Chapter 01 Pandas Foundations.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Chapter 1: Pandas Foundations\n",
    "\n",
    "## Recipes\n",
    "* [Dissecting the anatomy of a DataFrame](#Dissecting-the-anatomy-of-a-DataFrame)\n",
    "* [Accessing the main DataFrame components](#Accessing-the-main-DataFrame-components)\n",
    "* [Understanding data types](#Understanding-data-types)\n",
    "* [Selecting a single column of data as a Series](#Selecting-a-single-column-of-data-as-a-Series)\n",
    "* [Calling Series methods](#Calling-Series-methods)\n",
    "* [Working with operators on a Series](#Working-with-operators-on-a-Series)\n",
    "* [Chaining Series methods together](#Chaining-Series-methods-together)\n",
    "* [Making the index meaningful](#Making-the-index-meaningful)\n",
    "* [Renaming row and column names](#Renaming-row-and-column-names)\n",
    "* [Creating and deleting columns](#Creating-and-deleting-columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dissecting the anatomy of a DataFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Change options to get specific output for book"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pd.set_option('max_columns', 8, 'max_rows', 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>color</th>\n",
       "      <th>director_name</th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>duration</th>\n",
       "      <th>...</th>\n",
       "      <th>actor_2_facebook_likes</th>\n",
       "      <th>imdb_score</th>\n",
       "      <th>aspect_ratio</th>\n",
       "      <th>movie_facebook_likes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Color</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>723.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>...</td>\n",
       "      <td>936.0</td>\n",
       "      <td>7.9</td>\n",
       "      <td>1.78</td>\n",
       "      <td>33000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Color</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "      <td>302.0</td>\n",
       "      <td>169.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Color</td>\n",
       "      <td>Sam Mendes</td>\n",
       "      <td>602.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>...</td>\n",
       "      <td>393.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.35</td>\n",
       "      <td>85000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Color</td>\n",
       "      <td>Christopher Nolan</td>\n",
       "      <td>813.0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>...</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>8.5</td>\n",
       "      <td>2.35</td>\n",
       "      <td>164000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Doug Walker</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   color      director_name  num_critic_for_reviews  duration  \\\n",
       "0  Color      James Cameron                   723.0     178.0   \n",
       "1  Color     Gore Verbinski                   302.0     169.0   \n",
       "2  Color         Sam Mendes                   602.0     148.0   \n",
       "3  Color  Christopher Nolan                   813.0     164.0   \n",
       "4    NaN        Doug Walker                     NaN       NaN   \n",
       "\n",
       "           ...           actor_2_facebook_likes  imdb_score aspect_ratio  \\\n",
       "0          ...                            936.0         7.9         1.78   \n",
       "1          ...                           5000.0         7.1         2.35   \n",
       "2          ...                            393.0         6.8         2.35   \n",
       "3          ...                          23000.0         8.5         2.35   \n",
       "4          ...                             12.0         7.1          NaN   \n",
       "\n",
       "   movie_facebook_likes  \n",
       "0                 33000  \n",
       "1                     0  \n",
       "2                 85000  \n",
       "3                164000  \n",
       "4                     0  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie = pd.read_csv('data/movie.csv')\n",
    "movie.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![dataframe anatomy](./images/ch01_dataframe_anatomy.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Accessing the main DataFrame components"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "columns = movie.columns\n",
    "index = movie.index\n",
    "data = movie.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['color', 'director_name', 'num_critic_for_reviews', 'duration',\n",
       "       'director_facebook_likes', 'actor_3_facebook_likes', 'actor_2_name',\n",
       "       'actor_1_facebook_likes', 'gross', 'genres', 'actor_1_name',\n",
       "       'movie_title', 'num_voted_users', 'cast_total_facebook_likes',\n",
       "       'actor_3_name', 'facenumber_in_poster', 'plot_keywords',\n",
       "       'movie_imdb_link', 'num_user_for_reviews', 'language', 'country',\n",
       "       'content_rating', 'budget', 'title_year', 'actor_2_facebook_likes',\n",
       "       'imdb_score', 'aspect_ratio', 'movie_facebook_likes'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=4916, step=1)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([['Color', 'James Cameron', 723.0, ..., 7.9, 1.78, 33000],\n",
       "       ['Color', 'Gore Verbinski', 302.0, ..., 7.1, 2.35, 0],\n",
       "       ['Color', 'Sam Mendes', 602.0, ..., 6.8, 2.35, 85000],\n",
       "       ..., \n",
       "       ['Color', 'Benjamin Roberds', 13.0, ..., 6.3, nan, 16],\n",
       "       ['Color', 'Daniel Hsia', 14.0, ..., 6.3, 2.35, 660],\n",
       "       ['Color', 'Jon Gunn', 43.0, ..., 6.6, 1.85, 456]], dtype=object)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.indexes.range.RangeIndex"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.indexes.base.Index"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "issubclass(pd.RangeIndex, pd.Index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## There's more"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([   0,    1,    2, ..., 4913, 4914, 4915])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['color', 'director_name', 'num_critic_for_reviews', 'duration',\n",
       "       'director_facebook_likes', 'actor_3_facebook_likes', 'actor_2_name',\n",
       "       'actor_1_facebook_likes', 'gross', 'genres', 'actor_1_name',\n",
       "       'movie_title', 'num_voted_users', 'cast_total_facebook_likes',\n",
       "       'actor_3_name', 'facenumber_in_poster', 'plot_keywords',\n",
       "       'movie_imdb_link', 'num_user_for_reviews', 'language', 'country',\n",
       "       'content_rating', 'budget', 'title_year', 'actor_2_facebook_likes',\n",
       "       'imdb_score', 'aspect_ratio', 'movie_facebook_likes'], dtype=object)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "columns.values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Understanding data types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "movie = pd.read_csv('data/movie.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "color                       object\n",
       "director_name               object\n",
       "num_critic_for_reviews     float64\n",
       "duration                   float64\n",
       "director_facebook_likes    float64\n",
       "                            ...   \n",
       "title_year                 float64\n",
       "actor_2_facebook_likes     float64\n",
       "imdb_score                 float64\n",
       "aspect_ratio               float64\n",
       "movie_facebook_likes         int64\n",
