proj1_visualization.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Name: Lea Wei  \n",
    "uniqname: zhuoqunw  \n",
    "Bechdel project visualization  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ThemeRegistry.enable('fivethirtyeight')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import altair as alt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "#from genderperformr import GenderPerformr\n",
    "#gp = GenderPerformr()\n",
    "alt.themes.enable(\"fivethirtyeight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DataTransformerRegistry.enable('csv')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import data\n",
    "bech_budget_revenue = pd.read_csv(\"/Users/zhuoqunwei/Development/UMSI/SI618/project1/cleaned datasets/bech_budget_revenue.csv\")\n",
    "bech_movie = pd.read_csv(\"/Users/zhuoqunwei/Development/UMSI/SI618/project1/cleaned datasets/bech_movie.csv\")\n",
    "bechdel = pd.read_csv(\"/Users/zhuoqunwei/Development/UMSI/SI618/project1/cleaned datasets/bechdel.csv\")\n",
    "alt.data_transformers.enable('csv') #deal with extremely large dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Q0: percentage of movies passing the test over decades "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>imdbid</th>\n",
       "      <th>rating</th>\n",
       "      <th>title</th>\n",
       "      <th>year</th>\n",
       "      <th>test_result</th>\n",
       "      <th>year_group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8040</td>\n",
       "      <td>392728.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Roundhay Garden Scene</td>\n",
       "      <td>1888</td>\n",
       "      <td>Pass 0:Fewer than two women</td>\n",
       "      <td>1880-1920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5433</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Pauvre Pierrot</td>\n",
       "      <td>1892</td>\n",
       "      <td>Pass 0:Fewer than two women</td>\n",
       "      <td>1880-1920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6200</td>\n",
       "      <td>132134.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Execution of Mary, Queen of Scots, The</td>\n",
       "      <td>1895</td>\n",
       "      <td>Pass 0:Fewer than two women</td>\n",
       "      <td>1880-1920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5444</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Tables Turned on the Gardener</td>\n",
       "      <td>1895</td>\n",
       "      <td>Pass 0:Fewer than two women</td>\n",
       "      <td>1880-1920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5406</td>\n",
       "      <td>131.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Une nuit terrible</td>\n",
       "      <td>1896</td>\n",
       "      <td>Pass 0:Fewer than two women</td>\n",
       "      <td>1880-1920</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     id    imdbid  rating                                   title  year  \\\n",
       "0  8040  392728.0       0                   Roundhay Garden Scene  1888   \n",
       "1  5433       3.0       0                          Pauvre Pierrot  1892   \n",
       "2  6200  132134.0       0  Execution of Mary, Queen of Scots, The  1895   \n",
       "3  5444      14.0       0           Tables Turned on the Gardener  1895   \n",
       "4  5406     131.0       0                       Une nuit terrible  1896   \n",
       "\n",
       "                   test_result year_group  \n",
       "0  Pass 0:Fewer than two women  1880-1920  \n",
       "1  Pass 0:Fewer than two women  1880-1920  \n",
       "2  Pass 0:Fewer than two women  1880-1920  \n",
       "3  Pass 0:Fewer than two women  1880-1920  \n",
       "4  Pass 0:Fewer than two women  1880-1920  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create year group\n",
    "bins = [1880, 1920, 1930, 1940, 1950, 1960, 1970, 1980, 1990, 2000, 2010, 2020]\n",
    "bechdel['year_group'] = pd.cut(bechdel['year'], bins,\n",
    "                              labels=['1880-1920', '1920s', '1930s', '1940s','1950s', '1960s', '1970s', '1980s', '1990s','2000s','2010s'])\n",
    "bechdel.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year_group  test_result                          \n",
       "1880-1920   Pass 0:Fewer than two women                63\n",
       "            Pass 1:Women don't talk to each other       2\n",
       "            Pass 2:Women only talk about men            5\n",
       "            Pass 3:Passes Bechdel Test                 14\n",
       "1920s       Pass 0:Fewer than two women                37\n",
       "            Pass 1:Women don't talk to each other      13\n",
       "            Pass 2:Women only talk about men           19\n",
       "            Pass 3:Passes Bechdel Test                 21\n",
       "1930s       Pass 0:Fewer than two women                25\n",
       "            Pass 1:Women don't talk to each other      43\n",
       "            Pass 2:Women only talk about men           45\n",
       "            Pass 3:Passes Bechdel Test                107\n",
       "1940s       Pass 0:Fewer than two women                30\n",
       "            Pass 1:Women don't talk to each other      44\n",
       "            Pass 2:Women only talk about men           34\n",
       "            Pass 3:Passes Bechdel Test                104\n",
       "1950s       Pass 0:Fewer than two women                41\n",
       "            Pass 1:Women don't talk to each other      60\n",
       "            Pass 2:Women only talk about men           44\n",
       "            Pass 3:Passes Bechdel Test                139\n",
       "1960s       Pass 0:Fewer than two women                66\n",
       "            Pass 1:Women don't talk to each other      93\n",
       "            Pass 2:Women only talk about men           30\n",
       "            Pass 3:Passes Bechdel Test                152\n",
       "1970s       Pass 0:Fewer than two women                45\n",
       "            Pass 1:Women don't talk to each other     109\n",
       "            Pass 2:Women only talk about men           45\n",
       "            Pass 3:Passes Bechdel Test                184\n",
       "1980s       Pass 0:Fewer than two women                73\n",
       "            Pass 1:Women don't talk to each other     146\n",
       "            Pass 2:Women only talk about men           72\n",
       "            Pass 3:Passes Bechdel Test                347\n",
       "1990s       Pass 0:Fewer than two women                88\n",
       "            Pass 1:Women don't talk to each other     268\n",
       "            Pass 2:Women only talk about men          113\n",
       "            Pass 3:Passes Bechdel Test                646\n",
       "2000s       Pass 0:Fewer than two women               202\n",
