klasse.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "csvfile = pandas.read_csv(\"https://pkgstore.datahub.io/core/pharmaceutical-drug-spending/data_csv/data/db46fb3c420e7100e1d2b1f973e2cbcd/data_csv.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LOCATION</th>\n",
       "      <th>TIME</th>\n",
       "      <th>PC_HEALTHXP</th>\n",
       "      <th>PC_GDP</th>\n",
       "      <th>USD_CAP</th>\n",
       "      <th>FLAG_CODES</th>\n",
       "      <th>TOTAL_SPEND</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1971</td>\n",
       "      <td>15.992</td>\n",
       "      <td>0.727</td>\n",
       "      <td>35.720</td>\n",
       "      <td>NaN</td>\n",
       "      <td>462.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1972</td>\n",
       "      <td>15.091</td>\n",
       "      <td>0.686</td>\n",
       "      <td>36.056</td>\n",
       "      <td>NaN</td>\n",
       "      <td>475.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1973</td>\n",
       "      <td>15.117</td>\n",
       "      <td>0.681</td>\n",
       "      <td>39.871</td>\n",
       "      <td>NaN</td>\n",
       "      <td>533.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1974</td>\n",
       "      <td>14.771</td>\n",
       "      <td>0.755</td>\n",
       "      <td>47.559</td>\n",
       "      <td>NaN</td>\n",
       "      <td>652.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1975</td>\n",
       "      <td>11.849</td>\n",
       "      <td>0.682</td>\n",
       "      <td>47.561</td>\n",
       "      <td>NaN</td>\n",
       "      <td>660.76</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  LOCATION  TIME  PC_HEALTHXP  PC_GDP  USD_CAP FLAG_CODES  TOTAL_SPEND\n",
       "0      AUS  1971       15.992   0.727   35.720        NaN       462.11\n",
       "1      AUS  1972       15.091   0.686   36.056        NaN       475.11\n",
       "2      AUS  1973       15.117   0.681   39.871        NaN       533.47\n",
       "3      AUS  1974       14.771   0.755   47.559        NaN       652.65\n",
       "4      AUS  1975       11.849   0.682   47.561        NaN       660.76"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csvfile.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(csvfile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TIME</th>\n",
       "      <th>PC_HEALTHXP</th>\n",
       "      <th>PC_GDP</th>\n",
       "      <th>USD_CAP</th>\n",
       "      <th>TOTAL_SPEND</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1036.000000</td>\n",
       "      <td>1036.000000</td>\n",
       "      <td>1036.000000</td>\n",
       "      <td>1036.000000</td>\n",
       "      <td>1036.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1996.809846</td>\n",
       "      <td>16.406307</td>\n",
       "      <td>1.170948</td>\n",
       "      <td>295.046989</td>\n",
       "      <td>11765.423118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>12.498330</td>\n",
       "      <td>6.389064</td>\n",
       "      <td>0.465635</td>\n",
       "      <td>209.152134</td>\n",
       "      <td>34878.286123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1970.000000</td>\n",
       "      <td>5.545000</td>\n",
       "      <td>0.207000</td>\n",
       "      <td>3.160000</td>\n",
       "      <td>6.290000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1987.000000</td>\n",
       "      <td>11.516250</td>\n",
       "      <td>0.768250</td>\n",
       "      <td>111.098500</td>\n",
       "      <td>728.180000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1999.000000</td>\n",
       "      <td>14.967500</td>\n",
       "      <td>1.141500</td>\n",
       "      <td>266.332000</td>\n",
       "      <td>2349.570000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2007.000000</td>\n",
       "      <td>20.590500</td>\n",
       "      <td>1.523250</td>\n",
       "      <td>446.109500</td>\n",
       "      <td>7778.180000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2016.000000</td>\n",
       "      <td>40.239000</td>\n",
       "      <td>2.797000</td>\n",
       "      <td>1162.399000</td>\n",