       "Length: 28, dtype: object"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "float64    13\n",
       "int64       3\n",
       "object     12\n",
       "dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie.get_dtype_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Selecting a single column of data as a Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "movie = pd.read_csv('data/movie.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0           James Cameron\n",
       "1          Gore Verbinski\n",
       "2              Sam Mendes\n",
       "3       Christopher Nolan\n",
       "4             Doug Walker\n",
       "              ...        \n",
       "4911          Scott Smith\n",
       "4912                  NaN\n",
       "4913     Benjamin Roberds\n",
       "4914          Daniel Hsia\n",
       "4915             Jon Gunn\n",
       "Name: director_name, Length: 4916, dtype: object"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie['director_name']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0           James Cameron\n",
       "1          Gore Verbinski\n",
       "2              Sam Mendes\n",
       "3       Christopher Nolan\n",
       "4             Doug Walker\n",
       "              ...        \n",
       "4911          Scott Smith\n",
       "4912                  NaN\n",
       "4913     Benjamin Roberds\n",
       "4914          Daniel Hsia\n",
       "4915             Jon Gunn\n",
       "Name: director_name, Length: 4916, dtype: object"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie.director_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(movie['director_name'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## There's more"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'director_name'"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "director = movie['director_name'] # save Series to variable\n",
    "director.name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>director_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>James Cameron</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Gore Verbinski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sam Mendes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Christopher Nolan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Doug Walker</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       director_name\n",
       "0      James Cameron\n",
       "1     Gore Verbinski\n",
       "2         Sam Mendes\n",
       "3  Christopher Nolan\n",
       "4        Doug Walker"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "director.to_frame().head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calling Series methods"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Getting ready..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "442"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s_attr_methods = set(dir(pd.Series))\n",
    "len(s_attr_methods)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "445"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_attr_methods = set(dir(pd.DataFrame))\n",
    "len(df_attr_methods)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "376"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(s_attr_methods & df_attr_methods)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How to do it..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "movie = pd.read_csv('data/movie.csv')\n",
    "director = movie['director_name']\n",
    "actor_1_fb_likes = movie['actor_1_facebook_likes']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        James Cameron\n",
       "1       Gore Verbinski\n",
       "2           Sam Mendes\n",
       "3    Christopher Nolan\n",
       "4          Doug Walker\n",
       "Name: director_name, dtype: object"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "director.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     1000.0\n",
       "1    40000.0\n",
       "2    11000.0\n",
       "3    27000.0\n",
       "4      131.0\n",
       "Name: actor_1_facebook_likes, dtype: float64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actor_1_fb_likes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Steven Spielberg    26\n",
       "Woody Allen         22\n",
       "Clint Eastwood      20\n",
       "Martin Scorsese     20\n",
       "                    ..\n",
       "James Nunn           1\n",
       "Gerard Johnstone     1\n",
       "Ethan Maniquis       1\n",
       "Antony Hoffman       1\n",
       "Name: director_name, Length: 2397, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('max_rows', 8)\n",
    "director.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000.0     436\n",
       "11000.0    206\n",
       "2000.0     189\n",
       "3000.0     150\n",
       "          ... \n",
       "216.0        1\n",
       "859.0        1\n",
       "225.0        1\n",
       "334.0        1\n",
       "Name: actor_1_facebook_likes, Length: 877, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actor_1_fb_likes.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4916"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "director.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4916,)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "director.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4916"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(director)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4814"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "director.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4909"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actor_1_fb_likes.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "982.0"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actor_1_fb_likes.quantile()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 640000.0, 6494.488490527602, 982.0, 15106.986883848309, 31881444.0)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actor_1_fb_likes.min(), actor_1_fb_likes.max(), \\\n",
    "actor_1_fb_likes.mean(), actor_1_fb_likes.median(), \\\n",
    "actor_1_fb_likes.std(), actor_1_fb_likes.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count      4909.000000\n",
       "mean       6494.488491\n",
       "std       15106.986884\n",
       "min           0.000000\n",
       "25%         607.000000\n",
       "50%         982.000000\n",
       "75%       11000.000000\n",
       "max      640000.000000\n",
       "Name: actor_1_facebook_likes, dtype: float64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actor_1_fb_likes.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count                 4814\n",
       "unique                2397\n",
       "top       Steven Spielberg\n",
       "freq                    26\n",
       "Name: director_name, dtype: object"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "director.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "510.0"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actor_1_fb_likes.quantile(.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.1      240.0\n",
       "0.2      510.0\n",
       "0.3      694.0\n",
       "0.4      854.0\n",
       "        ...   \n",
       "0.6     1000.0\n",
       "0.7     8000.0\n",
       "0.8    13000.0\n",
       "0.9    18000.0\n",
       "Name: actor_1_facebook_likes, Length: 9, dtype: float64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actor_1_fb_likes.quantile([.1, .2, .3, .4, .5, .6, .7, .8, .9])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       False\n",
       "1       False\n",
       "2       False\n",
       "3       False\n",
       "        ...  \n",
       "4912     True\n",
       "4913    False\n",
