From the course: Python Data Visualization: Create Impactful Visuals, Animations, and Dashboards by Pearson

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Demo, part 2

Demo, part 2 - Python Tutorial

From the course: Python Data Visualization: Create Impactful Visuals, Animations, and Dashboards by Pearson

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Demo, part 2

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Now that we have a good understanding of the basic functionality of Matplotlib, we can see how we can use it to generate more sophisticated types of plots like bubble plots. So we're going to start by loading some data from gapminder.org using Pandas. So for this, we're just going to do pd.readcsv data gapminder.csv, and we're going to define a couple of useful arrays, one of colors, and one of continents. We can take a look at the data, and essentially what we have are five different columns, one with the country, one with GDP, population, life expectancy, and the corresponding continent that that country is located in. The continent is given by numerical ID, so zero is Africa, one is Americas, etc. What we're going to do is we're going to plot all of this data into a single chart using all the tools we learned so far. We're going to do this by encoding this information in multiple ways into the plot. In particular, we're going to set the GDP to be along the x-axis, the life…

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