       "      <td>373009.910000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              TIME  PC_HEALTHXP       PC_GDP      USD_CAP    TOTAL_SPEND\n",
       "count  1036.000000  1036.000000  1036.000000  1036.000000    1036.000000\n",
       "mean   1996.809846    16.406307     1.170948   295.046989   11765.423118\n",
       "std      12.498330     6.389064     0.465635   209.152134   34878.286123\n",
       "min    1970.000000     5.545000     0.207000     3.160000       6.290000\n",
       "25%    1987.000000    11.516250     0.768250   111.098500     728.180000\n",
       "50%    1999.000000    14.967500     1.141500   266.332000    2349.570000\n",
       "75%    2007.000000    20.590500     1.523250   446.109500    7778.180000\n",
       "max    2016.000000    40.239000     2.797000  1162.399000  373009.910000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csvfile.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LOCATION</th>\n",
       "      <th>TIME</th>\n",
       "      <th>PC_HEALTHXP</th>\n",
       "      <th>PC_GDP</th>\n",
       "      <th>USD_CAP</th>\n",
       "      <th>FLAG_CODES</th>\n",
       "      <th>TOTAL_SPEND</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1976</td>\n",
       "      <td>10.920</td>\n",
       "      <td>0.630</td>\n",
       "      <td>46.908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>658.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1977</td>\n",
       "      <td>10.087</td>\n",
       "      <td>0.613</td>\n",
       "      <td>47.649</td>\n",
       "      <td>NaN</td>\n",
       "      <td>676.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1978</td>\n",
       "      <td>9.958</td>\n",
       "      <td>0.591</td>\n",
       "      <td>50.799</td>\n",
       "      <td>NaN</td>\n",
       "      <td>729.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1979</td>\n",
       "      <td>8.981</td>\n",
       "      <td>0.523</td>\n",
       "      <td>49.766</td>\n",
       "      <td>NaN</td>\n",
       "      <td>722.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1980</td>\n",
       "      <td>9.263</td>\n",
       "      <td>0.540</td>\n",
       "      <td>56.972</td>\n",
       "      <td>NaN</td>\n",
       "      <td>837.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1981</td>\n",
       "      <td>9.388</td>\n",
       "      <td>0.548</td>\n",
       "      <td>65.390</td>\n",
       "      <td>NaN</td>\n",
       "      <td>976.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1982</td>\n",
       "      <td>9.248</td>\n",
       "      <td>0.564</td>\n",
       "      <td>67.606</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1026.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1983</td>\n",
       "      <td>9.589</td>\n",
       "      <td>0.580</td>\n",
       "      <td>74.083</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1138.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1984</td>\n",
       "      <td>9.465</td>\n",
       "      <td>0.569</td>\n",
       "      <td>77.270</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1201.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1985</td>\n",
       "      <td>9.560</td>\n",
       "      <td>0.580</td>\n",
       "      <td>84.134</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1325.78</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   LOCATION  TIME  PC_HEALTHXP  PC_GDP  USD_CAP FLAG_CODES  TOTAL_SPEND\n",
       "5       AUS  1976       10.920   0.630   46.908        NaN       658.26\n",
       "6       AUS  1977       10.087   0.613   47.649        NaN       676.23\n",
       "7       AUS  1978        9.958   0.591   50.799        NaN       729.37\n",
       "8       AUS  1979        8.981   0.523   49.766        NaN       722.30\n",
       "9       AUS  1980        9.263   0.540   56.972        NaN       837.03\n",
       "10      AUS  1981        9.388   0.548   65.390        NaN       976.08\n",
       "11      AUS  1982        9.248   0.564   67.606        NaN      1026.12\n",
       "12      AUS  1983        9.589   0.580   74.083        NaN      1138.58\n",
       "13      AUS  1984        9.465   0.569   77.270        NaN      1201.08\n",