       "4914    False\n",
       "4915    False\n",
       "Name: director_name, Length: 4916, dtype: bool"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "director.isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4916"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actor_1_fb_likes_filled = actor_1_fb_likes.fillna(0)\n",
    "actor_1_fb_likes_filled.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4909"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actor_1_fb_likes_dropped = actor_1_fb_likes.dropna()\n",
    "actor_1_fb_likes_dropped.size"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## There's more..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Steven Spielberg    0.005401\n",
       "Woody Allen         0.004570\n",
       "Clint Eastwood      0.004155\n",
       "Martin Scorsese     0.004155\n",
       "                      ...   \n",
       "James Nunn          0.000208\n",
       "Gerard Johnstone    0.000208\n",
       "Ethan Maniquis      0.000208\n",
       "Antony Hoffman      0.000208\n",
       "Name: director_name, Length: 2397, dtype: float64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "director.value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "director.hasnans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        True\n",
       "1        True\n",
       "2        True\n",
       "3        True\n",
       "        ...  \n",
       "4912    False\n",
       "4913     True\n",
       "4914     True\n",
       "4915     True\n",
       "Name: director_name, Length: 4916, dtype: bool"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "director.notnull()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Working with operators on a Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pd.options.display.max_rows = 6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "5 + 9    # plus operator example. Adds 5 and 9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "4 ** 2   # exponentiation operator. Raises 4 to the second power"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "a = 10   # assignment operator."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "5 <= 9   # less than or equal to operator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'abcdefg'"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'abcde' + 'fg'    # plus operator for strings. C"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "not (5 <= 9)      # not is an operator that is a reserved keyword and reverse a boolean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "7 in [1, 2, 6]    # in operator checks for membership of a list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{2, 3}"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set([1,2,3]) & set([2,3,4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for -: 'list' and 'int'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-57-7ca967348b32>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for -: 'list' and 'int'"
     ]
    }
   ],
   "source": [
    "[1, 2, 3] - 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'set' object does not support indexing",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-58-98d710c0ee48>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0ma\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0ma\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m                 \u001b[0;31m# the indexing operator does not work with sets\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: 'set' object does not support indexing"
     ]
    }
   ],
   "source": [
    "a = set([1,2,3])     \n",
    "a[0]                 # the indexing operator does not work with sets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Getting ready..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       7.9\n",
       "1       7.1\n",
       "2       6.8\n",
       "       ... \n",
       "4913    6.3\n",
       "4914    6.3\n",
       "4915    6.6\n",
       "Name: imdb_score, Length: 4916, dtype: float64"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie = pd.read_csv('data/movie.csv')\n",
    "imdb_score = movie['imdb_score']\n",
    "imdb_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       8.9\n",
       "1       8.1\n",
       "2       7.8\n",
       "       ... \n",
       "4913    7.3\n",
       "4914    7.3\n",
       "4915    7.6\n",
       "Name: imdb_score, Length: 4916, dtype: float64"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imdb_score + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       19.75\n",
       "1       17.75\n",
       "2       17.00\n",
       "        ...  \n",
       "4913    15.75\n",
       "4914    15.75\n",
       "4915    16.50\n",
       "Name: imdb_score, Length: 4916, dtype: float64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imdb_score * 2.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       1.0\n",
       "1       1.0\n",
       "2       0.0\n",
       "       ... \n",
       "4913    0.0\n",
       "4914    0.0\n",
       "4915    0.0\n",
       "Name: imdb_score, Length: 4916, dtype: float64"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imdb_score // 7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        True\n",
       "1        True\n",
       "2       False\n",
       "        ...  \n",
       "4913    False\n",
       "4914    False\n",
       "4915    False\n",
       "Name: imdb_score, Length: 4916, dtype: bool"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imdb_score > 7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "director = movie['director_name']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        True\n",
       "1       False\n",
       "2       False\n",
       "        ...  \n",
       "4913    False\n",
       "4914    False\n",
       "4915    False\n",
       "Name: director_name, Length: 4916, dtype: bool"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "director == 'James Cameron'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## There's more..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       8.9\n",
       "1       8.1\n",
       "2       7.8\n",
       "       ... \n",
       "4913    7.3\n",
       "4914    7.3\n",
       "4915    7.6\n",
       "Name: imdb_score, Length: 4916, dtype: float64"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imdb_score.add(1)              # imdb_score + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       19.75\n",
       "1       17.75\n",
       "2       17.00\n",
       "        ...  \n",
       "4913    15.75\n",
       "4914    15.75\n",
       "4915    16.50\n",
       "Name: imdb_score, Length: 4916, dtype: float64"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imdb_score.mul(2.5)            # imdb_score * 2.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       1.0\n",
       "1       1.0\n",
       "2       0.0\n",
       "       ... \n",
       "4913    0.0\n",
       "4914    0.0\n",
       "4915    0.0\n",
       "Name: imdb_score, Length: 4916, dtype: float64"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imdb_score.floordiv(7)         # imdb_score // 7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        True\n",
       "1        True\n",
       "2       False\n",
       "        ...  \n",
       "4913    False\n",
       "4914    False\n",
       "4915    False\n",
       "Name: imdb_score, Length: 4916, dtype: bool"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imdb_score.gt(7)               # imdb_score > 7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        True\n",
       "1       False\n",
       "2       False\n",
       "        ...  \n",