       "            Pass 1:Women don't talk to each other     546\n",
       "            Pass 2:Women only talk about men          198\n",
       "            Pass 3:Passes Bechdel Test               1431\n",
       "2010s       Pass 0:Fewer than two women               201\n",
       "            Pass 1:Women don't talk to each other     558\n",
       "            Pass 2:Women only talk about men          268\n",
       "            Pass 3:Passes Bechdel Test               1803\n",
       "Name: id, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count_test = bechdel.groupby([\"year_group\",\"test_result\"])[\"id\"].count()\n",
    "#count_test[\"id\"]=count_test[\"id\"].fillna(0)\n",
    "count_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "percent_test = count_test.groupby(level=[0]).apply(lambda g: g / g.sum()).to_frame(name = 'percent').reset_index()\n",
    "percent_test.columns = ['Decades', 'Test Result', 'Percent']\n",
    "\n",
    "percent_test.head()\n",
    "\n",
    "percent_test.loc[percent_test['Test Result'] == \"Pass 0:Fewer than two women\", 'Test Result'] = 'Pass 0 of 3'\n",
    "percent_test.loc[percent_test['Test Result'] == \"Pass 1:Women don't talk to each other\", 'Test Result'] = 'Pass 1 of 3'\n",
    "percent_test.loc[percent_test['Test Result'] == \"Pass 2:Women only talk about men\", 'Test Result'] = 'Pass 2 of 3'\n",
    "percent_test.loc[percent_test['Test Result'] == \"Pass 3:Passes Bechdel Test\", 'Test Result'] = 'Pass all 3'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300, \"strokeWidth\": 0}, \"axis\": {\"grid\": false}, \"title\": {\"anchor\": \"start\", \"fontSize\": 20}}, \"layer\": [{\"mark\": \"bar\", \"encoding\": {\"color\": {\"type\": \"nominal\", \"field\": \"Test Result\", \"legend\": {\"orient\": \"top\", \"title\": null}}, \"opacity\": {\"value\": 0.9}, \"order\": {\"type\": \"nominal\", \"field\": \"Test Result\"}, \"x\": {\"type\": \"quantitative\", \"axis\": {\"format\": \".0%\"}, \"field\": \"Percent\", \"stack\": \"normalize\", \"title\": \"\"}, \"y\": {\"type\": \"ordinal\", \"field\": \"Decades\", \"title\": \"\"}}}, {\"mark\": {\"type\": \"text\", \"color\": \"white\", \"dx\": -11, \"dy\": 3}, \"encoding\": {\"order\": {\"type\": \"nominal\", \"field\": \"Test Result\"}, \"text\": {\"type\": \"quantitative\", \"field\": \"Percent\", \"format\": \".0%\"}, \"x\": {\"type\": \"quantitative\", \"field\": \"Percent\", \"stack\": \"normalize\"}, \"y\": {\"type\": \"ordinal\", \"field\": \"Decades\"}}}], \"data\": {\"url\": \"altair-data-465def74fc727106030cf93da7e0ffdc.csv\", \"format\": {\"type\": \"csv\"}}, \"height\": 350, \"title\": {\"text\": [\"Percentage of movies passing the bechdel test over decades: since 1880\"], \"subtitle\": [\"Criteria:\", \"1.have at least two named women\", \"2.who talk to each other\", \"3.about something besides men\", \"* combine 1880-1920 because of the lack of data in each decade\"], \"color\": \"black\"}, \"width\": 650, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
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       "alt.LayerChart(...)"
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     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "time_trend = alt.Chart(percent_test).mark_bar().encode(\n",
    "    y = alt.Y(\"Decades:O\", title = \"\"),\n",
    "    x = alt.X(\"Percent\", \n",
    "              stack=\"normalize\", \n",
    "              axis=alt.Axis(format='.0%'),\n",
    "              title=\"\"),\n",
    "    color = alt.Color(\"Test Result:N\", legend=alt.Legend(orient='top', title=None)),\n",
    "    order = \"Test Result:N\",\n",
    "    opacity = alt.value(0.9)\n",
    ")\n",
    "\n",
    "text = alt.Chart(percent_test).mark_text(dx=-11, dy=3, color='white').encode(\n",
    "    x=alt.X('Percent', stack=\"normalize\"),\n",
    "    y=alt.Y('Decades:O'),\n",
    "    text=alt.Text('Percent', format='.0%'),\n",
    "    order = \"Test Result:N\"\n",
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    "\n",
    "alt.layer(time_trend, text).properties(height=350, width=650, title={\n",
    "      \"text\": [\"Percentage of movies passing the bechdel test over decades: since 1880\"], \n",
    "      \"subtitle\": [\"Criteria:\",\n",
    "                   \"1.have at least two named women\",\n",
    "                   \"2.who talk to each other\",\n",
    "                   \"3.about something besides men\",\n",
    "                   \"* combine 1880-1920 because of the lack of data in each decade\"],\n",
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    "    strokeWidth=0\n",
    ")"
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  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Q1: percentage of movies passing the test by production country (>50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>imdbid</th>\n",
       "      <th>country</th>\n",
       "      <th>binary_pass</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>574</td>\n",
       "      <td>Australia</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2101</td>\n",
       "      <td>USA</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3973</td>\n",
       "      <td>USA</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>4972</td>\n",
       "      <td>USA</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>6745</td>\n",
       "      <td>USA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>97631</th>\n",
       "      <td>9308382</td>\n",
       "      <td>UK</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97636</th>\n",
       "      <td>9484998</td>\n",
       "      <td>USA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97637</th>\n",
       "      <td>9484998</td>\n",
       "      <td>Hong Kong</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97642</th>\n",
       "      <td>9683478</td>\n",
       "      <td>USA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97657</th>\n",
       "      <td>9737798</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11803 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        imdbid      country  binary_pass\n",
       "0          574    Australia            0\n",
       "3         2101          USA            0\n",
       "5         3973          USA            0\n",
       "7         4972          USA            0\n",
       "13        6745          USA            1\n",
       "...        ...          ...          ...\n",
       "97631  9308382           UK            1\n",
       "97636  9484998          USA            1\n",
       "97637  9484998    Hong Kong            1\n",
       "97642  9683478          USA            1\n",
       "97657  9737798  Switzerland            1\n",
       "\n",
       "[11803 rows x 3 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country_test = bech_movie[[\"imdbid\", \"country\", \"binary_pass\"]]\n",
