In this article, we will learn how to Create a grouped bar plot in Matplotlib. Let’s discuss some concepts :
- Matplotlib is a tremendous visualization library in Python for 2D plots of arrays. Matplotlib may be a multi-platform data visualization library built on NumPy arrays and designed to figure with the broader SciPy stack. It had been introduced by John Hunter within the year 2002.
- A bar plot or bar graph may be a graph that represents the category of knowledge with rectangular bars with lengths and heights that’s proportional to the values which they represent. The bar plots are often plotted horizontally or vertically.
- A bar chart is a great way to compare categorical data across one or two dimensions. More often than not, it’s more interesting to compare values across two dimensions and for that, a grouped bar chart is needed.
Approach:
- Import Library (Matplotlib)
- Import / create data.
- Plot the bars in the grouped manner.
Example 1: (Simple grouped bar plot)
Python3
# importing packageimport matplotlib.pyplot as pltimport numpy as np # create datax = np.arange(5)y1 = [34, 56, 12, 89, 67]y2 = [12, 56, 78, 45, 90]width = 0.40 # plot data in grouped manner of bar typeplt.bar(x-0.2, y1, width)plt.bar(x+0.2, y2, width) |
Output :
Example 2: (Grouped bar chart with more than 2 data)
Python3
# importing packageimport matplotlib.pyplot as pltimport numpy as np # create datax = np.arange(5)y1 = [34, 56, 12, 89, 67]y2 = [12, 56, 78, 45, 90]y3 = [14, 23, 45, 25, 89]width = 0.2 # plot data in grouped manner of bar typeplt.bar(x-0.2, y1, width, color='cyan')plt.bar(x, y2, width, color='orange')plt.bar(x+0.2, y3, width, color='green')plt.xticks(x, ['Team A', 'Team B', 'Team C', 'Team D', 'Team E'])plt.xlabel("Teams")plt.ylabel("Scores")plt.legend(["Round 1", "Round 2", "Round 3"])plt.show() |
Output :
Example 3: (Grouped Bar chart using dataframe plot)
Python3
# importing packageimport matplotlib.pyplot as pltimport pandas as pd # create datadf = pd.DataFrame([['A', 10, 20, 10, 30], ['B', 20, 25, 15, 25], ['C', 12, 15, 19, 6], ['D', 10, 29, 13, 19]], columns=['Team', 'Round 1', 'Round 2', 'Round 3', 'Round 4'])# view dataprint(df) # plot grouped bar chartdf.plot(x='Team', kind='bar', stacked=False, title='Grouped Bar Graph with dataframe') |
Output :