       "14      AUS  1985        9.560   0.580   84.134        NaN      1325.78"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csvfile[5:15]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LOCATION</th>\n",
       "      <th>TIME</th>\n",
       "      <th>PC_HEALTHXP</th>\n",
       "      <th>PC_GDP</th>\n",
       "      <th>USD_CAP</th>\n",
       "      <th>FLAG_CODES</th>\n",
       "      <th>TOTAL_SPEND</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1979</td>\n",
       "      <td>8.981</td>\n",
       "      <td>0.523</td>\n",
       "      <td>49.766</td>\n",
       "      <td>NaN</td>\n",
       "      <td>722.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1980</td>\n",
       "      <td>9.263</td>\n",
       "      <td>0.540</td>\n",
       "      <td>56.972</td>\n",
       "      <td>NaN</td>\n",
       "      <td>837.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1981</td>\n",
       "      <td>9.388</td>\n",
       "      <td>0.548</td>\n",
       "      <td>65.390</td>\n",
       "      <td>NaN</td>\n",
       "      <td>976.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1982</td>\n",
       "      <td>9.248</td>\n",
       "      <td>0.564</td>\n",
       "      <td>67.606</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1026.12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   LOCATION  TIME  PC_HEALTHXP  PC_GDP  USD_CAP FLAG_CODES  TOTAL_SPEND\n",
       "8       AUS  1979        8.981   0.523   49.766        NaN       722.30\n",
       "9       AUS  1980        9.263   0.540   56.972        NaN       837.03\n",
       "10      AUS  1981        9.388   0.548   65.390        NaN       976.08\n",
       "11      AUS  1982        9.248   0.564   67.606        NaN      1026.12"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csvfile.query('PC_HEALTHXP < 10')[1:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import altair"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n",
      "3\n",
      "5\n"
     ]
    }
   ],
   "source": [
    "a = [ 1, 2, 3, 4, 5 ]\n",
    "\n",
    "for i, v in enumerate(a):\n",
    "    if i % 2 == 0:\n",
    "        print(v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LOCATION</th>\n",
       "      <th>TIME</th>\n",
       "      <th>PC_HEALTHXP</th>\n",
       "      <th>PC_GDP</th>\n",
       "      <th>USD_CAP</th>\n",
       "      <th>FLAG_CODES</th>\n",
       "      <th>TOTAL_SPEND</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1971</td>\n",
       "      <td>15.992</td>\n",
       "      <td>0.727</td>\n",
       "      <td>35.720</td>\n",
       "      <td>NaN</td>\n",
       "      <td>462.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1972</td>\n",
       "      <td>15.091</td>\n",
       "      <td>0.686</td>\n",
       "      <td>36.056</td>\n",
       "      <td>NaN</td>\n",
       "      <td>475.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1973</td>\n",
       "      <td>15.117</td>\n",
       "      <td>0.681</td>\n",
       "      <td>39.871</td>\n",
       "      <td>NaN</td>\n",
       "      <td>533.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1974</td>\n",
       "      <td>14.771</td>\n",
       "      <td>0.755</td>\n",
       "      <td>47.559</td>\n",
       "      <td>NaN</td>\n",
       "      <td>652.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AUS</td>\n",
       "      <td>1975</td>\n",
       "      <td>11.849</td>\n",
       "      <td>0.682</td>\n",
       "      <td>47.561</td>\n",
       "      <td>NaN</td>\n",
       "      <td>660.76</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  LOCATION  TIME  PC_HEALTHXP  PC_GDP  USD_CAP FLAG_CODES  TOTAL_SPEND\n",
       "0      AUS  1971       15.992   0.727   35.720        NaN       462.11\n",
       "1      AUS  1972       15.091   0.686   36.056        NaN       475.11\n",
       "2      AUS  1973       15.117   0.681   39.871        NaN       533.47\n",
       "3      AUS  1974       14.771   0.755   47.559        NaN       652.65\n",
