Python | Grouped bar plots in python

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Bar plots

Bar plots, also known as bar charts, are a type of chart used to compare the values of different categories. They display the values as rectangular bars with lengths proportional to the values they represent. Bar plots are commonly used to compare the sizes of different categories, identify trends, and visualize changes over time.

In Python, you can create bar plots using various libraries such as Matplotlib, Seaborn, and Plotly. Here's an example using Matplotlib:

import matplotlib.pyplot as plt

# Sample data

categories = ['A', 'B', 'C', 'D', 'E']

values = [10, 24, 36, 45, 52]

# Create a bar plot

plt.bar(categories, values)

# Set the title and axis labels

plt.title('Bar Plot of Categories')

plt.xlabel('Categories')

plt.ylabel('Values')

# Show the plot

plt.show()

In this example, we have five categories and their corresponding values. We create a bar plot using plt.bar(), where the first argument is the list of categories and the second argument is the list of values. We then set the title and axis labels using plt.title(), plt.xlabel(), and plt.ylabel(), and display the plot using plt.show().

You can also customize the appearance of the bar plot by specifying the color, width, and other options. For example, to change the color of the bars to red, add color='red' to the plt.bar() call. To change the width of the bars to 0.5, add width=0.5.