PyGal documentation.ipynb

{
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A PyGal documentation by Mukul Pathak. http://mukulpathak.com "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### PyGal Reference Guide\n",
    "Source:\n",
    "    http://www.pygal.org/en/stable/documentation/index.html\n",
    "    \n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "PyGal is a python SVG (Scalable Vector Graphics) Charts Creator. It defines in vector based graphics in XML format. In this document we will use PyGal and see it's various features."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To install PyGal in our systems, we will run the \"pip install pygal\" command on terminal or with an \"!\" on jupyter notebook as shown below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pygal in /Users/mukulpathak/opt/miniconda3/lib/python3.7/site-packages (2.4.0)\r\n"
     ]
    }
   ],
   "source": [
    "!pip install pygal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#We then import pygal and other important packages\n",
    "import pygal\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### First we will run a basic program involving PyGal.\n",
    "## 1. Use of Line Chart\n",
    "Here, I have collected data from PyGal's documentation website showing browser usage in percentage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "line_chart = pygal.Line()        #Calls Line functionality of PyGal\n",
    "line_chart.title = 'Browser usage evolution (in %)'\n",
    "line_chart.x_labels = map(str, range(2002, 2013))\n",
    "line_chart.add('Firefox', [None, None,    0, 16.6,   25,   31, 36.4, 45.5, 46.3, 42.8, 37.1])\n",
    "line_chart.add('Chrome',  [None, None, None, None, None,    0,  3.9, 10.8, 23.8, 35.3])\n",
    "line_chart.add('IE',      [85.8, 84.6, 84.7, 74.5,   66, 58.6, 54.7, 44.8, 36.2, 26.6, 20.1])\n",
    "line_chart.add('Others',  [14.2, 15.4, 15.3,  8.9,    9, 10.4,  8.9,  5.8,  6.7,  6.8,  7.5])\n",
    "line_chart.render_to_file('pic.svg')   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This will create an svg file named \"pic.svg\" in the current directory."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In order to render the visualisations on IPYNB file, we will run the following HTML code which will fetch scripts from Github repos involving jquery.js & tooltips.min.js. And then render the charts on browser."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import display, HTML\n",
    "\n",
    "base_html = \"\"\"\n",
    "<!DOCTYPE html>\n",
    "<html>\n",
    "  <head>\n",
    "  <script type=\"text/javascript\" src=\"http://kozea.github.com/pygal.js/javascripts/svg.jquery.js\"></script>\n",
    "  <script type=\"text/javascript\" src=\"https://kozea.github.io/pygal.js/2.0.x/pygal-tooltips.min.js\"\"></script>\n",
    "  </head>\n",
    "  <body>\n",
    "    <figure>\n",
    "      {rendered_chart}\n",
    "    </figure>\n",
    "  </body>\n",
    "</html>\n",
    "\"\"\"\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we will perform visualisation on 2013 movie database fetched from tmdb. This db has a total of 71 movie entries from 2017 and has 13 columns depicting different details of the movie. We will see those in detail while running the .head() command"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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",
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       "\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>budget</th>\n",
       "      <th>genres</th>\n",
       "      <th>id</th>\n",
       "      <th>keywords</th>\n",
       "      <th>popularity</th>\n",
       "      <th>production_companies</th>\n",
       "      <th>production_countries</th>\n",
       "      <th>release_date</th>\n",
       "      <th>revenue</th>\n",
       "      <th>runtime</th>\n",
       "      <th>title</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>vote_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>15000000</td>\n",
       "      <td>[{\"id\": 53, \"name\": \"Thriller\"}, {\"id\": 878, \"...</td>\n",
       "      <td>333371</td>\n",
       "      <td>[{\"id\": 1930, \"name\": \"kidnapping\"}, {\"id\": 23...</td>\n",
       "      <td>53.698683</td>\n",
       "      <td>[{\"name\": \"Paramount Pictures\", \"id\": 4}, {\"na...</td>\n",
       "      <td>us</td>\n",
       "      <td>3/10/16</td>\n",
       "      <td>108286421</td>\n",
       "      <td>103</td>\n",
       "      <td>10 Cloverfield Lane</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>50000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 18, \"nam...</td>\n",
       "      <td>300671</td>\n",
       "      <td>[{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...</td>\n",
       "      <td>42.526529</td>\n",