       "4      AUS  1975       11.849   0.682   47.561        NaN       660.76"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csvfile.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we will load the chart and visualise it, because it is a good thing to do!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.vegalite.v2+json": {
       "$schema": "https://vega.github.io/schema/vega-lite/v2.3.0.json",
       "config": {
        "view": {
         "height": 300,
         "width": 400
        }
       },
       "data": {
        "values": [
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.727,
          "PC_HEALTHXP": 15.992,
          "TIME": 1971,
          "TOTAL_SPEND": 462.11,
          "USD_CAP": 35.72
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.6859999999999999,
          "PC_HEALTHXP": 15.091,
          "TIME": 1972,
          "TOTAL_SPEND": 475.11,
          "USD_CAP": 36.056
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.6809999999999999,
          "PC_HEALTHXP": 15.117,
          "TIME": 1973,
          "TOTAL_SPEND": 533.47,
          "USD_CAP": 39.871
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.755,
          "PC_HEALTHXP": 14.770999999999999,
          "TIME": 1974,
          "TOTAL_SPEND": 652.65,
          "USD_CAP": 47.559
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.682,
          "PC_HEALTHXP": 11.849,
          "TIME": 1975,
          "TOTAL_SPEND": 660.76,
          "USD_CAP": 47.56100000000001
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.63,
          "PC_HEALTHXP": 10.92,
          "TIME": 1976,
          "TOTAL_SPEND": 658.26,
          "USD_CAP": 46.908
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.613,
          "PC_HEALTHXP": 10.087,
          "TIME": 1977,
          "TOTAL_SPEND": 676.23,
          "USD_CAP": 47.648999999999994
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.591,
          "PC_HEALTHXP": 9.958,
          "TIME": 1978,
          "TOTAL_SPEND": 729.37,
          "USD_CAP": 50.799
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.523,
          "PC_HEALTHXP": 8.981,
          "TIME": 1979,
          "TOTAL_SPEND": 722.3,
          "USD_CAP": 49.766000000000005
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.54,
          "PC_HEALTHXP": 9.263,
          "TIME": 1980,
          "TOTAL_SPEND": 837.03,
          "USD_CAP": 56.972
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.5479999999999999,
          "PC_HEALTHXP": 9.388,
          "TIME": 1981,
          "TOTAL_SPEND": 976.08,
          "USD_CAP": 65.39
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.564,
          "PC_HEALTHXP": 9.248,
          "TIME": 1982,
          "TOTAL_SPEND": 1026.12,
          "USD_CAP": 67.60600000000001
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.58,
          "PC_HEALTHXP": 9.589,
          "TIME": 1983,
          "TOTAL_SPEND": 1138.58,
          "USD_CAP": 74.083
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.569,
          "PC_HEALTHXP": 9.465,
          "TIME": 1984,
          "TOTAL_SPEND": 1201.08,
          "USD_CAP": 77.27
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.58,
          "PC_HEALTHXP": 9.56,
          "TIME": 1985,
          "TOTAL_SPEND": 1325.78,
          "USD_CAP": 84.134
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.599,
          "PC_HEALTHXP": 9.568,
          "TIME": 1986,
          "TOTAL_SPEND": 1440.69,
          "USD_CAP": 89.94
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.5820000000000001,
          "PC_HEALTHXP": 9.543,
          "TIME": 1987,
          "TOTAL_SPEND": 1521.94,
          "USD_CAP": 93.57799999999999
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.595,
          "PC_HEALTHXP": 9.823,
          "TIME": 1988,
          "TOTAL_SPEND": 1686.73,
          "USD_CAP": 102.027
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.623,
          "PC_HEALTHXP": 10.199,
          "TIME": 1989,
          "TOTAL_SPEND": 1869.71,
          "USD_CAP": 111.197
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.677,
          "PC_HEALTHXP": 10.474,
          "TIME": 1990,
          "TOTAL_SPEND": 2061,
          "USD_CAP": 120.773
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.7390000000000001,