       "4913    False\n",
       "4914    False\n",
       "4915    False\n",
       "Name: director_name, Length: 4916, dtype: bool"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "director.eq('James Cameron')   # director == 'James Cameron'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       2\n",
       "1       2\n",
       "2       1\n",
       "       ..\n",
       "4913    1\n",
       "4914    1\n",
       "4915    1\n",
       "Name: imdb_score, Length: 4916, dtype: int64"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imdb_score.astype(int).mod(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "a = type(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "type"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "a = type(imdb_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    2\n",
       "2    3\n",
       "dtype: int64"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a([1,2,3])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Chaining Series methods together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "movie = pd.read_csv('data/movie.csv')\n",
    "actor_1_fb_likes = movie['actor_1_facebook_likes']\n",
    "director = movie['director_name']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Steven Spielberg    26\n",
       "Woody Allen         22\n",
       "Clint Eastwood      20\n",
       "Name: director_name, dtype: int64"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "director.value_counts().head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actor_1_fb_likes.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('float64')"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actor_1_fb_likes.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     1000\n",
       "1    40000\n",
       "2    11000\n",
       "3    27000\n",
       "4      131\n",
       "Name: actor_1_facebook_likes, dtype: int64"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actor_1_fb_likes.fillna(0)\\\n",
    "                .astype(int)\\\n",
    "                .head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## There's more..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0014239218877135883"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actor_1_fb_likes.isnull().mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     1000\n",
       "1    40000\n",
       "2    11000\n",
       "3    27000\n",
       "4      131\n",
       "Name: actor_1_facebook_likes, dtype: int64"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(actor_1_fb_likes.fillna(0)\n",
    "                 .astype(int)\n",
    "                 .head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Making the index meaningful"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "movie = pd.read_csv('data/movie.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4916, 28)"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>color</th>\n",
       "      <th>director_name</th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>duration</th>\n",
       "      <th>...</th>\n",
       "      <th>actor_2_facebook_likes</th>\n",
       "      <th>imdb_score</th>\n",
       "      <th>aspect_ratio</th>\n",
       "      <th>movie_facebook_likes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>movie_title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>Avatar</th>\n",
       "      <td>Color</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>723.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>...</td>\n",
       "      <td>936.0</td>\n",
       "      <td>7.9</td>\n",
       "      <td>1.78</td>\n",
       "      <td>33000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pirates of the Caribbean: At World's End</th>\n",
       "      <td>Color</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "      <td>302.0</td>\n",
       "      <td>169.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spectre</th>\n",
       "      <td>Color</td>\n",
       "      <td>Sam Mendes</td>\n",
       "      <td>602.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>...</td>\n",
       "      <td>393.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.35</td>\n",
       "      <td>85000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A Plague So Pleasant</th>\n",
       "      <td>Color</td>\n",
       "      <td>Benjamin Roberds</td>\n",
       "      <td>13.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shanghai Calling</th>\n",
       "      <td>Color</td>\n",
       "      <td>Daniel Hsia</td>\n",
       "      <td>14.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>719.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>2.35</td>\n",
       "      <td>660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>My Date with Drew</th>\n",
       "      <td>Color</td>\n",
       "      <td>Jon Gunn</td>\n",
       "      <td>43.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>...</td>\n",
       "      <td>23.0</td>\n",
       "      <td>6.6</td>\n",
       "      <td>1.85</td>\n",
       "      <td>456</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4916 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          color     director_name  \\\n",
       "movie_title                                                         \n",
       "Avatar                                    Color     James Cameron   \n",
       "Pirates of the Caribbean: At World's End  Color    Gore Verbinski   \n",
       "Spectre                                   Color        Sam Mendes   \n",
       "...                                         ...               ...   \n",
       "A Plague So Pleasant                      Color  Benjamin Roberds   \n",
       "Shanghai Calling                          Color       Daniel Hsia   \n",
       "My Date with Drew                         Color          Jon Gunn   \n",
       "\n",
       "                                          num_critic_for_reviews  duration  \\\n",
       "movie_title                                                                  \n",
       "Avatar                                                     723.0     178.0   \n",
       "Pirates of the Caribbean: At World's End                   302.0     169.0   \n",
       "Spectre                                                    602.0     148.0   \n",
       "...                                                          ...       ...   \n",
       "A Plague So Pleasant                                        13.0      76.0   \n",
       "Shanghai Calling                                            14.0     100.0   \n",
       "My Date with Drew                                           43.0      90.0   \n",
       "\n",
       "                                                  ...           \\\n",
       "movie_title                                       ...            \n",
       "Avatar                                            ...            \n",
       "Pirates of the Caribbean: At World's End          ...            \n",
       "Spectre                                           ...            \n",
       "...                                               ...            \n",
       "A Plague So Pleasant                              ...            \n",
       "Shanghai Calling                                  ...            \n",
       "My Date with Drew                                 ...            \n",
       "\n",
       "                                          actor_2_facebook_likes  imdb_score  \\\n",
       "movie_title                                                                    \n",
       "Avatar                                                     936.0         7.9   \n",
