GapMinderEDA.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Gap Minder EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this notebook, you will explore the [Gapminder](https://www.gapminder.org/) dataset. This dataset became popular in a series of TED talks by [Hans Rosling](https://www.ted.com/speakers/hans_rosling). For this notebook we will use the cleaned version of this dataset provided by Jenny Bryan [here](https://github.com/jennybc/gapminder)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
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   "execution_count": 1,
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   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import altair as alt\n",
    "alt.enable_mime_rendering()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load the cleaned dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
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   },
   "outputs": [],
   "source": [
    "data = pd.read_csv('/data/gapminder/gapminder.tsv', sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
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     "locked": true,
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   "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>country</th>\n",
       "      <th>continent</th>\n",
       "      <th>year</th>\n",
       "      <th>lifeExp</th>\n",
       "      <th>pop</th>\n",
       "      <th>gdpPercap</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1952</td>\n",
       "      <td>28.801</td>\n",
       "      <td>8425333</td>\n",
       "      <td>779.445314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1957</td>\n",
       "      <td>30.332</td>\n",
       "      <td>9240934</td>\n",
       "      <td>820.853030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1962</td>\n",
       "      <td>31.997</td>\n",
       "      <td>10267083</td>\n",
       "      <td>853.100710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1967</td>\n",
       "      <td>34.020</td>\n",
       "      <td>11537966</td>\n",
       "      <td>836.197138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1972</td>\n",
       "      <td>36.088</td>\n",
       "      <td>13079460</td>\n",
       "      <td>739.981106</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       country continent  year  lifeExp       pop   gdpPercap\n",
       "0  Afghanistan      Asia  1952   28.801   8425333  779.445314\n",
       "1  Afghanistan      Asia  1957   30.332   9240934  820.853030\n",
       "2  Afghanistan      Asia  1962   31.997  10267083  853.100710\n",
       "3  Afghanistan      Asia  1967   34.020  11537966  836.197138\n",
       "4  Afghanistan      Asia  1972   36.088  13079460  739.981106"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Life expectancy over time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create an `alt.Chart` with Altair to explore life expectancy over time:\n",
    "\n",
    "* Use a line mark.\n",
    "* Encode `year` as the x position with a `timeUnit` of `year`.\n",
    "* Encode the `mean` of `lifeExp` as the y position.\n",
    "* Encode `continent` as the color with a nominal datatype."
   ]
  },
  {
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     "points": 4,
     "schema_version": 1,
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",
      "text/plain": [
       "<altair.VegaLite object>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# YOUR CODE HERE\n",
    "alt.Chart(data).mark_line().encode(\n",
    "    alt.X(\"year:T\", timeUnit = \"year\"),\n",
    "    alt.Y(\"mean(lifeExp):Q\"),\n",
    "    alt.Color(\"continent:N\")\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filter years"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Show the unique values in the `year` column:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "deletable": false,
    "nbgrader": {
     "checksum": "1f025210913575de65439785adbe732d",
     "grade": true,
     "grade_id": "cell-e09276022d6711ab",
     "locked": false,
     "points": 2,
     "schema_version": 1,
     "solution": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, 2002,\n",
       "       2007])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['year'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a new `DataFrame` named `first_last` containing only the rows with the first or last years:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "deletable": false,