          "PC_HEALTHXP": 10.937000000000001,
          "TIME": 1991,
          "TOTAL_SPEND": 2322.21,
          "USD_CAP": 134.356
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.778,
          "PC_HEALTHXP": 11.407,
          "TIME": 1992,
          "TOTAL_SPEND": 2608.43,
          "USD_CAP": 149.096
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.8190000000000001,
          "PC_HEALTHXP": 11.977,
          "TIME": 1993,
          "TOTAL_SPEND": 2921.4,
          "USD_CAP": 165.359
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.8590000000000001,
          "PC_HEALTHXP": 12.508,
          "TIME": 1994,
          "TOTAL_SPEND": 3284.82,
          "USD_CAP": 183.972
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.882,
          "PC_HEALTHXP": 12.762,
          "TIME": 1995,
          "TOTAL_SPEND": 3585.59,
          "USD_CAP": 198.40599999999998
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.924,
          "PC_HEALTHXP": 13.106,
          "TIME": 1996,
          "TOTAL_SPEND": 3947.96,
          "USD_CAP": 215.606
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 0.95,
          "PC_HEALTHXP": 13.437000000000001,
          "TIME": 1997,
          "TOTAL_SPEND": 4306.87,
          "USD_CAP": 232.59
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 1.0190000000000001,
          "PC_HEALTHXP": 14.084000000000001,
          "TIME": 1998,
          "TOTAL_SPEND": 4897.19,
          "USD_CAP": 261.728
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 1.075,
          "PC_HEALTHXP": 14.679,
          "TIME": 1999,
          "TOTAL_SPEND": 5518.61,
          "USD_CAP": 291.589
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 1.194,
          "PC_HEALTHXP": 15.702,
          "TIME": 2000,
          "TOTAL_SPEND": 6486.45,
          "USD_CAP": 338.665
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 1.236,
          "PC_HEALTHXP": 16.059,
          "TIME": 2001,
          "TOTAL_SPEND": 7081.3,
          "USD_CAP": 364.77099999999996
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 1.213,
          "PC_HEALTHXP": 15.374,
          "TIME": 2002,
          "TOTAL_SPEND": 7330.84,
          "USD_CAP": 373.04400000000004
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 1.244,
          "PC_HEALTHXP": 15.761,
          "TIME": 2003,
          "TOTAL_SPEND": 7984.06,
          "USD_CAP": 401.30199999999996
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 1.2690000000000001,
          "PC_HEALTHXP": 15.655999999999999,
          "TIME": 2004,
          "TOTAL_SPEND": 8652.41,
          "USD_CAP": 429.88199999999995
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 1.213,
          "PC_HEALTHXP": 15.218,
          "TIME": 2005,
          "TOTAL_SPEND": 8821.02,
          "USD_CAP": 432.51300000000003
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 1.219,
          "PC_HEALTHXP": 15.276,
          "TIME": 2006,
          "TOTAL_SPEND": 9558.72,
          "USD_CAP": 461.82099999999997
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 1.225,
          "PC_HEALTHXP": 15.200999999999999,
          "TIME": 2007,
          "TOTAL_SPEND": 10119.86,
          "USD_CAP": 485.88699999999994
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 1.273,
          "PC_HEALTHXP": 15.412,
          "TIME": 2008,
          "TOTAL_SPEND": 10840.75,
          "USD_CAP": 510.17199999999997
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 1.334,
          "PC_HEALTHXP": 15.535,
          "TIME": 2009,
          "TOTAL_SPEND": 12011.21,
          "USD_CAP": 553.724
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 1.324,
          "PC_HEALTHXP": 15.63,
          "TIME": 2010,
          "TOTAL_SPEND": 12422.76,
          "USD_CAP": 563.857
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 1.315,
          "PC_HEALTHXP": 15.311,
          "TIME": 2011,
          "TOTAL_SPEND": 12977.79,
          "USD_CAP": 580.9209999999999
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 1.3359999999999999,
          "PC_HEALTHXP": 15.308,
          "TIME": 2012,
          "TOTAL_SPEND": 13247.71,
          "USD_CAP": 582.874
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 1.32,
