You can use the width argument to adjust the width of bars in a bar plot created by Matplotlib:
import matplotlib.pyplot as plt
plt.bar(x=df.category, height=df.amount, width=0.8)
The default value for width is 0.8 but you can increase this value to make the bars wider or decrease this value to make the bars more narrow.
The following example shows how to use this syntax in practice.
Example: Adjust Width of Bars in Matplotlib
Suppose we have the following pandas DataFrame that contains information about the total sales of various products at some grocery store:
import pandas as pd
#create DataFrame
df = pd.DataFrame({'item': ['Apples', 'Oranges', 'Kiwis', 'Bananas', 'Limes'],
'sales': [18, 22, 19, 14, 24]})
#view DataFrame
print(df)
item sales
0 Apples 18
1 Oranges 22
2 Kiwis 19
3 Bananas 14
4 Limes 24
We can use the following code to create a bar chart to visualize the number of sales of each item:
import matplotlib.pyplot as plt
#create bar chart
plt.bar(x=df.item, height=df.sales)
By default, Matplotlib uses a width of 0.8.
However, we can use the width argument to specify a different value:
import matplotlib.pyplot as plt
#create bar chart with narrow bars
plt.bar(x=df.item, height=df.sales, width=0.4)
Notice that the bars are much more narrow.
Also note that if you use a value of 1 for width, the bars will touch each other:
import matplotlib.pyplot as plt
#create bar chart with width of 1
plt.bar(x=df.item, height=df.sales, width=1, edgecolor='black')
Feel free to adjust the value for the width argument to make the bars in the plot as wide or narrow as you’d like.
Additional Resources
The following tutorials explain how to perform other common tasks in Matplotlib:
How to Create Stacked Bar Charts in Matplotlib
How to Create a Relative Frequency Histogram in Matplotlib
How to Create a Horizontal Barplot in Seaborn