    "nbgrader": {
     "checksum": "3e49bb1b9dd786a57f9122a25e50be49",
     "grade": false,
     "grade_id": "cell-88434ac189a17cd3",
     "locked": false,
     "schema_version": 1,
     "solution": true
    }
   },
   "outputs": [],
   "source": [
    "first_last = data.loc[(data[\"year\"] == 1952) | (data[\"year\"] == 2007)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "d8f69d2a57eba60489552b0a75f6f27f",
     "grade": false,
     "grade_id": "cell-e4e54d87564e1929",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "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>country</th>\n",
       "      <th>continent</th>\n",
       "      <th>year</th>\n",
       "      <th>lifeExp</th>\n",
       "      <th>pop</th>\n",
       "      <th>gdpPercap</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1952</td>\n",
       "      <td>28.801</td>\n",
       "      <td>8425333</td>\n",
       "      <td>779.445314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Asia</td>\n",
       "      <td>2007</td>\n",
       "      <td>43.828</td>\n",
       "      <td>31889923</td>\n",
       "      <td>974.580338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Albania</td>\n",
       "      <td>Europe</td>\n",
       "      <td>1952</td>\n",
       "      <td>55.230</td>\n",
       "      <td>1282697</td>\n",
       "      <td>1601.056136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Albania</td>\n",
       "      <td>Europe</td>\n",
       "      <td>2007</td>\n",
       "      <td>76.423</td>\n",
       "      <td>3600523</td>\n",
       "      <td>5937.029526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>Africa</td>\n",
       "      <td>1952</td>\n",
       "      <td>43.077</td>\n",
       "      <td>9279525</td>\n",
       "      <td>2449.008185</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        country continent  year  lifeExp       pop    gdpPercap\n",
       "0   Afghanistan      Asia  1952   28.801   8425333   779.445314\n",
       "11  Afghanistan      Asia  2007   43.828  31889923   974.580338\n",
       "12      Albania    Europe  1952   55.230   1282697  1601.056136\n",
       "23      Albania    Europe  2007   76.423   3600523  5937.029526\n",
       "24      Algeria    Africa  1952   43.077   9279525  2449.008185"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "first_last.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "c71bfda2464f10353ede3f2fa9affd4c",
     "grade": true,
     "grade_id": "cell-7f2b781769e3e6c6",
     "locked": true,
     "points": 2,
     "schema_version": 1,
     "solution": false
    }
   },
   "outputs": [],
   "source": [
    "assert len(first_last)==284"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tick chart of life expectancy by continent"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create an `alt.Chart` with Altair to explore the distribution of life expectancy, grouped by continent:\n",
    "\n",
    "* Use the filtered dataset `first_last`.\n",
    "* Use a tick mark.\n",
    "* Encode `lifeExp` as the x position.\n",
    "* Encode `continent` as the y position with a nominal datatype.\n",
    "* Encode `year` as the color with a nominal datatype."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "deletable": false,
    "nbgrader": {
     "checksum": "4a0c2310c81e8ee5af8e6c407a0b87c0",
     "grade": true,
     "grade_id": "cell-c7197115416be5e7",
     "locked": false,
     "points": 4,
     "schema_version": 1,
     "solution": true
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.vegalite.v1+json": {
       "$schema": "https://vega.github.io/schema/vega-lite/v1.2.1.json",
       "data": {
        "values": [
         {
          "continent": "Asia",
          "country": "Afghanistan",
          "gdpPercap": 779.4453145,
          "lifeExp": 28.801,
          "pop": 8425333,
          "year": 1952
         },
         {
          "continent": "Asia",
          "country": "Afghanistan",
          "gdpPercap": 974.5803384,
          "lifeExp": 43.828,
          "pop": 31889923,
          "year": 2007
         },
         {
          "continent": "Europe",
          "country": "Albania",
          "gdpPercap": 1601.056136,
          "lifeExp": 55.23,
          "pop": 1282697,