       "      <td>[{\"name\": \"Paramount Pictures\", \"id\": 4}, {\"na...</td>\n",
       "      <td>mt</td>\n",
       "      <td>1/13/16</td>\n",
       "      <td>69411370</td>\n",
       "      <td>144</td>\n",
       "      <td>13 Hours: The Secret Soldiers of Benghazi</td>\n",
       "      <td>7.0</td>\n",
       "      <td>938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>4500000</td>\n",
       "      <td>[{\"id\": 53, \"name\": \"Thriller\"}, {\"id\": 28, \"n...</td>\n",
       "      <td>375290</td>\n",
       "      <td>[{\"id\": 2227, \"name\": \"evacuation\"}, {\"id\": 60...</td>\n",
       "      <td>2.551559</td>\n",
       "      <td>[{\"name\": \"T-Series\", \"id\": 3522}, {\"name\": \"H...</td>\n",
       "      <td>in</td>\n",
       "      <td>1/22/16</td>\n",
       "      <td>32000000</td>\n",
       "      <td>126</td>\n",
       "      <td>Airlift</td>\n",
       "      <td>7.3</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>170000000</td>\n",
       "      <td>[{\"id\": 14, \"name\": \"Fantasy\"}]</td>\n",
       "      <td>241259</td>\n",
       "      <td>[{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...</td>\n",
       "      <td>56.268916</td>\n",
       "      <td>[{\"name\": \"Walt Disney Pictures\", \"id\": 2}, {\"...</td>\n",
       "      <td>gb</td>\n",
       "      <td>5/25/16</td>\n",
       "      <td>299370084</td>\n",
       "      <td>113</td>\n",
       "      <td>Alice Through the Looking Glass</td>\n",
       "      <td>6.5</td>\n",
       "      <td>1725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>110000000</td>\n",
       "      <td>[{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 878, ...</td>\n",
       "      <td>262504</td>\n",
       "      <td>[{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...</td>\n",
       "      <td>86.105615</td>\n",
       "      <td>[{\"name\": \"Summit Entertainment\", \"id\": 491}, ...</td>\n",
       "      <td>us</td>\n",
       "      <td>3/9/16</td>\n",
       "      <td>179246868</td>\n",
       "      <td>121</td>\n",
       "      <td>Allegiant</td>\n",
       "      <td>5.9</td>\n",
       "      <td>1998</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "      budget                                             genres      id  \\\n",
       "0   15000000  [{\"id\": 53, \"name\": \"Thriller\"}, {\"id\": 878, \"...  333371   \n",
       "1   50000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 18, \"nam...  300671   \n",
       "2    4500000  [{\"id\": 53, \"name\": \"Thriller\"}, {\"id\": 28, \"n...  375290   \n",
       "3  170000000                    [{\"id\": 14, \"name\": \"Fantasy\"}]  241259   \n",
       "4  110000000  [{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 878, ...  262504   \n",
       "\n",
       "                                            keywords  popularity  \\\n",
       "0  [{\"id\": 1930, \"name\": \"kidnapping\"}, {\"id\": 23...   53.698683   \n",
       "1  [{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...   42.526529   \n",
       "2  [{\"id\": 2227, \"name\": \"evacuation\"}, {\"id\": 60...    2.551559   \n",
       "3  [{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...   56.268916   \n",
       "4  [{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...   86.105615   \n",
       "\n",
       "                                production_companies production_countries  \\\n",
       "0  [{\"name\": \"Paramount Pictures\", \"id\": 4}, {\"na...                   us   \n",
       "1  [{\"name\": \"Paramount Pictures\", \"id\": 4}, {\"na...                   mt   \n",
       "2  [{\"name\": \"T-Series\", \"id\": 3522}, {\"name\": \"H...                   in   \n",
       "3  [{\"name\": \"Walt Disney Pictures\", \"id\": 2}, {\"...                   gb   \n",
       "4  [{\"name\": \"Summit Entertainment\", \"id\": 491}, ...                   us   \n",
       "\n",
       "  release_date    revenue  runtime                                      title  \\\n",
       "0      3/10/16  108286421      103                        10 Cloverfield Lane   \n",
       "1      1/13/16   69411370      144  13 Hours: The Secret Soldiers of Benghazi   \n",
       "2      1/22/16   32000000      126                                    Airlift   \n",
       "3      5/25/16  299370084      113            Alice Through the Looking Glass   \n",
       "4       3/9/16  179246868      121                                  Allegiant   \n",
       "\n",
       "   vote_average  vote_count  \n",
       "0           6.8        2468  \n",
       "1           7.0         938  \n",
       "2           7.3          57  \n",
       "3           6.5        1725  \n",
