import matplotlib.pyplot as plt import pandas as pd df = pd.DataFrame({'x': ['A', 'B', 'C', 'D', 'E'], 'y': [50, 30, 70, 80, 60]}) plt.bar(df['x'], df['y'], align='center', width=0.5, color='b', label='data') plt.xlabel('X axis') plt.ylabel('Y axis') plt.title('Bar chart') plt.legend() plt.show() 

import matplotlib.pyplot as plt import pandas as pd df = pd.DataFrame({'x': ['A', 'B', 'C', 'D', 'E'], 'y1': [50, 30, 70, 80, 60], 'y2': [20, 40, 10, 50, 30]}) plt.bar(df['x'], df['y1'], align='center', width=0.5, color='b', label='Series 1') plt.bar(df['x'], df['y2'], bottom=df['y1'], align='center', width=0.5, color='g', label='Series 2') plt.xlabel('X axis') plt.ylabel('Y axis') plt.title('Stacked Bar Chart') plt.legend() plt.show() 

import matplotlib.pyplot as plt import pandas as pd import numpy as np # Prepare the data df = pd.DataFrame({ 'group': ['G1', 'G2', 'G3', 'G4', 'G5'], 'men_means': [20, 35, 30, 35, 27], 'women_means': [25, 32, 34, 20, 25] }) ind = np.arange(len(df)) # x-axis position width = 0.35 # width of each bar  # Plot the bar chart fig, ax = plt.subplots() rects1 = ax.bar(ind, df['men_means'], width, color='r') rects2 = ax.bar(ind + width, df['women_means'], width, color='y') # Add labels, legend, and axis labels ax.set_xticks(ind + width / 2) ax.set_xticklabels(df['group']) ax.legend((rects1[0], rects2[0]), ('Men', 'Women')) ax.set_xlabel('Groups') ax.set_ylabel('Scores') # Display the plot plt.show() 

import matplotlib.pyplot as plt import pandas as pd # Prepare the data df = pd.DataFrame({ 'x': ['Group 1', 'Group 2', 'Group 3', 'Group 4', 'Group 5'], 'y1': [10, 20, 30, 25, 30], 'y2': [20, 25, 30, 15, 20], 'y3': [30, 30, 25, 20, 10] }) # calculate percentage y_percent = df.iloc[:, 1:].div(df.iloc[:, 1:].sum(axis=1), axis=0) * 100 # plot the chart fig, ax = plt.subplots() ax.bar(df['x'], y_percent.iloc[:, 0], label='Series 1', color='r') ax.bar(df['x'], y_percent.iloc[:, 1], bottom=y_percent.iloc[:, 0], label='Series 2', color='g') ax.bar(df['x'], y_percent.iloc[:, 2], bottom=y_percent.iloc[:, :2].sum(axis=1), label='Series 3', color='b') # Display the plot plt.show()