Matplotlib may be used to create bar charts. You might like the Matplotlib gallery.
Related course
The course below is all about data visualization:
Bar chart code
The code below creates a bar chart:
import matplotlib.pyplot as plt; plt.rcdefaults() import numpy as np import matplotlib.pyplot as plt objects = ('Python', 'C++', 'Java', 'Perl', 'Scala', 'Lisp') y_pos = np.arange(len(objects)) performance = [10,8,6,4,2,1] plt.bar(y_pos, performance, align='center', alpha=0.5) plt.xticks(y_pos, objects) plt.ylabel('Usage') plt.title('Programming language usage') plt.show() |
Output:
Matplotlib charts can be horizontal, to create a horizontal bar chart:
import matplotlib.pyplot as plt; plt.rcdefaults() import numpy as np import matplotlib.pyplot as plt objects = ('Python', 'C++', 'Java', 'Perl', 'Scala', 'Lisp') y_pos = np.arange(len(objects)) performance = [10,8,6,4,2,1] plt.barh(y_pos, performance, align='center', alpha=0.5) plt.yticks(y_pos, objects) plt.xlabel('Usage') plt.title('Programming language usage') plt.show() |
Output:
More on bar charts
You can compare two data series using this Matplotlib code:
import numpy as np import matplotlib.pyplot as plt # data to plot n_groups = 4 means_frank = (90, 55, 40, 65) means_guido = (85, 62, 54, 20) # create plot fig, ax = plt.subplots() index = np.arange(n_groups) bar_width = 0.35 opacity = 0.8 rects1 = plt.bar(index, means_frank, bar_width, alpha=opacity, color='b', label='Frank') rects2 = plt.bar(index + bar_width, means_guido, bar_width, alpha=opacity, color='g', label='Guido') plt.xlabel('Person') plt.ylabel('Scores') plt.title('Scores by person') plt.xticks(index + bar_width, ('A', 'B', 'C', 'D')) plt.legend() plt.tight_layout() plt.show() |
Output:
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