Matplotlib Tutorial
Making a graph that captures the attention and tells the beholder an insightful story.
Hello, and welcome to this Python + Matplotlib tutorial, the place I’ll present you the way to create the attractive polar histogram you see above.
Polar histograms are nice when you’ve too many values for the standard bar chart. The round form the place every bar will get thinner in direction of the center permits us to cram extra data into the identical space.
A pleasant characteristic is the ensuing visible comparability between the bottom and highest values as they meet one another after one lap across the heart.
On this tutorial, I’m utilizing information from the World Happiness Report and details about revenue ranges from the World Bank. Each information sources are publicly accessible below Inventive Commons licenses.
My information body accommodates 146 nations and three columns.
Right here’s what it seems to be like.
I’ll present and clarify each line of code required to create the visualization. If you wish to observe alongside, you’ll find the code and information I’m utilizing on this GitHub repository.
Let’s get began.
Importing libraries
We solely want customary Python libraries acquainted to everybody. PIL shouldn’t be obligatory, nevertheless it’s my most well-liked alternative for dealing with photos which we do when including flags.
import math
import numpy as np
import pandas as pdimport seaborn as sns
import matplotlib.pyplot as plt
from PIL import Picture
from matplotlib.traces import Line2D
from matplotlib.patches import Wedge
from matplotlib.offsetbox import OffsetImage, AnnotationBbox
The one factor that stands out is a number of particular Matplotlib imports on the finish. I’ll cowl these elements later within the tutorial.
As common, I exploit pandas to load the info.