          "year": 1952
         },
         {
          "continent": "Europe",
          "country": "Albania",
          "gdpPercap": 5937.029525999999,
          "lifeExp": 76.423,
          "pop": 3600523,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Algeria",
          "gdpPercap": 2449.008185,
          "lifeExp": 43.077,
          "pop": 9279525,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Algeria",
          "gdpPercap": 6223.367465,
          "lifeExp": 72.301,
          "pop": 33333216,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Angola",
          "gdpPercap": 3520.610273,
          "lifeExp": 30.015,
          "pop": 4232095,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Angola",
          "gdpPercap": 4797.231267,
          "lifeExp": 42.731,
          "pop": 12420476,
          "year": 2007
         },
         {
          "continent": "Americas",
          "country": "Argentina",
          "gdpPercap": 5911.315053,
          "lifeExp": 62.485,
          "pop": 17876956,
          "year": 1952
         },
         {
          "continent": "Americas",
          "country": "Argentina",
          "gdpPercap": 12779.379640000001,
          "lifeExp": 75.32,
          "pop": 40301927,
          "year": 2007
         },
         {
          "continent": "Oceania",
          "country": "Australia",
          "gdpPercap": 10039.595640000001,
          "lifeExp": 69.12,
          "pop": 8691212,
          "year": 1952
         },
         {
          "continent": "Oceania",
          "country": "Australia",
          "gdpPercap": 34435.367439999995,
          "lifeExp": 81.235,
          "pop": 20434176,
          "year": 2007
         },
         {
          "continent": "Europe",
          "country": "Austria",
          "gdpPercap": 6137.076492,
          "lifeExp": 66.8,
          "pop": 6927772,
          "year": 1952
         },
         {
          "continent": "Europe",
          "country": "Austria",
          "gdpPercap": 36126.4927,
          "lifeExp": 79.829,
          "pop": 8199783,
          "year": 2007
         },
         {
          "continent": "Asia",
          "country": "Bahrain",
          "gdpPercap": 9867.084765000001,
          "lifeExp": 50.93899999999999,
          "pop": 120447,
          "year": 1952
         },
         {
          "continent": "Asia",
          "country": "Bahrain",
          "gdpPercap": 29796.048339999998,
          "lifeExp": 75.635,
          "pop": 708573,
          "year": 2007
         },
         {
          "continent": "Asia",
          "country": "Bangladesh",
          "gdpPercap": 684.2441716,
          "lifeExp": 37.484,
          "pop": 46886859,
          "year": 1952
         },
         {
          "continent": "Asia",
          "country": "Bangladesh",
          "gdpPercap": 1391.253792,
          "lifeExp": 64.062,
          "pop": 150448339,
          "year": 2007
         },
         {
          "continent": "Europe",
          "country": "Belgium",
          "gdpPercap": 8343.105126999999,
          "lifeExp": 68,
          "pop": 8730405,
          "year": 1952
         },
         {
          "continent": "Europe",
          "country": "Belgium",
          "gdpPercap": 33692.60508,
          "lifeExp": 79.441,
          "pop": 10392226,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Benin",
          "gdpPercap": 1062.7522,
          "lifeExp": 38.223,
          "pop": 1738315,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Benin",
          "gdpPercap": 1441.284873,
          "lifeExp": 56.728,
          "pop": 8078314,
          "year": 2007
         },
         {
          "continent": "Americas",
          "country": "Bolivia",
          "gdpPercap": 2677.3263469999997,
          "lifeExp": 40.414,
          "pop": 2883315,
          "year": 1952
         },
         {
          "continent": "Americas",
          "country": "Bolivia",
          "gdpPercap": 3822.1370840000004,
          "lifeExp": 65.554,
          "pop": 9119152,
          "year": 2007
         },
         {
          "continent": "Europe",
          "country": "Bosnia and Herzegovina",
          "gdpPercap": 973.5331947999999,
          "lifeExp": 53.82,
          "pop": 2791000,
          "year": 1952
         },
         {
          "continent": "Europe",
          "country": "Bosnia and Herzegovina",
