Exercises-2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from mpltools import style\n",
    "from mpltools import layout\n",
    "\n",
    "style.use('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>body {\n",
       "    margin: 0;\n",
       "    font-family: Helvetica;\n",
       "}\n",
       "table.dataframe {\n",
       "    border-collapse: collapse;\n",
       "    border: none;\n",
       "}\n",
       "table.dataframe tr {\n",
       "    border: none;\n",
       "}\n",
       "table.dataframe td, table.dataframe th {\n",
       "    margin: 0;\n",
       "    border: 1px solid white;\n",
       "    padding-left: 0.25em;\n",
       "    padding-right: 0.25em;\n",
       "}\n",
       "table.dataframe th:not(:empty) {\n",
       "    background-color: #fec;\n",
       "    text-align: left;\n",
       "    font-weight: normal;\n",
       "}\n",
       "table.dataframe tr:nth-child(2) th:empty {\n",
       "    border-left: none;\n",
       "    border-right: 1px dashed #888;\n",
       "}\n",
       "table.dataframe td {\n",
       "    border: 2px solid #ccf;\n",
       "    background-color: #f4f4ff;\n",
       "}\n",
       "h3 {\n",
       "    color: white;\n",
       "    background-color: black;\n",
       "    padding: 0.5em;\n",
       "}\n",
       "</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.core.display import HTML\n",
    "css = open('style-table.css').read() + open('style-notebook.css').read()\n",
    "HTML('<style>{}</style>'.format(css))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>                 Night Walker</td>\n",
       "      <td> 2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>             Black Devil Doll</td>\n",
       "      <td> 2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>                Sedmaya pulya</td>\n",
       "      <td> 1973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td> The Gentleman from Louisiana</td>\n",
       "      <td> 1936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>                Agente XU 777</td>\n",
       "      <td> 1963</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          title  year\n",
       "0                  Night Walker  2017\n",
       "1              Black Devil Doll  2007\n",
       "2                 Sedmaya pulya  1973\n",
       "3  The Gentleman from Louisiana  1936\n",
       "4                 Agente XU 777  1963"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titles = pd.DataFrame.from_csv('data/titles.csv', index_col=None)\n",
    "titles.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>year</th>\n",
       "      <th>name</th>\n",
       "      <th>type</th>\n",
       "      <th>character</th>\n",
       "      <th>n</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>                   Suuri illusioni</td>\n",
       "      <td> 1985</td>\n",
       "      <td>    Homo $</td>\n",
       "      <td> actor</td>\n",
       "      <td>  Guests</td>\n",
       "      <td> 22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>    Gangsta Rap: The Glockumentary</td>\n",
       "      <td> 2007</td>\n",
       "      <td> Too $hort</td>\n",
       "      <td> actor</td>\n",
       "      <td> Himself</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>                 Menace II Society</td>\n",
       "      <td> 1993</td>\n",
       "      <td> Too $hort</td>\n",
       "      <td> actor</td>\n",
       "      <td> Lew-Loc</td>\n",
       "      <td> 27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td> Porndogs: The Adventures of Sadie</td>\n",
       "      <td> 2009</td>\n",
       "      <td> Too $hort</td>\n",
       "      <td> actor</td>\n",
       "      <td>   Bosco</td>\n",
       "      <td>  3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>                Stop Pepper Palmer</td>\n",
       "      <td> 2014</td>\n",
       "      <td> Too $hort</td>\n",
       "      <td> actor</td>\n",
       "      <td> Himself</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               title  year       name   type character   n\n",
       "0                    Suuri illusioni  1985     Homo $  actor    Guests  22\n",
       "1     Gangsta Rap: The Glockumentary  2007  Too $hort  actor   Himself NaN\n",
       "2                  Menace II Society  1993  Too $hort  actor   Lew-Loc  27\n",
       "3  Porndogs: The Adventures of Sadie  2009  Too $hort  actor     Bosco   3\n",
       "4                 Stop Pepper Palmer  2014  Too $hort  actor   Himself NaN"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cast = pd.DataFrame.from_csv('data/cast.csv', index_col=None)\n",
    "cast.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### What are the ten most common movie names of all time?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Hamlet                  19\n",
       "Macbeth                 14\n",
       "Carmen                  14\n",
       "The Three Musketeers    12\n",
       "Maya                    11\n",
       "dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titles['title'].value_counts().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "86898    xXx\n",
       "Name: title, dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titles['title'][titles.title == 'xXx']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Which three years of the 1930s saw the most films released?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1172d17f0>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1174705c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "moviesOf1930s = titles[(titles.year >= 1930) & (titles.year < 1940)]\n",
    "\n",
    "moviesOf1930s.year.value_counts().sort_index().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Plot the number of films that have been released each decade over the history of cinema."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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tLS3YbDbcbjdWqxW49R9/c3Ozb53m5mYcDkefPYHbx3vXaWpqwm634/F4aG9vH3CvoHfC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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10aa2ff28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = titles\n",
    "t.groupby(t.year // 10 * 10).size().plot(kind='bar')\n",
    "del t"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Plot the number of \"Hamlet\" films made each decade."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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KWeiPPfZY0PX5+fnIz8+PWCAiIvp6eKYoEZEkWOhERJJgoRMRSYKFTkQkCRY6EZEkWOhE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\npwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117a70be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hFilms = titles[titles.title == 'Hamlet']\n",
    "hFilms.groupby(hFilms.year // 10 * 10).size().plot(kind='bar')\n",
    "del hFilms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "Missing parentheses in call to 'print' (<ipython-input-81-0f5ad439a26e>, line 1)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-81-0f5ad439a26e>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m    print matplotlib.pyplot.plt.style.available\u001b[0m\n\u001b[0m                   ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m Missing parentheses in call to 'print'\n"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Plot the number of \"Rustler\" characters in each decade of the history of film."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Plot the number of \"Batman\" characters each decade."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### What are the 11 most common character names in movie history?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Who are the 10 people most often credited as \"Herself\" in film history?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Who are the 10 people most often credited as \"Himself\" in film history?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Which actors or actresses appeared in the most movies in the year 1945?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Which actors or actresses appeared in the most movies in the year 1985?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Plot how many roles Mammootty has played in each year of his career."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### What are the 10 most frequent roles that start with the phrase \"Patron in\"?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### What are the 10 most frequent roles that start with the word \"Science\"?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Plot the n-values of the roles that Judi Dench has played over her career."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Plot the n-values of Cary Grant's roles through his career."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Plot the n-value of the roles that Sidney Poitier has acted over the years."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### How many leading (n=1) roles were available to actors, and how many to actresses, in the 1950s?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### How many supporting (n=2) roles were available to actors, and how many to actresses, in the 1950s?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Y1NfXm+oDAOCi7HxdFQDQrxEGAADCAABAGAAARBgAAEQYAABEGAAARBgAAEQYAADk8Exn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\njAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112f05c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "c = cast\n",
    "c = c[c.name == \"George Clooney\"]\n",
    "c.groupby(['year']).size().plot(kind='hist')\n",
    "del c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}