{ "cells": [ { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Import your data" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
\n", " | Country | \n", "Continent | \n", "GDP_per_capita | \n", "life_expectancy | \n", "Population | \n", "
---|---|---|---|---|---|
0 | \n", "Afghanistan | \n", "Asia | \n", "663 | \n", "54.863 | \n", "22856302 | \n", "
1 | \n", "Albania | \n", "Europe | \n", "4195 | \n", "74.200 | \n", "3071856 | \n", "
2 | \n", "Algeria | \n", "Africa | \n", "5098 | \n", "68.963 | \n", "30533827 | \n", "
3 | \n", "Angola | \n", "Africa | \n", "2446 | \n", "45.234 | \n", "13926373 | \n", "
4 | \n", "Antigua and Barbuda | \n", "N. America | \n", "12738 | \n", "73.544 | \n", "77656 | \n", "