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Python matplotlib is how to draw, many novices are not very clear about this, in order to help you solve this problem, the following small series will explain in detail for everyone, there are people who need this can learn, I hope you can gain something.

1. Introduction of matpltlib library

matplotlib is an excellent Python data visualization third-party library

When drawing with matpltlib library, first introduce it, load pyplot inside, and name it plt, and then use plot function to draw

import matplotlib.pyplot as plt #plt is an alias for the imported module 2.pyplot Basic Icon Function Summary

3. Plot function drawing syntax rules

plot function parameters: plot([x],y,[format],**kwargs)

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4. line chart

from matplotlib import pyplot as plt

#generated data #abscissa data from 2017 to 2022, the third parameter can control the step size, can write or not write x = range (2017, 2022)#y value corresponding to ordinate y1 = [49, 48, 45, 52, 50]y2 = [60, 62, 61, 65, 63]#generate graph plt.title ("LMY and her mother's weight")plt.xlabel('year')plt.ylabel('kg')plt.plot(x, y1, color='green', label='LMY')plt.plot(x, y2, color='purple', label='mother')plt.grid(alpha=0.5)plt.legend(loc='upper right')#Display graph plt.show()

4. scatter plot

from matplotlib import pyplot as pltimport numpy as np#generate data #abscissa data from 2017 to 2022, the third parameter can control the step size, can be written or not x = range (2017, 2022)# y corresponds to the ordinate value y1 = [49, 48, 45, 52, 50]y2 = [60, 62, 61, 65, 63]#Generate graphics plt.title ("LMY and her mother's weight")plt.xlabel('year')plt.ylabel('kg')#dot size area = np.pi*4**2plt.scatter (x, y1, s=area, c='yellow', alpha=1)plt.scatter(x, y2, s=area, c='blue', alpha=1)plt.legend()plt.yticks(())plt.show()

5. histogram

from matplotlib import pyplot as pltimport numpy as np#generate data #abscissa data from 2017 to 2022, the third parameter can control the step size, can write or not write x = [2017, 2018, 2019, 2020, 2021]# y corresponding to the ordinate value y1 = [49, 48, 45, 52, 50]y2 = [60, 62, 61, 65, 63]#Generate graphics plt.title ("LMY and her mother's weight")plt.ylabel ('frequency ')plt.xlabel ('kg')#Size of point plt.hist (y1, bottom=None, color='purple')plt.hist (y2, bottom=None, color='pink')plt.show()# n, bins, patches = plt.hist (arr, bins=50, normed=1, facecolor='green', alpha=0.75)'''arr: 1-D array to calculate histogram bins: Number of histogram bins, optional, default is 10normed: Normalize the resulting histogram vector, default is 0facecolor: histogram color alpha: transparency''

6. Bar charts

longitudinal

from matplotlib import pyplot as pltimport numpy as nparr = np.arange(2017, 2022)x = [49, 48, 45, 52, 50] #x-axis y = [2017, 2018, 2019, 2020, 2021]rect = plt.bar (arr, x, width=0.5)plt.title('LMY')plt.xlabel('weight') plt.ylabel('year') plt.legend()plt.show()

transverse

plurality of

from matplotlib import pyplot as pltimport numpy as nparr = np.arange(2017, 2022)x1 = [49, 48, 45, 52, 50] #x-axis x2 = [60, 62, 61, 65, 63]y = [2017, 2018, 2019, 2020, 2021]rects1 = plt.bar (arr, x1, 0.5, color='purple', label='LMY')rects2 = plt.bar(arr, x2, 0.5, color='yellow', label='Mother', alpha=0.3)plt.title("LMY and her mother's weight")plt.xlabel('weight')plt.ylabel('year')plt.legend()plt.show()

7. pie chart

from matplotlib import patches, pyplot as pltimport numpy as nplabel_list = ['49',' 48','45',' 52','50'] size = [20, 20, 20, 20]#color = [' red','pink',' blue','green',' purple'] explore = [0, 0, 0.15, 0, 0]patches, l_text, p_text = plt.pie(size, explode=explode, colors=color, labels=label_list, labeldistance=1.2, autopct="%1.2f%%", shadow=False, startangle=90, pctdistance=0.6)plt.axis('equal')plt.title("LMY's weight")plt.legend(loc='upper left')plt.show()

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