       "4           5.9        1998  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tmdb = pd.read_csv(\"tmdb.csv\")  # Load the dataset\n",
    "tmdb.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Using PyGal bar graph, we will first find top 10 movies with highest budget.\n",
    "## 2. Use of Bar Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title\n",
       "10 Cloverfield Lane                           15000000\n",
       "13 Hours: The Secret Soldiers of Benghazi     50000000\n",
       "Airlift                                        4500000\n",
       "Alice Through the Looking Glass              170000000\n",
       "Allegiant                                    110000000\n",
       "Bad Moms                                      20000000\n",
       "Batman v Superman: Dawn of Justice           250000000\n",
       "Ben-Hur                                      100000000\n",
       "Captain America: Civil War                   250000000\n",
       "Central Intelligence                          50000000\n",
       "Name: budget, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Mobudget=tmdb.groupby('title')['budget'].mean()\n",
    "Mobudget.head(10)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 7,
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height=\"12\" width=\"12\" x=\"0.0\" y=\"1009.0\" /><text x=\"17.0\" y=\"1019.2\">The Angry Bird…</text><title>The Angry Birds Movie</title></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-49\"><rect class=\"color-49 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1030.0\" /><text x=\"17.0\" y=\"1040.2\">The BFG</text></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-50\"><rect class=\"color-50 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1051.0\" /><text x=\"17.0\" y=\"1061.2\">The Birth of a…</text><title>The Birth of a Nation</title></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-51\"><rect class=\"color-51 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1072.0\" /><text x=\"17.0\" y=\"1082.2\">The Boss</text></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-52\"><rect class=\"color-52 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1093.0\" /><text x=\"17.0\" y=\"1103.2\">The Boy</text></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-53\"><rect class=\"color-53 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1114.0\" /><text x=\"17.0\" y=\"1124.2\">The Conjuring 2</text></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-54\"><rect class=\"color-54 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1135.0\" /><text x=\"17.0\" y=\"1145.2\">The Finest Hou…</text><title>The Finest Hours</title></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-55\"><rect class=\"color-55 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1156.0\" /><text x=\"17.0\" y=\"1166.2\">The Forest</text></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-56\"><rect class=\"color-56 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1177.0\" /><text x=\"17.0\" y=\"1187.2\">The Huntsman: …</text><title>The Huntsman: Winter's War</title></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-57\"><rect class=\"color-57 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1198.0\" /><text x=\"17.0\" y=\"1208.2\">The Infiltrator</text></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-58\"><rect class=\"color-58 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1219.0\" /><text x=\"17.0\" y=\"1229.2\">The Jungle Book</text></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-59\"><rect class=\"color-59 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1240.0\" /><text x=\"17.0\" y=\"1250.2\">The Legend of …</text><title>The Legend of Tarzan</title></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-60\"><rect class=\"color-60 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1261.0\" /><text x=\"17.0\" y=\"1271.2\">The Monkey Kin…</text><title>The Monkey King 2</title></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-61\"><rect class=\"color-61 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1282.0\" /><text x=\"17.0\" y=\"1292.2\">The Neon Demon</text></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-62\"><rect class=\"color-62 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1303.0\" /><text x=\"17.0\" y=\"1313.2\">The Purge: Ele…</text><title>The Purge: Election Year</title></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-63\"><rect class=\"color-63 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1324.0\" /><text x=\"17.0\" y=\"1334.2\">The Secret Lif…</text><title>The Secret Life of Pets</title></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-64\"><rect class=\"color-64 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1345.0\" /><text x=\"17.0\" y=\"1355.2\">The Shallows</text></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-65\"><rect class=\"color-65 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1366.0\" /><text x=\"17.0\" y=\"1376.2\">The Witch</text></g><g class=\"legend reactive 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x=\"0.0\" y=\"1471.0\" /><text x=\"17.0\" y=\"1481.2\">Zoolander 2</text></g></g><g class=\"legends\" transform=\"translate(790, 30)\" /></g></svg>\n",