    "country_test = country_test.drop_duplicates()\n",
    "country_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>producation country</th>\n",
       "      <th>number of movies</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>USA</td>\n",
       "      <td>5332</td>\n",
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       "      <th>1</th>\n",
       "      <td>UK</td>\n",
       "      <td>1330</td>\n",
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       "      <th>2</th>\n",
       "      <td>France</td>\n",
       "      <td>960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Germany</td>\n",
       "      <td>538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Canada</td>\n",
       "      <td>533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Japan</td>\n",
       "      <td>377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Italy</td>\n",
       "      <td>298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Spain</td>\n",
       "      <td>238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Australia</td>\n",
       "      <td>176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>China</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Sweden</td>\n",
       "      <td>124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>India</td>\n",
       "      <td>111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Mexico</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Hong Kong</td>\n",
       "      <td>107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Ireland</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Netherlands</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Hungary</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>South Korea</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   producation country  number of movies\n",
       "0                  USA              5332\n",
       "1                   UK              1330\n",
       "2               France               960\n",
       "3              Germany               538\n",
       "4               Canada               533\n",
       "5                Japan               377\n",
       "6                Italy               298\n",
       "7                Spain               238\n",
       "8            Australia               176\n",
       "9                China               146\n",
       "10             Belgium               138\n",
       "11              Sweden               124\n",
       "12               India               111\n",
       "13              Mexico               108\n",
       "14           Hong Kong               107\n",
       "15             Ireland                90\n",
       "16             Denmark                88\n",
       "17         Netherlands                63\n",
       "18             Hungary                61\n",
       "19         South Korea                59\n",
       "20         Switzerland                55"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country_count = country_test.groupby([\"country\"]).count()[\"imdbid\"].reset_index()\n",
    "country_count_50 = country_count[country_count[\"imdbid\"]>50]\n",
    "country_count_50.columns = [\"producation country\", \"number of movies\"]\n",
    "country_count_50.sort_values(by=[\"number of movies\"], ascending=False).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div id=\"altair-viz-daa378de2bc240f19c3e2df0505dc3ee\"></div>\n",
       "<script type=\"text/javascript\">\n",
       "  (function(spec, embedOpt){\n",
       "    let outputDiv = document.currentScript.previousElementSibling;\n",
       "    if (outputDiv.id !== \"altair-viz-daa378de2bc240f19c3e2df0505dc3ee\") {\n",
       "      outputDiv = document.getElementById(\"altair-viz-daa378de2bc240f19c3e2df0505dc3ee\");\n",
       "    }\n",
       "    const paths = {\n",
       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
       "    };\n",
       "\n",
       "    function loadScript(lib) {\n",
       "      return new Promise(function(resolve, reject) {\n",
       "        var s = document.createElement('script');\n",
       "        s.src = paths[lib];\n",
       "        s.async = true;\n",
       "        s.onload = () => resolve(paths[lib]);\n",
       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      });\n",
       "    }\n",
       "\n",
       "    function showError(err) {\n",
       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
       "      throw err;\n",
       "    }\n",
       "\n",
       "    function displayChart(vegaEmbed) {\n",
       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
       "    }\n",
       "\n",
       "    if(typeof define === \"function\" && define.amd) {\n",
       "      requirejs.config({paths});\n",
       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
       "    } else if (typeof vegaEmbed === \"function\") {\n",
       "      displayChart(vegaEmbed);\n",
       "    } else {\n",
       "      loadScript(\"vega\")\n",
       "        .then(() => loadScript(\"vega-lite\"))\n",
       "        .then(() => loadScript(\"vega-embed\"))\n",
       "        .catch(showError)\n",
       "        .then(() => displayChart(vegaEmbed));\n",
       "    }\n",
       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300, \"strokeWidth\": 0}, \"axis\": {\"grid\": false}, \"title\": {\"anchor\": \"start\", \"fontSize\": 20}}, \"layer\": [{\"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"field\": \"percent_pass\", \"title\": \"\"}, \"y\": {\"type\": \"nominal\", \"field\": \"country\", \"sort\": \"-x\", \"title\": \"\"}}, \"transform\": [{\"joinaggregate\": [{\"op\": \"mean\", \"field\": \"binary_pass\", \"as\": \"percent_pass\"}, {\"op\": \"count\", \"field\": \"imdbid\", \"as\": \"movie_count\"}], \"groupby\": [\"country\"]}, {\"filter\": \"(datum.movie_count > 50)\"}]}, {\"mark\": {\"type\": \"text\", \"align\": \"left\", \"baseline\": \"middle\", \"dx\": 3}, \"encoding\": {\"text\": {\"type\": \"quantitative\", \"field\": \"percent_pass\", \"format\": \".2%\"}, \"x\": {\"type\": \"quantitative\", \"axis\": {\"format\": \".0%\"}, \"field\": \"percent_pass\"}, \"y\": {\"type\": \"nominal\", \"field\": \"country\", \"sort\": \"-x\"}}, \"transform\": [{\"joinaggregate\": [{\"op\": \"mean\", \"field\": \"binary_pass\", \"as\": \"percent_pass\"}, {\"op\": \"count\", \"field\": \"imdbid\", \"as\": \"movie_count\"}], \"groupby\": [\"country\"]}, {\"filter\": \"(datum.movie_count > 50)\"}]}], \"data\": {\"url\": \"altair-data-adaf1b006dfb0560e04480300654bc0d.csv\", \"format\": {\"type\": \"csv\"}}, \"title\": {\"text\": [\"Percentage of movies passing the bechdel test by production country\"], \"subtitle\": [\"* Only include countries with more than 50 movies\", \"* Movies with more than one production country have been counted for each country\"], \"color\": \"black\"}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.LayerChart(...)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country_pass = alt.Chart(country_test).mark_bar().transform_joinaggregate(\n",