       "Pirates of the Caribbean: At World's End                  5000.0         7.1   \n",
       "Spectre                                                    393.0         6.8   \n",
       "...                                                          ...         ...   \n",
       "A Plague So Pleasant                                         0.0         6.3   \n",
       "Shanghai Calling                                           719.0         6.3   \n",
       "My Date with Drew                                           23.0         6.6   \n",
       "\n",
       "                                         aspect_ratio  movie_facebook_likes  \n",
       "movie_title                                                                  \n",
       "Avatar                                           1.78                 33000  \n",
       "Pirates of the Caribbean: At World's End         2.35                     0  \n",
       "Spectre                                          2.35                 85000  \n",
       "...                                               ...                   ...  \n",
       "A Plague So Pleasant                              NaN                    16  \n",
       "Shanghai Calling                                 2.35                   660  \n",
       "My Date with Drew                                1.85                   456  \n",
       "\n",
       "[4916 rows x 27 columns]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie2 = movie.set_index('movie_title')\n",
    "movie2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>color</th>\n",
       "      <th>director_name</th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>duration</th>\n",
       "      <th>...</th>\n",
       "      <th>actor_2_facebook_likes</th>\n",
       "      <th>imdb_score</th>\n",
       "      <th>aspect_ratio</th>\n",
       "      <th>movie_facebook_likes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>movie_title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>Avatar</th>\n",
       "      <td>Color</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>723.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>...</td>\n",
       "      <td>936.0</td>\n",
       "      <td>7.9</td>\n",
       "      <td>1.78</td>\n",
       "      <td>33000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pirates of the Caribbean: At World's End</th>\n",
       "      <td>Color</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "      <td>302.0</td>\n",
       "      <td>169.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spectre</th>\n",
       "      <td>Color</td>\n",
       "      <td>Sam Mendes</td>\n",
       "      <td>602.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>...</td>\n",
       "      <td>393.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.35</td>\n",
       "      <td>85000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A Plague So Pleasant</th>\n",
       "      <td>Color</td>\n",
       "      <td>Benjamin Roberds</td>\n",
       "      <td>13.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shanghai Calling</th>\n",
       "      <td>Color</td>\n",
       "      <td>Daniel Hsia</td>\n",
       "      <td>14.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>719.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>2.35</td>\n",
       "      <td>660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>My Date with Drew</th>\n",
       "      <td>Color</td>\n",
       "      <td>Jon Gunn</td>\n",
       "      <td>43.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>...</td>\n",
       "      <td>23.0</td>\n",
       "      <td>6.6</td>\n",
       "      <td>1.85</td>\n",
       "      <td>456</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4916 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          color     director_name  \\\n",
       "movie_title                                                         \n",
       "Avatar                                    Color     James Cameron   \n",
       "Pirates of the Caribbean: At World's End  Color    Gore Verbinski   \n",
       "Spectre                                   Color        Sam Mendes   \n",
       "...                                         ...               ...   \n",
       "A Plague So Pleasant                      Color  Benjamin Roberds   \n",
       "Shanghai Calling                          Color       Daniel Hsia   \n",
       "My Date with Drew                         Color          Jon Gunn   \n",
       "\n",
       "                                          num_critic_for_reviews  duration  \\\n",
       "movie_title                                                                  \n",
       "Avatar                                                     723.0     178.0   \n",
       "Pirates of the Caribbean: At World's End                   302.0     169.0   \n",
       "Spectre                                                    602.0     148.0   \n",
       "...                                                          ...       ...   \n",
       "A Plague So Pleasant                                        13.0      76.0   \n",
       "Shanghai Calling                                            14.0     100.0   \n",
       "My Date with Drew                                           43.0      90.0   \n",
       "\n",
       "                                                  ...           \\\n",
       "movie_title                                       ...            \n",
       "Avatar                                            ...            \n",
       "Pirates of the Caribbean: At World's End          ...            \n",
       "Spectre                                           ...            \n",
       "...                                               ...            \n",
       "A Plague So Pleasant                              ...            \n",
       "Shanghai Calling                                  ...            \n",
       "My Date with Drew                                 ...            \n",
       "\n",
       "                                          actor_2_facebook_likes  imdb_score  \\\n",
       "movie_title                                                                    \n",
       "Avatar                                                     936.0         7.9   \n",
       "Pirates of the Caribbean: At World's End                  5000.0         7.1   \n",
       "Spectre                                                    393.0         6.8   \n",
       "...                                                          ...         ...   \n",
       "A Plague So Pleasant                                         0.0         6.3   \n",
       "Shanghai Calling                                           719.0         6.3   \n",
       "My Date with Drew                                           23.0         6.6   \n",
       "\n",
       "                                         aspect_ratio  movie_facebook_likes  \n",
       "movie_title                                                                  \n",
       "Avatar                                           1.78                 33000  \n",
       "Pirates of the Caribbean: At World's End         2.35                     0  \n",
       "Spectre                                          2.35                 85000  \n",
       "...                                               ...                   ...  \n",
       "A Plague So Pleasant                              NaN                    16  \n",
       "Shanghai Calling                                 2.35                   660  \n",
       "My Date with Drew                                1.85                   456  \n",
