{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Overview\n", "This notebook demonstrates how to apply built-in theme templates to plotly.py figures" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import plotly.graph_objs as go\n", "import plotly.io as pio\n", "import pandas as pd" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Load gapminder dataset for 1982" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | country | \n", "year | \n", "pop | \n", "continent | \n", "lifeExp | \n", "gdpPercap | \n", "
---|---|---|---|---|---|---|
30 | \n", "Algeria | \n", "1982 | \n", "20033753.0 | \n", "Africa | \n", "61.368 | \n", "5745.160213 | \n", "
42 | \n", "Angola | \n", "1982 | \n", "7016384.0 | \n", "Africa | \n", "39.942 | \n", "2756.953672 | \n", "
126 | \n", "Benin | \n", "1982 | \n", "3641603.0 | \n", "Africa | \n", "50.904 | \n", "1277.897616 | \n", "
162 | \n", "Botswana | \n", "1982 | \n", "970347.0 | \n", "Africa | \n", "61.484 | \n", "4551.142150 | \n", "
198 | \n", "Burkina Faso | \n", "1982 | \n", "6634596.0 | \n", "Africa | \n", "48.122 | \n", "807.198586 | \n", "