    "    groupby=[\"country\"],\n",
    "    percent_pass=\"mean(binary_pass)\",\n",
    "    movie_count = \"count(imdbid)\"\n",
    ").transform_filter(\n",
    "    alt.datum.movie_count>50\n",
    ").encode(\n",
    "    y=alt.Y(\"country:N\", sort=\"-x\", title=\"\"),\n",
    "    x=alt.X(\"percent_pass:Q\", title=\"\"),\n",
    ")\n",
    "\n",
    "text2 = alt.Chart(country_test).mark_text(align='left',baseline='middle',dx=3).transform_joinaggregate(\n",
    "    groupby=[\"country\"],\n",
    "    percent_pass=\"mean(binary_pass)\",\n",
    "    movie_count = \"count(imdbid)\"\n",
    ").transform_filter(\n",
    "    alt.datum.movie_count>50\n",
    ").encode(\n",
    "    y=alt.Y(\"country:N\", sort=\"-x\"),\n",
    "    x=alt.X(\"percent_pass:Q\", axis=alt.Axis(format='.0%')),\n",
    "    text=alt.Text(\"percent_pass:Q\", format=\".2%\")\n",
    ")\n",
    "\n",
    "country_pass_bar = (country_pass + text2).properties(title={\n",
    "      \"text\": [\"Percentage of movies passing the bechdel test by production country\"],\n",
    "      \"subtitle\": [\"* Only include countries with more than 50 movies\",\"* Movies with more than one production country have been counted for each country\"],\n",
    "      \"color\": \"black\"\n",
    "    })\n",
    "(country_pass_bar).configure_title(fontSize=20,\n",
    "                       anchor=\"start\").configure_axis(\n",
    "    grid=False\n",
    ").configure_view(\n",
    "    strokeWidth=0\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Q2: percentage of movies passing the test by genre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "genre_test = bech_movie[[\"imdbid\", \"genre\", \"binary_pass\"]]\n",
    "#genre_test = genre_test.drop_duplicates()\n",
    "#genre_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>genre</th>\n",
       "      <th>number of movies</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Drama</td>\n",
       "      <td>22284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Comedy</td>\n",
       "      <td>12194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Action</td>\n",
       "      <td>9810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Adventure</td>\n",
       "      <td>8756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Romance</td>\n",
       "      <td>6513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Thriller</td>\n",
       "      <td>5994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Crime</td>\n",
       "      <td>5612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Horror</td>\n",
       "      <td>3510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Mystery</td>\n",
       "      <td>3473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Fantasy</td>\n",
       "      <td>3234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Sci-Fi</td>\n",
       "      <td>2934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Biography</td>\n",
       "      <td>2835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Animation</td>\n",
       "      <td>2680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Family</td>\n",
       "      <td>1993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>History</td>\n",
       "      <td>1892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>War</td>\n",
       "      <td>1302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Music</td>\n",
       "      <td>1053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Musical</td>\n",
       "      <td>737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Western</td>\n",
       "      <td>346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Sport</td>\n",
       "      <td>330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Film-Noir</td>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        genre  number of movies\n",
       "0       Drama             22284\n",
       "1      Comedy             12194\n",
       "2      Action              9810\n",
       "3   Adventure              8756\n",
       "4     Romance              6513\n",
       "5    Thriller              5994\n",
       "6       Crime              5612\n",
       "7      Horror              3510\n",
       "8     Mystery              3473\n",
       "9     Fantasy              3234\n",
       "10     Sci-Fi              2934\n",
       "11  Biography              2835\n",
       "12  Animation              2680\n",
       "13     Family              1993\n",
       "14    History              1892\n",
       "15        War              1302\n",
       "16      Music              1053\n",
       "17    Musical               737\n",
       "18    Western               346\n",
       "19      Sport               330\n",
       "20  Film-Noir               177"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "genre_num = genre_test.groupby([\"genre\"]).count()[\"imdbid\"].reset_index()\n",
    "genre_num.columns = [\"genre\", \"number of movies\"]\n",
    "genre_num.sort_values(by=[\"number of movies\"],ascending=False).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div id=\"altair-viz-b901b937a4174f7e906318f8a7d6c058\"></div>\n",
       "<script type=\"text/javascript\">\n",
       "  (function(spec, embedOpt){\n",
       "    let outputDiv = document.currentScript.previousElementSibling;\n",
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       "      outputDiv = document.getElementById(\"altair-viz-b901b937a4174f7e906318f8a7d6c058\");\n",
       "    }\n",
       "    const paths = {\n",
       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
       "    };\n",
       "\n",
       "    function loadScript(lib) {\n",
       "      return new Promise(function(resolve, reject) {\n",
       "        var s = document.createElement('script');\n",
       "        s.src = paths[lib];\n",
       "        s.async = true;\n",
       "        s.onload = () => resolve(paths[lib]);\n",
       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      });\n",
       "    }\n",
       "\n",
       "    function showError(err) {\n",
       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
       "      throw err;\n",
       "    }\n",
       "\n",
       "    function displayChart(vegaEmbed) {\n",
       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
       "    }\n",
       "\n",
       "    if(typeof define === \"function\" && define.amd) {\n",
       "      requirejs.config({paths});\n",
       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
