Ah, the pie chart. It’s a bit divisive in data visualization. Supporters say it’s an intuitive way to visualize the breakdown of a whole into parts, and detractors say that it’s clunky and likely to mislead people.

Here at Codecademy, we just follow some best practices: pie charts work best for breakdowns of 2-8 parts, and they are only a good choice when the takeaway doesn’t have to be too granular. People can’t tell the difference between 18% and 20% when looking at a pie chart, but they can compare “about 30%” to “about 50%”, for example.

With those strengths and limitations in mind, how do we make a pie chart using matplotlib? We use the plt.pie() function! plt.pie() takes the following parameters:

• x: the numeric variable shown as pieces of the pie. The function adds up all the x values to compare part and whole and auto-generate the pieces of the pie.
• labels: the variable used to label each section of the pie chart
• startangle: the rotation of the pie chart, adjusted to improve readability
• colors: an array of colors the chart will cycle through. If blank, defaults to matplotlib’s default 10-color “Tableau” palette.

x is the only required parameter here, but the others can all help make the pie chart more readable. A pie chart showing the five favorite donut flavors of conference attendees might be written with the following code:

plt.pie(x = data.donut_vote_count, labels = data.donut_flavor, startangle = 30, colors = ['brown', 'pink', 'purple', 'white', 'red'])

The startangle may or may not need adjusting – generally, this depends on how the pie pieces (and subsequently their labels) are distributed.