       "\n",
       "[4916 rows x 27 columns]"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('data/movie.csv', index_col='movie_title')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# There's more..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        text-align: right;\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>movie_title</th>\n",
       "      <th>color</th>\n",
       "      <th>director_name</th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>...</th>\n",
       "      <th>actor_2_facebook_likes</th>\n",
       "      <th>imdb_score</th>\n",
       "      <th>aspect_ratio</th>\n",
       "      <th>movie_facebook_likes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Avatar</td>\n",
       "      <td>Color</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>723.0</td>\n",
       "      <td>...</td>\n",
       "      <td>936.0</td>\n",
       "      <td>7.9</td>\n",
       "      <td>1.78</td>\n",
       "      <td>33000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>Color</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "      <td>302.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Spectre</td>\n",
       "      <td>Color</td>\n",
       "      <td>Sam Mendes</td>\n",
       "      <td>602.0</td>\n",
       "      <td>...</td>\n",
       "      <td>393.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.35</td>\n",
       "      <td>85000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4913</th>\n",
       "      <td>A Plague So Pleasant</td>\n",
       "      <td>Color</td>\n",
       "      <td>Benjamin Roberds</td>\n",
       "      <td>13.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4914</th>\n",
       "      <td>Shanghai Calling</td>\n",
       "      <td>Color</td>\n",
       "      <td>Daniel Hsia</td>\n",
       "      <td>14.0</td>\n",
       "      <td>...</td>\n",
       "      <td>719.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>2.35</td>\n",
       "      <td>660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4915</th>\n",
       "      <td>My Date with Drew</td>\n",
       "      <td>Color</td>\n",
       "      <td>Jon Gunn</td>\n",
       "      <td>43.0</td>\n",
       "      <td>...</td>\n",
       "      <td>23.0</td>\n",
       "      <td>6.6</td>\n",
       "      <td>1.85</td>\n",
       "      <td>456</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4916 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   movie_title  color     director_name  \\\n",
       "0                                       Avatar  Color     James Cameron   \n",
       "1     Pirates of the Caribbean: At World's End  Color    Gore Verbinski   \n",
       "2                                      Spectre  Color        Sam Mendes   \n",
       "...                                        ...    ...               ...   \n",
       "4913                      A Plague So Pleasant  Color  Benjamin Roberds   \n",
       "4914                          Shanghai Calling  Color       Daniel Hsia   \n",
       "4915                         My Date with Drew  Color          Jon Gunn   \n",
       "\n",
       "      num_critic_for_reviews         ...           actor_2_facebook_likes  \\\n",
       "0                      723.0         ...                            936.0   \n",
       "1                      302.0         ...                           5000.0   \n",
       "2                      602.0         ...                            393.0   \n",
       "...                      ...         ...                              ...   \n",
       "4913                    13.0         ...                              0.0   \n",
       "4914                    14.0         ...                            719.0   \n",
       "4915                    43.0         ...                             23.0   \n",
       "\n",
       "      imdb_score  aspect_ratio movie_facebook_likes  \n",
       "0            7.9          1.78                33000  \n",
       "1            7.1          2.35                    0  \n",
       "2            6.8          2.35                85000  \n",
       "...          ...           ...                  ...  \n",
       "4913         6.3           NaN                   16  \n",
       "4914         6.3          2.35                  660  \n",
       "4915         6.6          1.85                  456  \n",
       "\n",
       "[4916 rows x 28 columns]"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie2.reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Renaming row and column names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "movie = pd.read_csv('data/movie.csv', index_col='movie_title')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "idx_rename = {'Avatar':'Ratava', 'Spectre': 'Ertceps'} \n",
    "col_rename = {'director_name':'Director Name', \n",
    "              'num_critic_for_reviews': 'Critical Reviews'} "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>color</th>\n",
       "      <th>Director Name</th>\n",
       "      <th>Critical Reviews</th>\n",
       "      <th>duration</th>\n",
       "      <th>...</th>\n",
       "      <th>actor_2_facebook_likes</th>\n",
       "      <th>imdb_score</th>\n",
       "      <th>aspect_ratio</th>\n",
       "      <th>movie_facebook_likes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>movie_title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>Ratava</th>\n",
       "      <td>Color</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>723.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>...</td>\n",
       "      <td>936.0</td>\n",
       "      <td>7.9</td>\n",
       "      <td>1.78</td>\n",
       "      <td>33000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pirates of the Caribbean: At World's End</th>\n",
       "      <td>Color</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "      <td>302.0</td>\n",
       "      <td>169.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ertceps</th>\n",
       "      <td>Color</td>\n",
       "      <td>Sam Mendes</td>\n",
       "      <td>602.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>...</td>\n",
       "      <td>393.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.35</td>\n",
       "      <td>85000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Dark Knight Rises</th>\n",
       "      <td>Color</td>\n",
       "      <td>Christopher Nolan</td>\n",
       "      <td>813.0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>...</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>8.5</td>\n",
       "      <td>2.35</td>\n",
       "      <td>164000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Star Wars: Episode VII - The Force Awakens</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Doug Walker</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            color      Director Name  \\\n",
       "movie_title                                                            \n",
       "Ratava                                      Color      James Cameron   \n",
       "Pirates of the Caribbean: At World's End    Color     Gore Verbinski   \n",
       "Ertceps                                     Color         Sam Mendes   \n",
       "The Dark Knight Rises                       Color  Christopher Nolan   \n",
       "Star Wars: Episode VII - The Force Awakens    NaN        Doug Walker   \n",
       "\n",
       "                                            Critical Reviews  duration  \\\n",
       "movie_title                                                              \n",
       "Ratava                                                 723.0     178.0   \n",