          "gdpPercap": 7446.298803,
          "lifeExp": 74.852,
          "pop": 4552198,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Botswana",
          "gdpPercap": 851.2411407,
          "lifeExp": 47.622,
          "pop": 442308,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Botswana",
          "gdpPercap": 12569.851770000001,
          "lifeExp": 50.728,
          "pop": 1639131,
          "year": 2007
         },
         {
          "continent": "Americas",
          "country": "Brazil",
          "gdpPercap": 2108.944355,
          "lifeExp": 50.917,
          "pop": 56602560,
          "year": 1952
         },
         {
          "continent": "Americas",
          "country": "Brazil",
          "gdpPercap": 9065.800825,
          "lifeExp": 72.39,
          "pop": 190010647,
          "year": 2007
         },
         {
          "continent": "Europe",
          "country": "Bulgaria",
          "gdpPercap": 2444.2866480000002,
          "lifeExp": 59.6,
          "pop": 7274900,
          "year": 1952
         },
         {
          "continent": "Europe",
          "country": "Bulgaria",
          "gdpPercap": 10680.79282,
          "lifeExp": 73.005,
          "pop": 7322858,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Burkina Faso",
          "gdpPercap": 543.2552413,
          "lifeExp": 31.975,
          "pop": 4469979,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Burkina Faso",
          "gdpPercap": 1217.032994,
          "lifeExp": 52.295,
          "pop": 14326203,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Burundi",
          "gdpPercap": 339.29645869999996,
          "lifeExp": 39.031,
          "pop": 2445618,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Burundi",
          "gdpPercap": 430.07069160000003,
          "lifeExp": 49.58,
          "pop": 8390505,
          "year": 2007
         },
         {
          "continent": "Asia",
          "country": "Cambodia",
          "gdpPercap": 368.46928560000003,
          "lifeExp": 39.417,
          "pop": 4693836,
          "year": 1952
         },
         {
          "continent": "Asia",
          "country": "Cambodia",
          "gdpPercap": 1713.7786859999999,
          "lifeExp": 59.723,
          "pop": 14131858,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Cameroon",
          "gdpPercap": 1172.667655,
          "lifeExp": 38.523,
          "pop": 5009067,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Cameroon",
          "gdpPercap": 2042.0952399999999,
          "lifeExp": 50.43,
          "pop": 17696293,
          "year": 2007
         },
         {
          "continent": "Americas",
          "country": "Canada",
          "gdpPercap": 11367.16112,
          "lifeExp": 68.75,
          "pop": 14785584,
          "year": 1952
         },
         {
          "continent": "Americas",
          "country": "Canada",
          "gdpPercap": 36319.235010000004,
          "lifeExp": 80.653,
          "pop": 33390141,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Central African Republic",
          "gdpPercap": 1071.310713,
          "lifeExp": 35.463,
          "pop": 1291695,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Central African Republic",
          "gdpPercap": 706.016537,
          "lifeExp": 44.74100000000001,
          "pop": 4369038,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Chad",
          "gdpPercap": 1178.665927,
          "lifeExp": 38.092,
          "pop": 2682462,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Chad",
          "gdpPercap": 1704.0637239999999,
          "lifeExp": 50.651,
          "pop": 10238807,
          "year": 2007
         },
         {
          "continent": "Americas",
          "country": "Chile",
          "gdpPercap": 3939.9787890000002,
          "lifeExp": 54.745,
          "pop": 6377619,
          "year": 1952
         },
         {
          "continent": "Americas",
          "country": "Chile",
          "gdpPercap": 13171.63885,
          "lifeExp": 78.553,
          "pop": 16284741,
          "year": 2007
         },
         {
          "continent": "Asia",
          "country": "China",
          "gdpPercap": 400.44861099999997,
          "lifeExp": 44,
          "pop": 556263527,
          "year": 1952
         },
         {
          "continent": "Asia",
