>\n",
       "      <td>2018</td>\n",
       "      <td>8</td>\n",
       "      <td>Lionel Messi</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>Athlete (Association football)</td>\n",
       "      <td>0</td>\n",
       "      <td>Lionel_Messi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>200</td>\n",
       "      <td>2018</td>\n",
       "      <td>9</td>\n",
       "      <td>Ed Sheeran</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Musician</td>\n",
       "      <td>0</td>\n",
       "      <td>Ed_Sheeran</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>201</td>\n",
       "      <td>2018</td>\n",
       "      <td>10</td>\n",
       "      <td>Cristiano Ronaldo</td>\n",
       "      <td>Portugal</td>\n",
       "      <td>Athlete (Association football)</td>\n",
       "      <td>0</td>\n",
       "      <td>Cristiano_Ronaldo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>202 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     year  rank          recipient              country  \\\n",
       "0    1999     1     Michael Jordan        United States   \n",
       "1    1999     2      Oprah Winfrey        United States   \n",
       "2    1999     3  Leonardo DiCaprio        United States   \n",
       "3    1999     4     Jerry Seinfeld        United States   \n",
       "4    1999     5   Steven Spielberg        United States   \n",
       "..    ...   ...                ...                  ...   \n",
       "197  2018     6                 U2  Republic of Ireland   \n",
       "198  2018     7           Coldplay       United Kingdom   \n",
       "199  2018     8       Lionel Messi            Argentina   \n",
       "200  2018     9         Ed Sheeran       United Kingdom   \n",
       "201  2018    10  Cristiano Ronaldo             Portugal   \n",
       "\n",
       "                             career  tied              title  \n",
       "0         Sportsperson (Basketball)     0     Michael_Jordan  \n",
       "1            Television Personality     0      Oprah_Winfrey  \n",
       "2                             Actor     0  Leonardo_DiCaprio  \n",
       "3                             Actor     0     Jerry_Seinfeld  \n",
       "4                         Filmmaker     0   Steven_Spielberg  \n",
       "..                              ...   ...                ...  \n",
       "197                       Musicians     0                 U2  \n",
       "198                       Musicians     0           Coldplay  \n",
       "199  Athlete (Association football)     0       Lionel_Messi  \n",
       "200                        Musician     0         Ed_Sheeran  \n",
       "201  Athlete (Association football)     0  Cristiano_Ronaldo  \n",
       "\n",
       "[202 rows x 7 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Oprah_Winfrey       16\n",
       "Tiger_Woods         12\n",
       "Steven_Spielberg    11\n",
       "Tom_Cruise           6\n",
       "Beyoncé              6\n",
       "Name: title, dtype: int64"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"title\"].value_counts().head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Spice_Girls       1\n",
       "Ed_Sheeran        1\n",
       "Kylie_Jenner      1\n",
       "Rush_Limbaugh     1\n",
       "Kim_Kardashian    1\n",
       "Name: title, dtype: int64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"title\"].value_counts().tail(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_edits = df.groupby(\"title\")[\"rank\"].agg([len])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
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       "      <td>The_Weeknd</td>\n",
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       "      <td>12</td>\n",
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      "text/plain": [
       "             len\n",
       "title           \n",
       "The_Weeknd     1\n",
       "Tiger_Woods   12\n",
       "Tom_Cruise     6\n",
       "Tom_Hanks      3\n",
       "U2             5"
      ]
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     "execution_count": 71,
     "metadata": {},
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    }
   ],
   "source": [
    "df_edits.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
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       "      <td>Robin Williams</td>\n",
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       "      <td>Ed Sheeran</td>\n",
       "      <td>United Kingdom</td>\n",
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       "      <td>U2</td>\n",
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       "    <tr>\n",
       "      <td>198</td>\n",
       "      <td>2018</td>\n",
       "      <td>7</td>\n",
       "      <td>Coldplay</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Musicians</td>\n",
       "      <td>0</td>\n",
       "      <td>Coldplay</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>194</td>\n",
       "      <td>2018</td>\n",
       "      <td>3</td>\n",
       "      <td>Kylie Jenner</td>\n",
       "      <td>United States</td>\n",
       "      <td>Personality</td>\n",
       "      <td>0</td>\n",
       "      <td>Kylie_Jenner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>195</td>\n",
       "      <td>2018</td>\n",
       "      <td>4</td>\n",
       "      <td>Judy Sheindlin</td>\n",
       "      <td>United States</td>\n",
       "      <td>Personality</td>\n",
       "      <td>0</td>\n",
       "      <td>Judy_Sheindlin</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>202 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     year  rank          recipient              country       career  tied  \\\n",
       "2    1999     3  Leonardo DiCaprio        United States        Actor     0   \n",
       "3    1999     4     Jerry Seinfeld        United States        Actor     0   \n",
       "6    1999     7      Harrison Ford        United States        Actor     0   \n",
       "7    1999     8     Robin Williams        United States        Actor     0   \n",
       "4    1999     5   Steven Spielberg        United States    Filmmaker     0   \n",
       "..    ...   ...                ...                  ...          ...   ...   \n",
       "200  2018     9         Ed Sheeran       United Kingdom     Musician     0   \n",
       "197  2018     6                 U2  Republic of Ireland    Musicians     0   \n",
       "198  2018     7           Coldplay       United Kingdom    Musicians     0   \n",
       "194  2018     3       Kylie Jenner        United States  Personality     0   \n",
       "195  2018     4     Judy Sheindlin        United States  Personality     0   \n",
       "\n",
       "                 title  \n",
       "2    Leonardo_DiCaprio  \n",
       "3       Jerry_Seinfeld  \n",
       "6        Harrison_Ford  \n",
       "7       Robin_Williams  \n",
       "4     Steven_Spielberg  \n",
       "..                 ...  \n",
       "200         Ed_Sheeran  \n",
       "197                 U2  \n",
       "198           Coldplay  \n",
       "194       Kylie_Jenner  \n",
       "195     Judy_Sheindlin  \n",
       "\n",
       "[202 rows x 7 columns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by=[\"year\", \"career\"], ascending=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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