       "    </figure>\n",
       "  </body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bar_chart = pygal.Bar(height=400)\n",
    "[bar_chart.add(x[0], x[1]) for x in Mobudget.items()]\n",
    "display(HTML(base_html.format(rendered_chart=bar_chart.render(is_unicode=True))))  #This line will render the graphs on our IPYNB file itself\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### We will create a popularity chart depicting popularity of the movie.\n",
    "## 3. Use of Treemap/Area chart\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title\n",
       "10 Cloverfield Lane                          [53.698682999999996]\n",
       "13 Hours: The Secret Soldiers of Benghazi             [42.526529]\n",
       "Airlift                                                [2.551559]\n",
       "Alice Through the Looking Glass              [56.268916000000004]\n",
       "Allegiant                                             [86.105615]\n",
       "                                                     ...         \n",
       "The Young Messiah                            [1.8845580000000002]\n",
       "Triple 9                                              [29.371987]\n",
       "Warcraft                                              [63.148529]\n",
       "X-Men: Apocalypse                                    [139.272042]\n",
       "Zoolander 2                                           [37.253774]\n",
       "Name: popularity, Length: 71, dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "popularityChart = tmdb.groupby(['title'])['popularity'].apply(list) #convert all the movies into a lit form by grouping popularity & title\n",
    "popularityChart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<!DOCTYPE html>\n",
       "<html>\n",
       "  <head>\n",
       "  <script type=\"text/javascript\" src=\"http://kozea.github.com/pygal.js/javascripts/svg.jquery.js\"></script>\n",
       "  <script type=\"text/javascript\" src=\"https://kozea.github.io/pygal.js/2.0.x/pygal-tooltips.min.js\"\"></script>\n",
       "  </head>\n",
       "  <body>\n",
       "    <figure>\n",
       "      <?xml version='1.0' encoding='utf-8'?>\n",
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       "    </figure>\n",
       "  </body>\n",
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       "<IPython.core.display.HTML object>"
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   "source": [
    "treemap = pygal.Treemap(height=300)    #calling the treemap functionality\n",
    "[treemap.add(x[0], x[1]) for x in popularityChart.items()] #fetching all the inputs from the dataframe\n",
    "display(HTML(base_html.format(rendered_chart=treemap.render(is_unicode=True)))) #Running the same on ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### We will now see performances of each movies on gauge charts\n",
    "## 4. Use of Gauge Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "ratings=tmdb.groupby('title')['vote_average'].mean()  #grouping title with vote average"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "    </figure>\n",
       "  </body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gauge = pygal.SolidGauge(inner_radius=0.70) #creating a gauge with radius 0.7\n",
    "[gauge.add(x[0], [{\"value\" : x[1] * 10}] ) for x in ratings.iteritems()] #fetching values from df and getting scores out of 100.\n",
    "display(HTML(base_html.format(rendered_chart=gauge.render(is_unicode=True)))) #running the command"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Alternatively,\n",
    "we can also assemble all the gauge charts into one and create a different type of Gauge chart.\n",