          "country": "China",
          "gdpPercap": 4959.1148539999995,
          "lifeExp": 72.961,
          "pop": 1318683096,
          "year": 2007
         },
         {
          "continent": "Americas",
          "country": "Colombia",
          "gdpPercap": 2144.115096,
          "lifeExp": 50.643,
          "pop": 12350771,
          "year": 1952
         },
         {
          "continent": "Americas",
          "country": "Colombia",
          "gdpPercap": 7006.580419,
          "lifeExp": 72.889,
          "pop": 44227550,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Comoros",
          "gdpPercap": 1102.990936,
          "lifeExp": 40.715,
          "pop": 153936,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Comoros",
          "gdpPercap": 986.1478792000001,
          "lifeExp": 65.152,
          "pop": 710960,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Congo, Dem. Rep.",
          "gdpPercap": 780.5423257,
          "lifeExp": 39.143,
          "pop": 14100005,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Congo, Dem. Rep.",
          "gdpPercap": 277.55185869999997,
          "lifeExp": 46.461999999999996,
          "pop": 64606759,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Congo, Rep.",
          "gdpPercap": 2125.621418,
          "lifeExp": 42.111000000000004,
          "pop": 854885,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Congo, Rep.",
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          "lifeExp": 55.321999999999996,
          "pop": 3800610,
          "year": 2007
         },
         {
          "continent": "Americas",
          "country": "Costa Rica",
          "gdpPercap": 2627.0094710000003,
          "lifeExp": 57.206,
          "pop": 926317,
          "year": 1952
         },
         {
          "continent": "Americas",
          "country": "Costa Rica",
          "gdpPercap": 9645.06142,
          "lifeExp": 78.782,
          "pop": 4133884,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Cote d'Ivoire",
          "gdpPercap": 1388.594732,
          "lifeExp": 40.477,
          "pop": 2977019,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Cote d'Ivoire",
          "gdpPercap": 1544.750112,
          "lifeExp": 48.328,
          "pop": 18013409,
          "year": 2007
         },
         {
          "continent": "Europe",
          "country": "Croatia",
          "gdpPercap": 3119.23652,
          "lifeExp": 61.21,
          "pop": 3882229,
          "year": 1952
         },
         {
          "continent": "Europe",
          "country": "Croatia",
          "gdpPercap": 14619.222719999998,
          "lifeExp": 75.748,
          "pop": 4493312,
          "year": 2007
         },
         {
          "continent": "Americas",
          "country": "Cuba",
          "gdpPercap": 5586.53878,
          "lifeExp": 59.42100000000001,
          "pop": 6007797,
          "year": 1952
         },
         {
          "continent": "Americas",
          "country": "Cuba",
          "gdpPercap": 8948.102923,
          "lifeExp": 78.273,
          "pop": 11416987,
          "year": 2007
         },
         {
          "continent": "Europe",
          "country": "Czech Republic",
          "gdpPercap": 6876.14025,
          "lifeExp": 66.87,
          "pop": 9125183,
          "year": 1952
         },
         {
          "continent": "Europe",
          "country": "Czech Republic",
          "gdpPercap": 22833.30851,
          "lifeExp": 76.486,
          "pop": 10228744,
          "year": 2007
         },
         {
          "continent": "Europe",
          "country": "Denmark",
          "gdpPercap": 9692.385245,
          "lifeExp": 70.78,
          "pop": 4334000,
          "year": 1952
         },
         {
          "continent": "Europe",
          "country": "Denmark",
          "gdpPercap": 35278.41874,
          "lifeExp": 78.332,
          "pop": 5468120,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Djibouti",
          "gdpPercap": 2669.529475,
          "lifeExp": 34.812,
          "pop": 63149,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Djibouti",
          "gdpPercap": 2082.4815670000003,
          "lifeExp": 54.791000000000004,
          "pop": 496374,
          "year": 2007
         },
         {
          "continent": "Americas",
          "country": "Dominican Republic",