       "    } else if (typeof vegaEmbed === \"function\") {\n",
       "      displayChart(vegaEmbed);\n",
       "    } else {\n",
       "      loadScript(\"vega\")\n",
       "        .then(() => loadScript(\"vega-lite\"))\n",
       "        .then(() => loadScript(\"vega-embed\"))\n",
       "        .catch(showError)\n",
       "        .then(() => displayChart(vegaEmbed));\n",
       "    }\n",
       "  })({\"usermeta\": {\"embedOptions\": {\"theme\": \"fivethirtyeight\"}}, \"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300, \"strokeWidth\": 0}, \"axis\": {\"grid\": false}, \"title\": {\"anchor\": \"start\", \"fontSize\": 20}}, \"layer\": [{\"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"field\": \"percent_pass\", \"title\": \"\"}, \"y\": {\"type\": \"nominal\", \"field\": \"genre\", \"sort\": \"-x\", \"title\": \"\"}}, \"transform\": [{\"joinaggregate\": [{\"op\": \"mean\", \"field\": \"binary_pass\", \"as\": \"percent_pass\"}], \"groupby\": [\"genre\"]}]}, {\"mark\": {\"type\": \"text\", \"align\": \"left\", \"baseline\": \"middle\", \"dx\": 3}, \"encoding\": {\"text\": {\"type\": \"quantitative\", \"field\": \"percent_pass\", \"format\": \".2%\"}, \"x\": {\"type\": \"quantitative\", \"axis\": {\"format\": \".0%\"}, \"field\": \"percent_pass\"}, \"y\": {\"type\": \"nominal\", \"field\": \"genre\", \"sort\": \"-x\"}}, \"transform\": [{\"joinaggregate\": [{\"op\": \"mean\", \"field\": \"binary_pass\", \"as\": \"percent_pass\"}], \"groupby\": [\"genre\"]}]}], \"data\": {\"url\": \"altair-data-384669da5cdf10d508c6a739a14b8abe.csv\", \"format\": {\"type\": \"csv\"}}, \"title\": {\"text\": [\"Percentage of movies passing the bechdel test by genre\"], \"subtitle\": [\"* Movies with more than one genre have been counted for each genre\"], \"color\": \"black\"}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.LayerChart(...)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "genre_pass = alt.Chart(genre_test).mark_bar().transform_joinaggregate(\n",
    "    groupby=[\"genre\"],\n",
    "    percent_pass=\"mean(binary_pass)\"\n",
    ").encode(\n",
    "    y=alt.Y(\"genre:N\", sort=\"-x\", title=\"\"),\n",
    "    x=alt.X(\"percent_pass:Q\", title=\"\")\n",
    ")\n",
    "\n",
    "text2 = alt.Chart(genre_test).mark_text(align='left',baseline='middle',dx=3).transform_joinaggregate(\n",
    "    groupby=[\"genre\"],\n",
    "    percent_pass=\"mean(binary_pass)\"\n",
    ").encode(\n",
    "    y=alt.Y(\"genre:N\", sort=\"-x\"),\n",
    "    x=alt.X(\"percent_pass:Q\", axis=alt.Axis(format='.0%')),\n",
    "    text=alt.Text(\"percent_pass:Q\", format=\".2%\")\n",
    ")\n",
    "\n",
    "genre_pass_bar = (genre_pass + text2).properties(title={\n",
    "      \"text\": [\"Percentage of movies passing the bechdel test by genre\"],\n",
    "      \"subtitle\": [\"* Movies with more than one genre have been counted for each genre\"],\n",
    "      \"color\": \"black\"\n",
    "    })\n",
    "(genre_pass_bar).configure_title(fontSize=20,\n",
    "                       anchor=\"start\").configure_axis(\n",
    "    grid=False\n",
    ").configure_view(\n",
    "    strokeWidth=0\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Q3: percentage of movies passing the test by IMDb rating"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rating_test = bech_movie[[\"imdbid\", \"avg_vote\", \"total_votes\",\"males_allages_avg_vote\", \"females_allages_avg_vote\", \"binary_pass\"]]\n",
    "rating_test = rating_test.drop_duplicates()\n",
    "rating_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bin=[0,4,5,6,7,8,9,10]\n",
    "rating_test['imdb_star'] = pd.cut(rating_test['avg_vote'], bin,\n",
    "                              labels=['less than 4⭐️', '4⭐️', '5⭐️','6⭐️', '7⭐️', '8⭐️', '9⭐️'])\n",
    "rating_test['imdb_star_male'] = pd.cut(rating_test['males_allages_avg_vote'], bin,\n",
    "                              labels=['less than 4⭐️', '4⭐️', '5⭐️','6⭐️', '7⭐️', '8⭐️', '9⭐️'])\n",
    "\n",
    "rating_test['imdb_star_female'] = pd.cut(rating_test['females_allages_avg_vote'], bin,\n",
    "                              labels=['less than 4⭐️', '4⭐️', '5⭐️','6⭐️', '7⭐️', '8⭐️', '9⭐️'])\n",
    "\n",
    "rating_test.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rating_num = rating_test.groupby(\"imdb_star\").count()[\"imdbid\"].reset_index()\n",
    "rating_num.columns=[\"imdb rating\", \"number of vote\"]\n",
    "rating_num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rating_num_m = rating_test.groupby(\"imdb_star_male\").count()[\"imdbid\"].reset_index()\n",
    "rating_num_m.columns = [\"imdb rating by male\", \"number of vote\"]\n",
    "rating_num_m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rating_num_f = rating_test.groupby(\"imdb_star\").count()[\"imdbid\"].reset_index()\n",
    "rating_num_f.columns = [\"imdb rating by male\", \"number of vote\"]\n",
    "rating_num_f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rating_pass = alt.Chart(rating_test).mark_bar().transform_joinaggregate(\n",
    "    groupby=[\"imdb_star\"],\n",
    "    percent_pass=\"mean(binary_pass)\"\n",
    ").encode(\n",
    "    y=alt.Y(\"imdb_star:N\", title=\"\", sort=[\"less than 4⭐️\", \n",
    "                                                          \"4⭐️\",\n",
    "                                                          \"5⭐️\",\n",
    "                                                          \"6⭐️\",\n",
    "                                                          \"7⭐️\",\n",
    "                                                          \"8⭐️\"]),\n",
    "    x=alt.X(\"percent_pass:Q\", title=\"\")\n",
    ").transform_filter(\n",
    "    alt.FieldOneOfPredicate(field = 'imdb_star', oneOf = [\"less than 4⭐️\", \n",
    "                                                          \"4⭐️\",\n",
    "                                                          \"5⭐️\",\n",
    "                                                          \"6⭐️\",\n",
    "                                                          \"7⭐️\",\n",
    "                                                          \"8⭐️\"]))\n",
    "\n",
    "\n",
    "text3 = alt.Chart(rating_test).mark_text(align='left',baseline='middle',dx=3).transform_joinaggregate(\n",
    "    groupby=[\"imdb_star\"],\n",
    "    percent_pass=\"mean(binary_pass)\"\n",
    ").encode(\n",
    "    y=alt.Y(\"imdb_star:N\", title=\"\", sort=[\"less than 4⭐️\", \n",
    "                                                          \"4⭐️\",\n",
    "                                                          \"5⭐️\",\n",
    "                                                          \"6⭐️\",\n",
    "                                                          \"7⭐️\",\n",
    "                                                          \"8⭐️\"]),\n",
