1import numpy as np
2import matplotlib.pyplot as plt
3data = [[30, 25, 50, 20],
4[40, 23, 51, 17],
5[35, 22, 45, 19]]
6X = np.arange(4)
7fig = plt.figure()
8ax = fig.add_axes([0,0,1,1])
9ax.bar(X + 0.00, data[0], color = 'b', width = 0.25)
10ax.bar(X + 0.25, data[1], color = 'g', width = 0.25)
11ax.bar(X + 0.50, data[2], color = 'r', width = 0.25)
1import numpy as npimport matplotlib.pyplot as plt# data to plotn_groups = 4means_frank = (90, 55, 40, 65)means_guido = (85, 62, 54, 20)# create plotfig, ax = plt.subplots()index = np.arange(n_groups)bar_width = 0.35opacity = 0.8rects1 = 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()
1import matplotlib.pyplot as plt
2import numpy as np
3plt.bar(np.arange(0,100),np.arange(0,100))
1import matplotlib.pyplot as plt; plt.rcdefaults()import numpy as npimport matplotlib.pyplot as pltobjects = ('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()