          "gdpPercap": 1397.7171369999999,
          "lifeExp": 45.928000000000004,
          "pop": 2491346,
          "year": 1952
         },
         {
          "continent": "Americas",
          "country": "Dominican Republic",
          "gdpPercap": 6025.374752000001,
          "lifeExp": 72.235,
          "pop": 9319622,
          "year": 2007
         },
         {
          "continent": "Americas",
          "country": "Ecuador",
          "gdpPercap": 3522.110717,
          "lifeExp": 48.357,
          "pop": 3548753,
          "year": 1952
         },
         {
          "continent": "Americas",
          "country": "Ecuador",
          "gdpPercap": 6873.262326000001,
          "lifeExp": 74.994,
          "pop": 13755680,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Egypt",
          "gdpPercap": 1418.822445,
          "lifeExp": 41.893,
          "pop": 22223309,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Egypt",
          "gdpPercap": 5581.180998,
          "lifeExp": 71.33800000000001,
          "pop": 80264543,
          "year": 2007
         },
         {
          "continent": "Americas",
          "country": "El Salvador",
          "gdpPercap": 3048.3029,
          "lifeExp": 45.262,
          "pop": 2042865,
          "year": 1952
         },
         {
          "continent": "Americas",
          "country": "El Salvador",
          "gdpPercap": 5728.353514,
          "lifeExp": 71.878,
          "pop": 6939688,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Equatorial Guinea",
          "gdpPercap": 375.6431231,
          "lifeExp": 34.482,
          "pop": 216964,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Equatorial Guinea",
          "gdpPercap": 12154.08975,
          "lifeExp": 51.57899999999999,
          "pop": 551201,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Eritrea",
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          "lifeExp": 35.928000000000004,
          "pop": 1438760,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Eritrea",
          "gdpPercap": 641.3695236000001,
          "lifeExp": 58.04,
          "pop": 4906585,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Ethiopia",
          "gdpPercap": 362.1462796,
          "lifeExp": 34.078,
          "pop": 20860941,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Ethiopia",
          "gdpPercap": 690.8055759,
          "lifeExp": 52.946999999999996,
          "pop": 76511887,
          "year": 2007
         },
         {
          "continent": "Europe",
          "country": "Finland",
          "gdpPercap": 6424.519071,
          "lifeExp": 66.55,
          "pop": 4090500,
          "year": 1952
         },
         {
          "continent": "Europe",
          "country": "Finland",
          "gdpPercap": 33207.0844,
          "lifeExp": 79.313,
          "pop": 5238460,
          "year": 2007
         },
         {
          "continent": "Europe",
          "country": "France",
          "gdpPercap": 7029.809327,
          "lifeExp": 67.41,
          "pop": 42459667,
          "year": 1952
         },
         {
          "continent": "Europe",
          "country": "France",
          "gdpPercap": 30470.0167,
          "lifeExp": 80.657,
          "pop": 61083916,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Gabon",
          "gdpPercap": 4293.476475,
          "lifeExp": 37.003,
          "pop": 420702,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Gabon",
          "gdpPercap": 13206.48452,
          "lifeExp": 56.735,
          "pop": 1454867,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Gambia",
          "gdpPercap": 485.2306591,
          "lifeExp": 30,
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          "year": 1952
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         {
          "continent": "Africa",
          "country": "Gambia",
          "gdpPercap": 752.7497265,
          "lifeExp": 59.448,
          "pop": 1688359,
          "year": 2007
         },
         {
          "continent": "Europe",
          "country": "Germany",
          "gdpPercap": 7144.114393000001,
          "lifeExp": 67.5,
          "pop": 69145952,
          "year": 1952
         },
         {
          "continent": "Europe",
          "country": "Germany",
          "gdpPercap": 32170.37442,