          "PC_HEALTHXP": 14.989,
          "TIME": 2013,
          "TOTAL_SPEND": 14503.87,
          "USD_CAP": 627.4019999999999
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUS",
          "PC_GDP": 1.306,
          "PC_HEALTHXP": 14.386,
          "TIME": 2014,
          "TOTAL_SPEND": 14475.18,
          "USD_CAP": 616.997
         },
         {
          "FLAG_CODES": "B",
          "LOCATION": "AUT",
          "PC_GDP": 0.784,
          "PC_HEALTHXP": 10.131,
          "TIME": 1990,
          "TOTAL_SPEND": 1167.06,
          "USD_CAP": 152.003
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 0.78,
          "PC_HEALTHXP": 10.001,
          "TIME": 1991,
          "TOTAL_SPEND": 1241.7,
          "USD_CAP": 160.118
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 0.8009999999999999,
          "PC_HEALTHXP": 9.889,
          "TIME": 1992,
          "TOTAL_SPEND": 1330.63,
          "USD_CAP": 169.708
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 0.84,
          "PC_HEALTHXP": 9.746,
          "TIME": 1993,
          "TOTAL_SPEND": 1437.19,
          "USD_CAP": 181.793
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 0.852,
          "PC_HEALTHXP": 9.457,
          "TIME": 1994,
          "TOTAL_SPEND": 1524.39,
          "USD_CAP": 192.083
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 0.8540000000000001,
          "PC_HEALTHXP": 9.542,
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          "TOTAL_SPEND": 1600.27,
          "USD_CAP": 201.335
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 0.8759999999999999,
          "PC_HEALTHXP": 9.839,
          "TIME": 1996,
          "TOTAL_SPEND": 1706.56,
          "USD_CAP": 214.418
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.01,
          "PC_HEALTHXP": 11.213,
          "TIME": 1997,
          "TOTAL_SPEND": 2039.24,
          "USD_CAP": 255.92700000000002
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.087,
          "PC_HEALTHXP": 11.843,
          "TIME": 1998,
          "TOTAL_SPEND": 2303.45,
          "USD_CAP": 288.769
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.17,
          "PC_HEALTHXP": 12.550999999999998,
          "TIME": 1999,
          "TOTAL_SPEND": 2576.07,
          "USD_CAP": 322.318
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.1740000000000002,
          "PC_HEALTHXP": 12.734000000000002,
          "TIME": 2000,
          "TOTAL_SPEND": 2756.64,
          "USD_CAP": 344.082
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.198,
          "PC_HEALTHXP": 12.897,
          "TIME": 2001,
          "TOTAL_SPEND": 2863.55,
          "USD_CAP": 356.061
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.238,
          "PC_HEALTHXP": 13.154000000000002,
          "TIME": 2002,
          "TOTAL_SPEND": 3114.01,
          "USD_CAP": 385.30400000000003
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.304,
          "PC_HEALTHXP": 13.607000000000001,
          "TIME": 2003,
          "TOTAL_SPEND": 3387.34,
          "USD_CAP": 417.087
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.294,
          "PC_HEALTHXP": 13.41,
          "TIME": 2004,
          "TOTAL_SPEND": 3557.48,
          "USD_CAP": 435.327
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.2770000000000001,
          "PC_HEALTHXP": 13.325,
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          "TOTAL_SPEND": 3662.93,
          "USD_CAP": 445.18800000000005
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.268,
          "PC_HEALTHXP": 13.37,
          "TIME": 2006,
          "TOTAL_SPEND": 3926.23,
          "USD_CAP": 474.834
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.2890000000000001,
          "PC_HEALTHXP": 13.605,
          "TIME": 2007,
          "TOTAL_SPEND": 4187.97,
          "USD_CAP": 504.849
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.311,
          "PC_HEALTHXP": 13.606,
          "TIME": 2008,
          "TOTAL_SPEND": 4479.07,
          "USD_CAP": 538.253
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.271,
          "PC_HEALTHXP": 12.53,
          "TIME": 2009,
          "TOTAL_SPEND": 4315.71,