    "    x=alt.X(\"percent_pass:Q\", title=\"\", axis=alt.Axis(format='.0%')),\n",
    "    text=alt.Text(\"percent_pass:Q\", format=\".2%\")\n",
    ").transform_filter(\n",
    "    alt.FieldOneOfPredicate(field = 'imdb_star', oneOf = [\"less than 4⭐️\", \n",
    "                                                          \"4⭐️\",\n",
    "                                                          \"5⭐️\",\n",
    "                                                          \"6⭐️\",\n",
    "                                                          \"7⭐️\",\n",
    "                                                          \"8⭐️\"]))\n",
    "\n",
    "rating_pass_bar = (rating_pass + text3).properties(title={\n",
    "      \"text\": [\"Percentage of movies passing the bechdel test by IMDb rating\"],\n",
    "      \"subtitle\": [\"* Combine 1-3 stars to be 'less than 4 star'\",\"* Movies with more than 9 stars have been excluded due to extremely small amount of data\"],\n",
    "      \"color\": \"black\"\n",
    "    })\n",
    "(rating_pass_bar).configure_title(fontSize=20,\n",
    "                       anchor=\"start\").configure_axis(\n",
    "    grid=False\n",
    ").configure_view(\n",
    "    strokeWidth=0\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# male\n",
    "rating_pass_male = alt.Chart(rating_test).mark_bar().transform_joinaggregate(\n",
    "    groupby=[\"imdb_star_male\"],\n",
    "    percent_pass=\"mean(binary_pass)\"\n",
    ").encode(\n",
    "    y=alt.Y(\"imdb_star_male:N\", title=\"\", sort=[\"less than 4⭐️\", \n",
    "                                                          \"4⭐️\",\n",
    "                                                          \"5⭐️\",\n",
    "                                                          \"6⭐️\",\n",
    "                                                          \"7⭐️\",\n",
    "                                                          \"8⭐️\"]),\n",
    "    x=alt.X(\"percent_pass:Q\", title=\"\")\n",
    ").transform_filter(\n",
    "    alt.FieldOneOfPredicate(field = 'imdb_star_male', oneOf = [\"less than 4⭐️\", \n",
    "                                                          \"4⭐️\",\n",
    "                                                          \"5⭐️\",\n",
    "                                                          \"6⭐️\",\n",
    "                                                          \"7⭐️\",\n",
    "                                                          \"8⭐️\"]))\n",
    "\n",
    "\n",
    "text3_male = alt.Chart(rating_test).mark_text(align='left',baseline='middle',dx=3).transform_joinaggregate(\n",
    "    groupby=[\"imdb_star_male\"],\n",
    "    percent_pass=\"mean(binary_pass)\"\n",
    ").encode(\n",
    "    y=alt.Y(\"imdb_star_male:N\", title=\"\", sort=[\"less than 4⭐️\", \n",
    "                                                          \"4⭐️\",\n",
    "                                                          \"5⭐️\",\n",
    "                                                          \"6⭐️\",\n",
    "                                                          \"7⭐️\",\n",
    "                                                          \"8⭐️\"]),\n",
    "    x=alt.X(\"percent_pass:Q\", title=\"\", axis=alt.Axis(format='.0%')),\n",
    "    text=alt.Text(\"percent_pass:Q\", format=\".2%\")\n",
    ").transform_filter(\n",
    "    alt.FieldOneOfPredicate(field = 'imdb_star_male', oneOf = [\"less than 4⭐️\", \n",
    "                                                          \"4⭐️\",\n",
    "                                                          \"5⭐️\",\n",
    "                                                          \"6⭐️\",\n",
    "                                                          \"7⭐️\",\n",
    "                                                          \"8⭐️\"]))\n",
    "\n",
    "rating_pass_bar_male = (rating_pass_male + text3_male).properties(title={\n",
    "      \"text\": [\"Male Voter\"],\n",
    "      #\"subtitle\": [\"* Combine 1-3 stars to be 'less than 4 star'\",\"* Movies with more than 9 stars have been excluded due to extremely small amount of data\"],\n",
    "      \"color\": \"black\"\n",
    "    })\n",
    "(rating_pass_bar_male).configure_title(fontSize=15)\n",
    "\n",
    "# female\n",
    "rating_pass_female = alt.Chart(rating_test).mark_bar(color=\"orange\").transform_joinaggregate(\n",
    "    groupby=[\"imdb_star_female\"],\n",
    "    percent_pass=\"mean(binary_pass)\"\n",
    ").encode(\n",
    "    y=alt.Y(\"imdb_star_female:N\", title=\"\", sort=[\"less than 4⭐️\", \n",
    "                                                          \"4⭐️\",\n",
    "                                                          \"5⭐️\",\n",
    "                                                          \"6⭐️\",\n",
    "                                                          \"7⭐️\",\n",
    "                                                          \"8⭐️\"]),\n",
    "    x=alt.X(\"percent_pass:Q\", title=\"\")\n",
    ").transform_filter(\n",
    "    alt.FieldOneOfPredicate(field = 'imdb_star_female', oneOf = [\"less than 4⭐️\", \n",
    "                                                          \"4⭐️\",\n",
    "                                                          \"5⭐️\",\n",
    "                                                          \"6⭐️\",\n",
    "                                                          \"7⭐️\",\n",
    "                                                          \"8⭐️\"]))\n",
    "\n",
    "\n",
    "text3_female = alt.Chart(rating_test).mark_text(align='left',baseline='middle',dx=3).transform_joinaggregate(\n",
    "    groupby=[\"imdb_star_female\"],\n",
    "    percent_pass=\"mean(binary_pass)\"\n",
    ").encode(\n",
    "    y=alt.Y(\"imdb_star_female:N\", title=\"\", sort=[\"less than 4⭐️\", \n",
    "                                                          \"4⭐️\",\n",
    "                                                          \"5⭐️\",\n",
    "                                                          \"6⭐️\",\n",
    "                                                          \"7⭐️\",\n",
    "                                                          \"8⭐️\"]),\n",
    "    x=alt.X(\"percent_pass:Q\", title=\"\", axis=alt.Axis(format='.0%')),\n",
    "    text=alt.Text(\"percent_pass:Q\", format=\".2%\")\n",
    ").transform_filter(\n",
    "    alt.FieldOneOfPredicate(field = 'imdb_star_female', oneOf = [\"less than 4⭐️\", \n",
    "                                                          \"4⭐️\",\n",
    "                                                          \"5⭐️\",\n",
    "                                                          \"6⭐️\",\n",
    "                                                          \"7⭐️\",\n",