          "lifeExp": 79.406,
          "pop": 82400996,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Ghana",
          "gdpPercap": 911.2989371,
          "lifeExp": 43.148999999999994,
          "pop": 5581001,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Ghana",
          "gdpPercap": 1327.60891,
          "lifeExp": 60.022,
          "pop": 22873338,
          "year": 2007
         },
         {
          "continent": "Europe",
          "country": "Greece",
          "gdpPercap": 3530.690067,
          "lifeExp": 65.86,
          "pop": 7733250,
          "year": 1952
         },
         {
          "continent": "Europe",
          "country": "Greece",
          "gdpPercap": 27538.41188,
          "lifeExp": 79.483,
          "pop": 10706290,
          "year": 2007
         },
         {
          "continent": "Americas",
          "country": "Guatemala",
          "gdpPercap": 2428.2377690000003,
          "lifeExp": 42.023,
          "pop": 3146381,
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",
      "text/plain": [
       "<altair.VegaLite object>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# YOUR CODE HERE\n",
    "alt.Chart(first_last).mark_tick().encode(\n",
    "    alt.X(\"lifeExp:Q\"),\n",
    "    alt.Y(\"continent:N\"), \n",
    "    alt.Color(\"year:N\")\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Income and life expectancy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create an `alt.Chart` with Altair to explore the distribution of life expectancy, grouped by continent:\n",
    "\n",
    "* Use the filtered dataset `first_last`.\n",
    "* Use a circle mark.\n",
    "* Encode `gdpPercap` as the x position. Add a custom log scale, with a domain of `[100,100000]`.\n",
    "* Encode `lifeExp` as the y position. Add a custom scale with a domain of `[30,90]` and `zero=False`.\n",
    "* Encode `pop` as the size.\n",
    "* Encode `continent` as the color with a nominal datatype.\n",
    "* Encode `year` as the row.\n",
    "* Set human readable titles for the axes and legends in title case."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "deletable": false,
    "nbgrader": {
     "checksum": "b8f45f062e224fac9c8ee31ce2f4699d",
     "grade": true,
     "grade_id": "cell-23d2cd29914a77b2",
     "locked": false,
     "points": 8,
     "schema_version": 1,
     "solution": true
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.vegalite.v1+json": {
       "$schema": "https://vega.github.io/schema/vega-lite/v1.2.1.json",
       "data": {
        "values": [
         {
          "continent": "Asia",
          "country": "Afghanistan",
          "gdpPercap": 779.4453145,
          "lifeExp": 28.801,
          "pop": 8425333,
          "year": 1952
         },
         {
          "continent": "Asia",
          "country": "Afghanistan",
          "gdpPercap": 974.5803384,
          "lifeExp": 43.828,
          "pop": 31889923,
          "year": 2007
         },
         {
          "continent": "Europe",
          "country": "Albania",
          "gdpPercap": 1601.056136,
          "lifeExp": 55.23,
          "pop": 1282697,
          "year": 1952
         },
         {
          "continent": "Europe",
          "country": "Albania",
          "gdpPercap": 5937.029525999999,
          "lifeExp": 76.423,
          "pop": 3600523,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Algeria",
          "gdpPercap": 2449.008185,
          "lifeExp": 43.077,
          "pop": 9279525,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Algeria",
          "gdpPercap": 6223.367465,
          "lifeExp": 72.301,
          "pop": 33333216,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Angola",
          "gdpPercap": 3520.610273,
          "lifeExp": 30.015,
          "pop": 4232095,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Angola",
          "gdpPercap": 4797.231267,
          "lifeExp": 42.731,
          "pop": 12420476,
          "year": 2007
         },
         {
          "continent": "Americas",
          "country": "Argentina",
          "gdpPercap": 5911.315053,
          "lifeExp": 62.485,
          "pop": 17876956,
          "year": 1952
         },
         {
          "continent": "Americas",
          "country": "Argentina",
          "gdpPercap": 12779.379640000001,
          "lifeExp": 75.32,
          "pop": 40301927,
