The content of this article is about the analysis of the method of drawing histograms and subgraphs in Python (code examples). It has certain reference value. Friends in need can refer to it. I hope it will be helpful to you.
1. The drawing of histograms also requires the use of pylab under matplotlib, but when drawing line charts we use plot(), and when drawing histograms we need to use hist() . Due to the lack of real data in the drawing process, I use the random numbers generated by np.random.normal(a,b,c) to draw the histogram. a is the mean, b is the standard deviation, and c is the number of generated data. . Use np.arange(a,b,c) to determine the range and spacing of the x-axis of the histogram. a is the minimum value, b is the maximum value, and c is the spacing. Use plt.hist(a,b) to draw, a is the data, b is the characteristic of the histogram, which is optional.
import matplotlib.pylab as plt import numpy as np da = np.random.normal(5.0, 0.5, 3000) dis = np.arange(3.5, 5, 0.1) plt.hist(da, dis) plt.show()
2. When drawing a subplot, we need to divide the space into several parts first. In this case, we need to use the command plt.subplot(a,b,c), where a represents the row, b represents the column, and c Represents the current area starting from the first line and counting from left to right to c. For example, if you want to draw three subplots in the first row and one subplot in the second row, you need to use the following code
import matplotlib.pylab as plt import numpy as np plt.subplot(2, 3, 1) plt.subplot(2, 3, 2) plt.subplot(2, 3, 3) plt.subplot(2, 1, 2) plt.show()
3. After the area splitting is completed, how should we draw the corresponding image in each area? We used the code to split the area into four parts earlier. If we want to draw in a certain area, we only need to write the drawing code under the code of that part.
import matplotlib.pylab as plt import numpy as np plt.subplot(2, 3, 1) #下面的语句绘制第一个子图 x1 = [1, 3, 5, 7, 9, 11] y1 = [2, 4, 6, 8, 10, 12] plt.plot(x1, y1, 'c') plt.subplot(2, 3, 2) #下面的语句绘制第二个子图 x2 = [3, 5, 6, 7, 9, 13, 20] y2 = [1, 6, 2, 3, 5, 7, 11] plt.plot(x2, y2, 'ob') plt.subplot(2, 3, 3) #下面的语句绘制第三个子图 x3 = [2, 5, 7, 8, 10, 11] y3 = [3, 5, 4, 1, 15, 10] plt.plot(x3, y3, '-.') plt.plot(x3, y3, 's') plt.subplot(2, 1, 2) #下面的语句绘制第四个子图 da = np.random.normal(5.0, 0.5, 3000) dis = np.arange(3.5, 5, 0.1) plt.hist(da, dis) plt.show()
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