    "                                                          \"8⭐️\"]))\n",
    "\n",
    "rating_pass_bar_female = (rating_pass_female + text3_female).properties(title={\n",
    "      \"text\": [\"Female voter\"],\n",
    "      #\"subtitle\": [\"* Combine 1-3 stars to be 'less than 4 star'\",\"* Movies with more than 9 stars have been excluded due to extremely small amount of data\"],\n",
    "      \"color\": \"black\"\n",
    "    })\n",
    "(rating_pass_bar_female).configure_title(fontSize=15)\n",
    "\n",
    "(rating_pass_bar_male | rating_pass_bar_female).configure_title(fontSize=15).configure_axis(\n",
    "    grid=False\n",
    ").configure_view(\n",
    "    strokeWidth=0\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Q4: percentage of movies passing the test by crew gender"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "crew_pass = bech_movie[[\"imdbid\", \"director\", \"writer\",\"binary_pass\"]]\n",
    "crew_pass = crew_pass.drop_duplicates()\n",
    "crew_pass.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "new= crew_pass[\"director\"].str.split(\" \", n = 1, expand = True)\n",
    "crew_pass[\"director_name\"]= new[0] \n",
    "\n",
    "new2=crew_pass[\"writer\"].str.split(\" \", n = 1, expand = True)\n",
    "crew_pass[\"writer_name\"]= new2[0] \n",
    "\n",
    "crew_pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels_d=[]\n",
    "labels_w=[]\n",
    "for name in crew_pass[\"director_name\"]:\n",
    "    #print(name)\n",
    "    label = gp.predict(name)[1]\n",
    "    labels_d.append(label)\n",
    "for name in crew_pass[\"writer_name\"]:\n",
    "    label=gp.predict(name)[1]\n",
    "    labels_w.append(label)\n",
    "crew_pass[\"director_gender\"] = labels_d\n",
    "crew_pass[\"writer_gender\"] = labels_w"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# director gender & movie count\n",
    "dir_num = crew_pass.groupby(\"director_gender\").count()[\"imdbid\"].reset_index()\n",
    "dir_num.columns=[\"director gender\", \"number of movies\"]\n",
    "dir_num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# writer gender & movie count\n",
    "wr_num = crew_pass.groupby(\"writer_gender\").count()[\"imdbid\"].reset_index()\n",
    "wr_num.columns=[\"writer gender\", \"number of movies\"]\n",
    "wr_num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# director chart\n",
    "director_test = alt.Chart(crew_pass).mark_bar().transform_filter(\n",
    "    alt.FieldOneOfPredicate(field = 'director_gender', oneOf = [\"M\", \"F\"])\n",
    ").transform_joinaggregate(\n",
    "    groupby=[\"director_gender\"],\n",
    "    percent_pass=\"mean(binary_pass)\"\n",
    ").encode(\n",
    "    y=alt.Y('director_gender:N', sort = [\"M\",\"F\"], title=\"\"),\n",
    "    x=alt.X(\"percent_pass:Q\", title=\"\", axis=alt.Axis(format='.0%'))\n",
    ")\n",
    "\n",
    "text_d = alt.Chart(crew_pass).mark_text(dx=20).transform_filter(\n",
    "    alt.FieldOneOfPredicate(field = 'director_gender', oneOf = [\"M\", \"F\"])\n",
    ").transform_joinaggregate(\n",
    "    groupby=[\"director_gender\"],\n",
    "    percent_pass=\"mean(binary_pass)\"\n",
    ").encode(\n",
    "    y=alt.Y('director_gender:N', sort = [\"M\",\"F\"], title=\"\"),\n",
    "    x=alt.X(\"percent_pass:Q\", title=\"\"),\n",
    "    text=alt.Text(\"percent_pass:Q\", format=\".2%\")\n",
    ")\n",
    "\n",
    "director_chart = (director_test+text_d).properties(title=\"Director\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# writer chart\n",
    "writer_test = alt.Chart(crew_pass).mark_bar(color=\"orange\").transform_filter(\n",
    "    alt.FieldOneOfPredicate(field = 'writer_gender', oneOf = [\"M\", \"F\"])\n",
    ").transform_joinaggregate(\n",
    "    groupby=[\"writer_gender\"],\n",
    "    percent_pass=\"mean(binary_pass)\"\n",
    ").encode(\n",
    "    y=alt.Y('writer_gender:N', sort = [\"M\",\"F\"], title=\"\"),\n",
    "    x=alt.X(\"percent_pass:Q\", title=\"\", axis=alt.Axis(format='.0%'))\n",
    ")\n",
    "\n",
    "text_w = alt.Chart(crew_pass).mark_text(dx=20).transform_filter(\n",
    "    alt.FieldOneOfPredicate(field = 'writer_gender', oneOf = [\"M\", \"F\"])\n",
    ").transform_joinaggregate(\n",
    "    groupby=[\"writer_gender\"],\n",
    "    percent_pass=\"mean(binary_pass)\"\n",
    ").encode(\n",
    "    y=alt.Y('writer_gender:N', sort = [\"M\",\"F\"], title=\"\"),\n",
    "    x=alt.X(\"percent_pass:Q\", title=\"\"),\n",
    "    text=alt.Text(\"percent_pass:Q\", format=\".2%\")\n",
    ")\n",
    "\n",
    "writer_chart = (writer_test+text_w).properties(title={\n",
    "    \"text\":[\"Writer\"]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "(director_chart | writer_chart).properties(title={\n",
    "      \"text\": [\"Percentage of movies passing the bechdel test by crew gender\"],\n",
    "      \"subtitle\": [\"* M:Male\",\"* F:Female\", \"* Movies with multiple crew members have been counted for each crew member\"],\n",
    "      \"color\": \"black\"\n",
    "    }).configure_title(fontSize=20).configure_axis(\n",
    "    grid=False\n",
    ").configure_view(\n",
    "    strokeWidth=0\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Q4: median budget and bechdel test since 1990"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "budget_pass = bech_budget_revenue[[\"adj_budget\", \"test_result\"]]\n",
    "budget_pass.head()\n",
    "#len(budget_pass)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "budget_test = alt.Chart(budget_pass).mark_bar().transform_filter(\n",
    "    alt.datum.adj_budget != None\n",
    ").transform_joinaggregate(\n",
    "    groupby=[\"test_result\"],\n",
    "    median_budget=\"median(adj_budget)\"\n",
    ").encode(\n",
    "    x=alt.X(\"median_budget:Q\", title=\"\"),\n",
    "    y=alt.Y(\"test_result\", sort=\"x\", title=\"\"),\n",
    "    color=alt.condition(\n",
    "    alt.datum.test_result == \"Pass 3:Passes Bechdel Test\",  \n",
    "    alt.value('orange'),     \n",
    "    alt.value('steelblue')   \n",
    ") \n",
    ")\n",
    "\n",
    "text_budget = alt.Chart(budget_pass).mark_text(dx=25).transform_filter(\n",
    "    alt.datum.adj_budget != None\n",
    ").transform_joinaggregate(\n",
    "    groupby=[\"test_result\"],\n",
    "    median_budget=\"median(adj_budget)\"\n",
    ").encode(\n",
    "    x=alt.X(\"median_budget:Q\"),\n",
    "    y=alt.Y(\"test_result\", sort=\"x\"),\n",
    "    text=alt.Text(\"median_budget:Q\", format=\"$.4s\")\n",
    ")\n",
    "\n",
    "(budget_test+text_budget).properties(\n",
    "    title={\n",
    "        \"text\":[\"Median budget and Bechdel test (since 1990)\"],\n",
    "        \"subtitle\":[\"2019 dollar\"]\n",
    "    }\n",
    ").configure_title(anchor=\"start\",fontSize=20).configure_axis(\n",
