极速阅览

Libraries & Dataset

First, we need to load a few libraries and a dataset:

# libraries import matplotlib.pyplot as plt import numpy as np import pandas as pd # create dataset height = [3, 12, 5, 18, 45] bars = ('A', 'B', 'C', 'D', 'E') df = pd.DataFrame({ 'Group': bars, 'Value': height })

📍 Most basic

Building a horizontal barplot with matplotlib follows pretty much the same process as a vertical barplot. The only difference is that the barh() function must be used instead of the bar() function. Here is a basic example:

# Create horizontal bars plt.barh(y=df.Group, width=df.Value) # Show graphic plt.show()

↕️ Control order

A bar chart is always more insightful when ordered. It allows to understand how items are ranked much quicker. Since matplotlib traces the values in the order in which they are found in the data frame, you just have to sort the dataframe upfront to sort the chart:

# Sort the table df = df.sort_values(by=['Value']) # Create horizontal bars plt.barh(y=df.Group, width=df.Value) # Display the plot plt.show()

✨ Object-oriented API

Same graph as above using the matplotlib object oriented API instead of the pyplot API. See the matplotlib section for more about this.

# Initialize a Figure and an Axes fig, ax = plt.subplots() # Create horizontal bars ax.barh(y=df.Group, width=df.Value) # Show the plot plt.show()

Going further

This post explains how to create a horizontal barplot using matplotlib!

For more examples of how to create or customize your barplots, see the barplot section. You may also be interested in how to custom colors in a barplot.

Plotting a Horizontal Barplot using Matplotlib

Libraries & Dataset

📍 Most basic

↕️ Control order

✨ Object-oriented API

Going further

🚨 Grab the Data To Viz poster!

Plotting a Horizontal Barplot using Matplotlib

Libraries & Dataset

📍 Most basic

↕️ Control order

✨ Object-oriented API

Going further

Ranking

🚨 Grab the Data To Viz poster!