          "year": 2007
         },
         {
          "continent": "Oceania",
          "country": "Australia",
          "gdpPercap": 10039.595640000001,
          "lifeExp": 69.12,
          "pop": 8691212,
          "year": 1952
         },
         {
          "continent": "Oceania",
          "country": "Australia",
          "gdpPercap": 34435.367439999995,
          "lifeExp": 81.235,
          "pop": 20434176,
          "year": 2007
         },
         {
          "continent": "Europe",
          "country": "Austria",
          "gdpPercap": 6137.076492,
          "lifeExp": 66.8,
          "pop": 6927772,
          "year": 1952
         },
         {
          "continent": "Europe",
          "country": "Austria",
          "gdpPercap": 36126.4927,
          "lifeExp": 79.829,
          "pop": 8199783,
          "year": 2007
         },
         {
          "continent": "Asia",
          "country": "Bahrain",
          "gdpPercap": 9867.084765000001,
          "lifeExp": 50.93899999999999,
          "pop": 120447,
          "year": 1952
         },
         {
          "continent": "Asia",
          "country": "Bahrain",
          "gdpPercap": 29796.048339999998,
          "lifeExp": 75.635,
          "pop": 708573,
          "year": 2007
         },
         {
          "continent": "Asia",
          "country": "Bangladesh",
          "gdpPercap": 684.2441716,
          "lifeExp": 37.484,
          "pop": 46886859,
          "year": 1952
         },
         {
          "continent": "Asia",
          "country": "Bangladesh",
          "gdpPercap": 1391.253792,
          "lifeExp": 64.062,
          "pop": 150448339,
          "year": 2007
         },
         {
          "continent": "Europe",
          "country": "Belgium",
          "gdpPercap": 8343.105126999999,
          "lifeExp": 68,
          "pop": 8730405,
          "year": 1952
         },
         {
          "continent": "Europe",
          "country": "Belgium",
          "gdpPercap": 33692.60508,
          "lifeExp": 79.441,
          "pop": 10392226,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Benin",
          "gdpPercap": 1062.7522,
          "lifeExp": 38.223,
          "pop": 1738315,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Benin",
          "gdpPercap": 1441.284873,
          "lifeExp": 56.728,
          "pop": 8078314,
          "year": 2007
         },
         {
          "continent": "Americas",
          "country": "Bolivia",
          "gdpPercap": 2677.3263469999997,
          "lifeExp": 40.414,
          "pop": 2883315,
          "year": 1952
         },
         {
          "continent": "Americas",
          "country": "Bolivia",
          "gdpPercap": 3822.1370840000004,
          "lifeExp": 65.554,
          "pop": 9119152,
          "year": 2007
         },
         {
          "continent": "Europe",
          "country": "Bosnia and Herzegovina",
          "gdpPercap": 973.5331947999999,
          "lifeExp": 53.82,
          "pop": 2791000,
          "year": 1952
         },
         {
          "continent": "Europe",
          "country": "Bosnia and Herzegovina",
          "gdpPercap": 7446.298803,
          "lifeExp": 74.852,
          "pop": 4552198,
          "year": 2007
         },
         {
          "continent": "Africa",
          "country": "Botswana",
          "gdpPercap": 851.2411407,
          "lifeExp": 47.622,
          "pop": 442308,
          "year": 1952
         },
         {
          "continent": "Africa",
          "country": "Botswana",
          "gdpPercap": 12569.851770000001,
          "lifeExp": 50.728,
          "pop": 1639131,
          "year": 2007
         },
         {
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",
      "text/plain": [
       "<altair.VegaLite object>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# YOUR CODE HERE\n",
    "alt.Chart(first_last).mark_circle().encode(\n",
    "    alt.X(\"gdpPercap\", scale = alt.Scale(type = \"log\", domain = [100,100000]), title = \"GDP per Capita\"),\n",
    "    alt.Y(\"lifeExp\", scale = alt.Scale(domain = [30,90], zero = False), title = \"Life Expectancy\"),\n",
    "    alt.Size(\"pop\", title = \"Population\"),\n",
    "    alt.Color(\"continent:N\", title = \"Continent\"),\n",
    "    alt.Row(\"year\", title = \"Year\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}