       "Pirates of the Caribbean: At World's End               302.0     169.0   \n",
       "Ertceps                                                602.0     148.0   \n",
       "The Dark Knight Rises                                  813.0     164.0   \n",
       "Star Wars: Episode VII - The Force Awakens               NaN       NaN   \n",
       "\n",
       "                                                    ...           \\\n",
       "movie_title                                         ...            \n",
       "Ratava                                              ...            \n",
       "Pirates of the Caribbean: At World's End            ...            \n",
       "Ertceps                                             ...            \n",
       "The Dark Knight Rises                               ...            \n",
       "Star Wars: Episode VII - The Force Awakens          ...            \n",
       "\n",
       "                                            actor_2_facebook_likes  \\\n",
       "movie_title                                                          \n",
       "Ratava                                                       936.0   \n",
       "Pirates of the Caribbean: At World's End                    5000.0   \n",
       "Ertceps                                                      393.0   \n",
       "The Dark Knight Rises                                      23000.0   \n",
       "Star Wars: Episode VII - The Force Awakens                    12.0   \n",
       "\n",
       "                                            imdb_score aspect_ratio  \\\n",
       "movie_title                                                           \n",
       "Ratava                                             7.9         1.78   \n",
       "Pirates of the Caribbean: At World's End           7.1         2.35   \n",
       "Ertceps                                            6.8         2.35   \n",
       "The Dark Knight Rises                              8.5         2.35   \n",
       "Star Wars: Episode VII - The Force Awakens         7.1          NaN   \n",
       "\n",
       "                                            movie_facebook_likes  \n",
       "movie_title                                                       \n",
       "Ratava                                                     33000  \n",
       "Pirates of the Caribbean: At World's End                       0  \n",
       "Ertceps                                                    85000  \n",
       "The Dark Knight Rises                                     164000  \n",
       "Star Wars: Episode VII - The Force Awakens                     0  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie.rename(index=idx_rename, \n",
    "             columns=col_rename).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# There's more"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "movie = pd.read_csv('data/movie.csv', index_col='movie_title')\n",
    "index = movie.index\n",
    "columns = movie.columns\n",
    "\n",
    "index_list = index.tolist()\n",
    "column_list = columns.tolist()\n",
    "\n",
    "index_list[0] = 'Ratava'\n",
    "index_list[2] = 'Ertceps'\n",
    "column_list[1] = 'Director Name'\n",
    "column_list[2] = 'Critical Reviews'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Ratava', \"Pirates of the Caribbean: At World's End\", 'Ertceps', 'The Dark Knight Rises', 'Star Wars: Episode VII - The Force Awakens']\n"
     ]
    }
   ],
   "source": [
    "print(index_list[:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['color', 'Director Name', 'Critical Reviews', 'duration', 'director_facebook_likes', 'actor_3_facebook_likes', 'actor_2_name', 'actor_1_facebook_likes', 'gross', 'genres', 'actor_1_name', 'num_voted_users', 'cast_total_facebook_likes', 'actor_3_name', 'facenumber_in_poster', 'plot_keywords', 'movie_imdb_link', 'num_user_for_reviews', 'language', 'country', 'content_rating', 'budget', 'title_year', 'actor_2_facebook_likes', 'imdb_score', 'aspect_ratio', 'movie_facebook_likes']\n"
     ]
    }
   ],
   "source": [
    "print(column_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "movie.index = index_list\n",
    "movie.columns = column_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Ratava</th>\n",
       "      <td>Color</td>\n",
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       "      <td>Color</td>\n",
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       "      <th>Ertceps</th>\n",
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       "      <td>Sam Mendes</td>\n",
       "      <td>602.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>...</td>\n",
       "      <td>393.0</td>\n",
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       "      <td>2.35</td>\n",
       "      <td>85000</td>\n",
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       "    <tr>\n",
       "      <th>The Dark Knight Rises</th>\n",
       "      <td>Color</td>\n",
       "      <td>Christopher Nolan</td>\n",
       "      <td>813.0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>...</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>8.5</td>\n",
       "      <td>2.35</td>\n",
       "      <td>164000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Star Wars: Episode VII - The Force Awakens</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Doug Walker</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            color      Director Name  \\\n",
       "Ratava                                      Color      James Cameron   \n",
       "Pirates of the Caribbean: At World's End    Color     Gore Verbinski   \n",
       "Ertceps                                     Color         Sam Mendes   \n",
       "The Dark Knight Rises                       Color  Christopher Nolan   \n",
       "Star Wars: Episode VII - The Force Awakens    NaN        Doug Walker   \n",
       "\n",
       "                                            Critical Reviews  duration  \\\n",
       "Ratava                                                 723.0     178.0   \n",
       "Pirates of the Caribbean: At World's End               302.0     169.0   \n",
       "Ertceps                                                602.0     148.0   \n",
       "The Dark Knight Rises                                  813.0     164.0   \n",
       "Star Wars: Episode VII - The Force Awakens               NaN       NaN   \n",
       "\n",
       "                                                    ...           \\\n",
       "Ratava                                              ...            \n",
       "Pirates of the Caribbean: At World's End            ...            \n",
       "Ertceps                                             ...            \n",
       "The Dark Knight Rises                               ...            \n",
       "Star Wars: Episode VII - The Force Awakens          ...            \n",
       "\n",
       "                                            actor_2_facebook_likes  \\\n",
       "Ratava                                                       936.0   \n",
       "Pirates of the Caribbean: At World's End                    5000.0   \n",
       "Ertceps                                                      393.0   \n",
       "The Dark Knight Rises                                      23000.0   \n",
       "Star Wars: Episode VII - The Force Awakens                    12.0   \n",
       "\n",
       "                                            imdb_score aspect_ratio  \\\n",
       "Ratava                                             7.9         1.78   \n",