          "USD_CAP": 517.265
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.251,
          "PC_HEALTHXP": 12.368,
          "TIME": 2010,
          "TOTAL_SPEND": 4383.62,
          "USD_CAP": 524.143
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.236,
          "PC_HEALTHXP": 12.472999999999999,
          "TIME": 2011,
          "TOTAL_SPEND": 4588.41,
          "USD_CAP": 546.783
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.234,
          "PC_HEALTHXP": 12.181,
          "TIME": 2012,
          "TOTAL_SPEND": 4809.52,
          "USD_CAP": 570.525
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.245,
          "PC_HEALTHXP": 12.222000000000001,
          "TIME": 2013,
          "TOTAL_SPEND": 5037.85,
          "USD_CAP": 594.13
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.268,
          "PC_HEALTHXP": 12.324000000000002,
          "TIME": 2014,
          "TOTAL_SPEND": 5263.8,
          "USD_CAP": 616.256
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "AUT",
          "PC_GDP": 1.28,
          "PC_HEALTHXP": 12.407,
          "TIME": 2015,
          "TOTAL_SPEND": 5462.53,
          "USD_CAP": 632.737
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "BEL",
          "PC_GDP": 1.078,
          "PC_HEALTHXP": 28.113000000000003,
          "TIME": 1970,
          "TOTAL_SPEND": 404.74,
          "USD_CAP": 41.918
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "BEL",
          "PC_GDP": 1.109,
          "PC_HEALTHXP": 28.275,
          "TIME": 1971,
          "TOTAL_SPEND": 453.75,
          "USD_CAP": 46.908
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "BEL",
          "PC_GDP": 1.126,
          "PC_HEALTHXP": 27.629,
          "TIME": 1972,
          "TOTAL_SPEND": 506,
          "USD_CAP": 52.105
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "BEL",
          "PC_GDP": 1.2,
          "PC_HEALTHXP": 27.546999999999997,
          "TIME": 1973,
          "TOTAL_SPEND": 603.17,
          "USD_CAP": 61.916000000000004
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "BEL",
          "PC_GDP": 1.183,
          "PC_HEALTHXP": 26.779,
          "TIME": 1974,
          "TOTAL_SPEND": 675.73,
          "USD_CAP": 69.14699999999999
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "BEL",
          "PC_GDP": 1.208,
          "PC_HEALTHXP": 21.886,
          "TIME": 1975,
          "TOTAL_SPEND": 743.4,
          "USD_CAP": 75.852
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "BEL",
          "PC_GDP": 1.081,
          "PC_HEALTHXP": 18.88,
          "TIME": 1976,
          "TOTAL_SPEND": 741.51,
          "USD_CAP": 75.524
         },
         {
          "FLAG_CODES": null,
          "LOCATION": "BEL",
          "PC_GDP": 1.133,
          "PC_HEALTHXP": 18.301,
          "TIME": 1977,
          "TOTAL_SPEND": 830.91,
          "USD_CAP": 84.525
         },
         {
          "FLAG_CODES": null,
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          "PC_GDP": 1.286,
          "PC_HEALTHXP": 22.939,
          "TIME": 2015,
          "TOTAL_SPEND": 44655.62,
          "USD_CAP": 309.9
         }
        ]
       },
       "encoding": {
        "x": {
         "field": "PC_HEALTHXP",
         "type": "quantitative"
        },
        "y": {
         "field": "TOTAL_SPEND",
         "type": "quantitative"
        }
       },
       "mark": "point"
      },
      "image/png": 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",
      "text/plain": [
       "<VegaLite 2 object>\n",
       "\n",
       "If you see this message, it means the renderer has not been properly enabled\n",
       "for the frontend that you are using. For more information, see\n",
       "https://altair-viz.github.io/user_guide/troubleshooting.html\n"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "altair.Chart(csvfile).mark_point().encode(\n",
    "    x='PC_HEALTHXP',\n",
    "    y='TOTAL_SPEND'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2.0.0rc2'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "altair.__version__\n"
   ]
  }
 ],
 "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": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}