    "Let's do the alternative."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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/><text x=\"17.0\" y=\"935.2\">Star Trek Beyo…</text><title>Star Trek Beyond</title></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-45\"><rect class=\"color-45 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"946.0\" /><text x=\"17.0\" y=\"956.2\">Suicide Squad</text></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-46\"><rect class=\"color-46 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"967.0\" /><text x=\"17.0\" y=\"977.2\">Teenage Mutant…</text><title>Teenage Mutant Ninja Turtles: Out of the Shadows</title></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-47\"><rect class=\"color-47 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"988.0\" /><text x=\"17.0\" y=\"998.2\">The 5th Wave</text></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-48\"><rect class=\"color-48 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1009.0\" /><text x=\"17.0\" y=\"1019.2\">The Angry Bird…</text><title>The Angry 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Infiltrator</text></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-58\"><rect class=\"color-58 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1219.0\" /><text x=\"17.0\" y=\"1229.2\">The Jungle Book</text></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-59\"><rect class=\"color-59 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1240.0\" /><text x=\"17.0\" y=\"1250.2\">The Legend of …</text><title>The Legend of Tarzan</title></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-60\"><rect class=\"color-60 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1261.0\" /><text x=\"17.0\" y=\"1271.2\">The Monkey Kin…</text><title>The Monkey King 2</title></g><g class=\"legend reactive activate-serie\" id=\"activate-serie-61\"><rect class=\"color-61 reactive\" height=\"12\" width=\"12\" x=\"0.0\" y=\"1282.0\" /><text x=\"17.0\" y=\"1292.2\">The Neon Demon</text></g><g class=\"legend reactive activate-serie\" 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transform=\"translate(790, 30)\" /></g></svg>\n",
       "    </figure>\n",
       "  </body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gauge = pygal.Gauge(human_readable=True) #calling gauge with human readable form\n",
    "[gauge.add(x[0], [{\"value\" : x[1] }] ) for x in ratings.iteritems()] #getting values out of 10 this time. See, no multiplication with 10\n",
    "display(HTML(base_html.format(rendered_chart=gauge.render(is_unicode=True))))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### We will now show a map with movie production countries and counts on it.\n",
    "### 5. Use of World Map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For setup, we will run the pip command below to install from the file itself."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing /Users/mukulpathak/Library/Caches/pip/wheels/54/e6/11/5be0d3206bdc0ea8f0fcf1fe32661d7e614863c8b6a22655ae/pygal_maps_world-1.0.2-py3-none-any.whl\n",
      "Requirement already satisfied: pygal>=1.9.9 in /Users/mukulpathak/opt/miniconda3/lib/python3.7/site-packages (from pygal.maps.world) (2.4.0)\n",
      "Installing collected packages: pygal.maps.world\n",
      "Successfully installed pygal.maps.world\n"
     ]
    }
   ],
   "source": [
    "!pip install pygal.maps.world\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "releaseCou=tmdb['production_countries'].value_counts() #get counts for each location"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "us    44\n",
       "ca     7\n",
       "gb     6\n",
       "cn     3\n",
       "in     2\n",
       "hk     1\n",
       "fl     1\n",
       "dk     1\n",
       "fr     1\n",
       "bg     1\n",
       "de     1\n",
       "mt     1\n",
       "jp     1\n",
       "au     1\n",
       "Name: production_countries, dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "releaseCou"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "NOTE : PyGal will plot locations when countries are stored in the country code format. You can learn about the country codes for each country from the official website : http://www.pygal.org/en/stable/documentation/types/maps/pygal_maps_world.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'us': 44,\n",
       " 'ca': 7,\n",
       " 'gb': 6,\n",
       " 'cn': 3,\n",
       " 'in': 2,\n",
       " 'hk': 1,\n",
       " 'fl': 1,\n",
       " 'dk': 1,\n",
       " 'fr': 1,\n",
       " 'bg': 1,\n",
       " 'de': 1,\n",
       " 'mt': 1,\n",
       " 'jp': 1,\n",
       " 'au': 1}"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Convert Series into dictionary, PyGal works with dictionaries when it comes to maps. \n",
    "dictLoc = releaseCou.to_dict() \n",
    "dictLoc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pygal_maps_world.maps import World #import the world maps file from World package for PyGal\n",
    "\n",
    "wm1= World() #store World() parameter in wm1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "wm1.force_uri_protocol = 'http'\n",
    "wm1.title=\"Map of primary movie production location\"\n",
    "wm1.add('In 2017', dictLoc)  #pass the series to the map\n",
    "\n",
    "wm1.render_to_file('map.svg') #Since, the map won't be visible on the IPYNB file,store it locally on an SVG file.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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