    "    grid=False\n",
    ").configure_view(\n",
    "    strokeWidth=0\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Q5: median box office and bechdel test since 1990"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#bech_budget_revenue.head()\n",
    "#len(bech_budget_revenue)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dom_box_pass = bech_budget_revenue[[\"adj_domgross\", \"test_result\"]]\n",
    "dom_box_pass.head()\n",
    "# dom_box_pass[\"adj_domgross\"].count() 2118 non-empty adj_domgross"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# domestic\n",
    "dom_test = alt.Chart(dom_box_pass).mark_bar().transform_filter(\n",
    "    alt.datum.adj_domgross != None\n",
    ").transform_joinaggregate(\n",
    "    groupby=[\"test_result\"],\n",
    "    median_revenue=\"median(adj_domgross)\"\n",
    ").encode(\n",
    "    x=alt.X(\"median_revenue:Q\", title=\"\"),\n",
    "    y=alt.Y(\"test_result\", title=\"\"),\n",
    "    color=alt.condition(\n",
    "    alt.datum.test_result == \"Pass 3:Passes Bechdel Test\",  \n",
    "    alt.value('orange'),     \n",
    "    alt.value('steelblue')   \n",
    ")\n",
    ")\n",
    "\n",
    "text_budget = alt.Chart(dom_box_pass).mark_text(dx=25).transform_filter(\n",
    "    alt.datum.adj_domgross != None\n",
    ").transform_joinaggregate(\n",
    "    groupby=[\"test_result\"],\n",
    "    median_revenue=\"median(adj_domgross)\"\n",
    ").encode(\n",
    "    x=alt.X(\"median_revenue:Q\"),\n",
    "    y=alt.Y(\"test_result\"),\n",
    "    text=alt.Text(\"median_revenue:Q\", format=\"$.4s\")\n",
    ")\n",
    "\n",
    "domestic = (dom_test+text_budget).properties(\n",
    "    title={\n",
    "        \"text\":[\"Domestic\"]\n",
    "    }\n",
    ")\n",
    "#domestic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "int_box_pass = bech_budget_revenue[[\"adj_intgross\", \"test_result\"]]\n",
    "int_box_pass.head()\n",
    "#int_box_pass[\"adj_intgross\"].count() 2015 non-empty adj_intgross"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# international\n",
    "int_test = alt.Chart(int_box_pass).mark_bar().transform_filter(\n",
    "    alt.datum.adj_intgross != None\n",
    ").transform_joinaggregate(\n",
    "    groupby=[\"test_result\"],\n",
    "    median_revenue=\"median(adj_intgross)\"\n",
    ").encode(\n",
    "    x=alt.X(\"median_revenue:Q\", title=\"\"),\n",
    "    y=alt.Y(\"test_result\", title=\"\"),\n",
    "    color=alt.condition(\n",
    "    alt.datum.test_result == \"Pass 3:Passes Bechdel Test\",  \n",
    "    alt.value('orange'),     \n",
    "    alt.value('steelblue')   \n",
    "))\n",
    "\n",
    "text_budget_int = alt.Chart(int_box_pass).mark_text(dx=25).transform_filter(\n",
    "    alt.datum.adj_intgross != None\n",
    ").transform_joinaggregate(\n",
    "    groupby=[\"test_result\"],\n",
    "    median_revenue=\"median(adj_intgross)\"\n",
    ").encode(\n",
    "    x=alt.X(\"median_revenue:Q\"),\n",
    "    y=alt.Y(\"test_result\"),\n",
    "    text=alt.Text(\"median_revenue:Q\", format=\"$.4s\")\n",
    ")\n",
    "\n",
    "international = (int_test+text_budget_int).properties(\n",
    "    title={\n",
    "        \"text\":[\"International\"]\n",
    "    }\n",
    ")\n",
    "\n",
    "#international"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "(domestic|international).properties(\n",
    "    title={\n",
    "        \"text\": [\"Median box office and Bechdel Test (since 1990)\"],\n",
    "        \"subtitle\": [\"2019 dollar\"]\n",
    "    }\n",
    ").configure_title(fontSize=20).configure_axis(\n",
    "    grid=False\n",
    ").configure_view(\n",
    "    strokeWidth=0\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ROI\n",
    "dom_roi_pass = bech_budget_revenue[[\"dom_roi\", \"test_result\"]].dropna()\n",
    "#dom_roi_pass.head()\n",
    "len(dom_roi_pass)\n",
    "# dom_roi_pass[\"dom_roi\"].count() 2101 non-empty"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# domestic roi\n",
    "dom_roi_test = alt.Chart(dom_roi_pass).mark_bar().transform_joinaggregate(\n",
    "    groupby=[\"test_result\"],\n",
    "    median_roi=\"median(dom_roi)\"\n",
    ").encode(\n",
    "    x=alt.X(\"median_roi:Q\", title=\"\"),\n",
    "    y=alt.Y(\"test_result\", title=\"\"),\n",
    "    color=alt.condition(\n",
    "    alt.datum.test_result == \"Pass 3:Passes Bechdel Test\",  \n",
    "    alt.value('orange'),     \n",
    "    alt.value('steelblue')   )\n",
    ")\n",
    "\n",
    "text_domroi = alt.Chart(dom_roi_pass).mark_text(dx=15, color=\"black\").transform_joinaggregate(\n",
    "    groupby=[\"test_result\"],\n",
    "    median_roi=\"median(dom_roi)\"\n",
    ").encode(\n",
    "    x=alt.X(\"median_roi:Q\", title=\"\"),\n",
    "    y=alt.Y(\"test_result\", title=\"\"),\n",
    "    text=alt.Text(\"median_roi:Q\", format=\"$.2f\")\n",
    ")\n",
    "\n",
    "dom_roi = (dom_roi_test+text_domroi).properties(\n",
    "    title={\n",
    "        \"text\":[\"Domestic\"]\n",
    "    }\n",
    ")\n",
    "\n",
    "#dom_roi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "int_roi_pass = bech_budget_revenue[[\"int_roi\", \"test_result\"]].dropna()\n",
    "len(int_roi_pass)\n",
    "#int_roi_pass.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# international roi\n",
    "int_roi_test = alt.Chart(int_roi_pass).mark_bar().transform_joinaggregate(\n",
    "    groupby=[\"test_result\"],\n",
    "    median_roi=\"median(int_roi)\"\n",
    ").encode(\n",
    "    x=alt.X(\"median_roi:Q\", title=\"\"),\n",
    "    y=alt.Y(\"test_result\", title=\"\"),\n",
    "    color=alt.condition(\n",
    "    alt.datum.test_result == \"Pass 3:Passes Bechdel Test\",  \n",
    "    alt.value('orange'),     \n",
    "    alt.value('steelblue')   )\n",
    ")\n",
    "\n",
    "text_introi = alt.Chart(int_roi_pass).mark_text(dx=15, color=\"black\").transform_joinaggregate(\n",
    "    groupby=[\"test_result\"],\n",
    "    median_roi=\"median(int_roi)\"\n",
    ").encode(\n",
    "    x=alt.X(\"median_roi:Q\", title=\"\"),\n",
    "    y=alt.Y(\"test_result\", title=\"\"),\n",
    "    text=alt.Text(\"median_roi:Q\", format=\"$.2f\")\n",
    ")\n",
    "\n",
    "int_roi = (int_roi_test+text_introi).properties(\n",
    "    title={\n",
    "        \"text\":[\"International\"]\n",
    "    }\n",
    ")\n",
    "\n",
    "#int_roi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "(dom_roi | int_roi).properties(\n",
    "    title={\n",
    "        \"text\": [\"Median ROI and Bechdel Test (since 1990)\"],\n",
    "        \"subtitle\": [\"2019 dollar\"]\n",
    "    }\n",
    ").configure_title(fontSize=20).configure_axis(\n",
    "    grid=False\n",
    ").configure_view(\n",
    "    strokeWidth=0\n",
    ")"
   ]
  }
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