       "Pirates of the Caribbean: At World's End           7.1         2.35   \n",
       "Ertceps                                            6.8         2.35   \n",
       "The Dark Knight Rises                              8.5         2.35   \n",
       "Star Wars: Episode VII - The Force Awakens         7.1          NaN   \n",
       "\n",
       "                                            movie_facebook_likes  \n",
       "Ratava                                                     33000  \n",
       "Pirates of the Caribbean: At World's End                       0  \n",
       "Ertceps                                                    85000  \n",
       "The Dark Knight Rises                                     164000  \n",
       "Star Wars: Episode VII - The Force Awakens                     0  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creating and deleting columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "movie = pd.read_csv('data/movie.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "movie['has_seen'] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['color', 'director_name', 'num_critic_for_reviews', 'duration',\n",
       "       'director_facebook_likes', 'actor_3_facebook_likes', 'actor_2_name',\n",
       "       'actor_1_facebook_likes', 'gross', 'genres', 'actor_1_name',\n",
       "       'movie_title', 'num_voted_users', 'cast_total_facebook_likes',\n",
       "       'actor_3_name', 'facenumber_in_poster', 'plot_keywords',\n",
       "       'movie_imdb_link', 'num_user_for_reviews', 'language', 'country',\n",
       "       'content_rating', 'budget', 'title_year', 'actor_2_facebook_likes',\n",
       "       'imdb_score', 'aspect_ratio', 'movie_facebook_likes', 'has_seen'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "movie['actor_director_facebook_likes'] = (movie['actor_1_facebook_likes'] + \n",
    "                                              movie['actor_2_facebook_likes'] + \n",
    "                                              movie['actor_3_facebook_likes'] + \n",
    "                                              movie['director_facebook_likes'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "122"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie['actor_director_facebook_likes'].isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "movie['actor_director_facebook_likes'] = movie['actor_director_facebook_likes'].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "movie['is_cast_likes_more'] = (movie['cast_total_facebook_likes'] >= \n",
    "                                  movie['actor_director_facebook_likes'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie['is_cast_likes_more'].all()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "movie = movie.drop('actor_director_facebook_likes', axis='columns')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "movie['actor_total_facebook_likes'] = (movie['actor_1_facebook_likes'] + \n",
    "                                       movie['actor_2_facebook_likes'] + \n",
    "                                       movie['actor_3_facebook_likes'])\n",
    "\n",
    "movie['actor_total_facebook_likes'] = movie['actor_total_facebook_likes'].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie['is_cast_likes_more'] = movie['cast_total_facebook_likes'] >= \\\n",
    "                                  movie['actor_total_facebook_likes']\n",
    "    \n",
    "movie['is_cast_likes_more'].all()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "movie['pct_actor_cast_like'] = (movie['actor_total_facebook_likes'] / \n",
    "                                movie['cast_total_facebook_likes'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 1.0)"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie['pct_actor_cast_like'].min(), movie['pct_actor_cast_like'].max() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "movie_title\n",
       "Avatar                                        0.577369\n",
       "Pirates of the Caribbean: At World's End      0.951396\n",
       "Spectre                                       0.987521\n",
       "The Dark Knight Rises                         0.683783\n",
       "Star Wars: Episode VII - The Force Awakens    0.000000\n",
       "Name: pct_actor_cast_like, dtype: float64"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie.set_index('movie_title')['pct_actor_cast_like'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## There's more..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profit_index = movie.columns.get_loc('gross') + 1\n",
    "profit_index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "movie.insert(loc=profit_index,\n",
    "                 column='profit',\n",
    "                 value=movie['gross'] - movie['budget'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>color</th>\n",
       "      <th>director_name</th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>duration</th>\n",
       "      <th>...</th>\n",
       "      <th>has_seen</th>\n",
       "      <th>is_cast_likes_more</th>\n",
       "      <th>actor_total_facebook_likes</th>\n",
       "      <th>pct_actor_cast_like</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Color</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>723.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>2791.0</td>\n",
       "      <td>0.577369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Color</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "      <td>302.0</td>\n",
       "      <td>169.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>46000.0</td>\n",
       "      <td>0.951396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Color</td>\n",
       "      <td>Sam Mendes</td>\n",
       "      <td>602.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>11554.0</td>\n",
       "      <td>0.987521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Color</td>\n",
       "      <td>Christopher Nolan</td>\n",
       "      <td>813.0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>73000.0</td>\n",
       "      <td>0.683783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Doug Walker</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 33 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   color      director_name  num_critic_for_reviews  duration  \\\n",
       "0  Color      James Cameron                   723.0     178.0   \n",
       "1  Color     Gore Verbinski                   302.0     169.0   \n",
       "2  Color         Sam Mendes                   602.0     148.0   \n",
       "3  Color  Christopher Nolan                   813.0     164.0   \n",
       "4    NaN        Doug Walker                     NaN       NaN   \n",
       "\n",
       "          ...           has_seen  is_cast_likes_more  \\\n",
       "0         ...                  0                True   \n",
       "1         ...                  0                True   \n",
       "2         ...                  0                True   \n",
       "3         ...                  0                True   \n",
       "4         ...                  0                True   \n",
       "\n",
       "  actor_total_facebook_likes  pct_actor_cast_like  \n",
       "0                     2791.0             0.577369  \n",
       "1                    46000.0             0.951396  \n",
       "2                    11554.0             0.987521  \n",
       "3                    73000.0             0.683783  \n",
       "4                        0.0             0.000000  \n",
       "\n",
       "[5 rows x 33 columns]"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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