How to do a barplot with Matplotlib

1 min readMatplotlibPlotPandasDataFrameData
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Barplots are one of the most widely used plots in data visualization.

They can be used to compare the evolution of multiple variables over time.

Here is a simple example of a barplot, using the matplotlib library.

import matplotlib.pyplot as plt
import pandas as pd

# We generate a dataframe with some random data
df = pd.DataFrame(index = ['2018', '2019', '2020', '2021'], 
                  data={"sales": [28429, 41771, 55238, 120681]})

# We set our canvas
fig, axes = plt.subplots(1,1, figsize=(8,6))

# We do a bar plot on the axes
axes.bar(x=df.index,
         height=df["sales"], 
         label="Sales in USD")

# We set a title
axes.set_title("Sales per year")

# Change the labels
axes.set_xlabel("Year")
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()
How to do a barplot using Matplotlib library

As we can see we are using the axes.bar() method that will do a barplot given a index list and a list of heights.

In this example, we are plotting the amount of sales versus the year column.

Here is the result.

A barplot example illustrating the sales per year

Here you are ! You now know how to do a barplot in Python using Matplotlib library !

More on plots

If you want to know more about how to add labels, plot different types of plots, etc... checkout the other articles I wrote on the topic, just here :

Matplotlib - The Python You Need
We gathered the only Python essentials that you will probably ever need.
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