How to do a stack plot with Matplotlib
• 2 minStack plots are extremely useful when you want to compare multi-series data on the same axis.
Especially when you want to check whether there is some kind of correlation between those variables.
Here is a simple example of a stacked plot, using the matplotlib library.
import matplotlib.pyplot as plt
import pandas as pd
# We set our x labels
months = ['Jan', 'Feb', 'Mar',
'Apr', 'May', 'Jun',
'Jul', 'Aug', 'Sep',
'Oct', 'Nov', 'Dec']
# We add some random data
sales_per_month = {
'2018': [2221, 2315, 2455,
2304, 2670, 2181,
2768, 1897, 2488,
2456, 1915, 2759],
'2019': [3969, 3009, 3949,
4077, 3228, 3339,
3565, 3278, 3389,
2422, 3451, 4095],
'2020': [5222, 3875, 5132,
3872, 4592, 5685,
4289, 3517, 5243,
4794, 4693, 4324],
'2021': [10161, 8268, 3540,
10256, 10409, 9525,
10560, 10390, 10432,
11617, 10323, 15200],
}
# We set our canvas
fig, axes = plt.subplots(1,1, figsize=(8,6))
# We do a line plot on the axes
axes.stackplot(months,
sales_per_month.values(),
labels=sales_per_month.keys())
# We set a title
axes.set_title("Sales per month")
# Change the labels
axes.set_xlabel("Month")
axes.set_ylabel("In USD")
# Add the legend
axes.legend(loc='upper left')
# Fixing the layout to fit the size
fig.tight_layout()
# Showing the plot
plt.show()As we can see we are using the axes.stackplot() method that will plot a stackplot given a list of x values and multiple y as pd.Series.
(e.g. axes.stackplot(x, y1, y2, y3, ...))
In this example, we are plotting the sales per month in dollars and comparing it per year.
Here is the result.
Here you are ! You now know how to make stackplots.
More on plots
If you want to know more about how to add labels, plot different types of plots, etc... check out the other articles I wrote on the topic, just here :
