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Today, the editor will share with you the relevant knowledge points about how to draw line charts and bar charts in python. The content is detailed and the logic is clear. I believe most people still know too much about this knowledge, so share this article for your reference. I hope you can get something after reading this article.

Line chart

When the values of import matplotlib.pyplot as plt#x axes are different # x1 = [0PEM 0.1ret 0.3Regy 0.7Regy 0.8WE 0.9] # y1 = [0.71500.147Met 0.7088] # y1 = [0.996WH 0.6942pr 0.5599] # x2 = [0Mie 0.1Me 0.2pr 0.5pr 0.6pr 0.8pr 0.9re1] # y2= [0.71500.146pr 0.696pr 0.696recorder 0.3344] # x3 = [0prima 0.1pr 0.2pr 0.2pr 0.3rect 0.4ther 0.7ther 0.6ther 0.4ther 0.7ther 0.7cet 0.8cet 0.981] # y3 = [0.7150pr 0.7147e 0.7147pr 0.147e .7068, 0.7016, 0.6283, 0.5889, 0.5155, 0.4992, 0.4728, 0.3909, 0.3310) # when the x-axis has the same value, x = [1. ] y1 = [57pje 74pyrrt6] y1 = [57pje 74pyrm 69pyrm 82pr 99pr 99] y2 = [44pr 57pr 48pr 55pr 56pr 79] y3 = [61pl 7pr 59pr 59pr 59pr 598pl 588pr 588J 588J 548pcm68j81] plt.title ('courier monthly quantity') # line chart title plt.rcParams ['font.sans-serif'] = [' SimHei'] # line chart when Chinese characters need to be displayed Add this line plt.xlabel ('month / month') # x-axis title plt.ylabel ('number of couriers') # y-axis title plt.plot (x, y1, marker='o', markersize=3) # draw a line chart Add data point shape and set point size plt.plot (x, y2, marker=' ^', markersize=3) # ^: point shape is triangular plt.plot (x, y3, marker='*', markersize=3) # star for a, b in zip (x, y1): plt.text (a, b, b, ha='center', va='bottom', fontsize=10) # set data label position and font size for a, b in zip (x, y2): plt.text (a B, b, ha='center', va='bottom', fontsize=10) for a, b in zip (x, y3): plt.text (a, b, b, ha='center', va='bottom', fontsize=10) plt.legend (['Post', 'Shun Feng', 'Yuantong']) # set the line name plt.show () # display the line chart

Results:

Single bar graph

When the import matplotlib.pyplot as plt# bar chart needs to be displayed in Chinese You need the following two lines of code plt.rcParams ['font.sans-serif'] = [' SimHei'] plt.rcParams ['axes.unicode_minus'] = Falsequarters = (' first section', 'second quarter', 'third quarter', 'fourth quarter') # x-axis courier_number = [310,382,256,402] # number of x-axis plt.bar (quarters, courier_number) # drawing # plt.barh (quarters) Courier_number) # to put a bar chart horizontally Use the function barhplt.title ('results of the survey on the number of express deliveries in four quarters') # bar chart title plt.show ()

Results:

Juxtaposed bar chart

When the import matplotlib.pyplot as pltimport numpy as np# bar chart needs to be displayed in Chinese You need the following two lines of code plt.rcParams ['font.sans-serif'] = [' SimHei'] plt.rcParams ['axes.unicode_minus'] = False# to enter statistics quarters = (' first section', 'second quarter', 'third quarter', 'fourth quarter') # x-axis courier_number_before = [310,382,256,402] courier_number_now = [320,420,388 432] bar_width = 0.3 # set bar width index_before = np.arange (len (quarters)) # Abscissa of the previous fourth quarter bar index_now = index_before + bar_width # now the Abscissa of the fourth quarter bar chart # use the bar function twice to draw two sets of bar charts plt.bar (index_before, height=courier_number_before, width=bar_width, color='b', label=') plt.bar (index_now, height=courier_number_now) Width=bar_width, color='g', label=' this year') plt.legend () # display legend plt.xticks (index_before + bar_width/2, quarters) # Let the Abscissa scale show the express volume for four quarters Index_before + bar_width/2 is the position of the horizontal axis scale plt.ylabel ('number of deliveries') # ordinate axis title plt.title ('results of the survey on the number of deliveries in the four quarters of last year') # graphic title plt.show ()

These are all the contents of the article "how to draw line charts and bars in python". Thank you for reading! I believe you will gain a lot after reading this article. The editor will update different knowledge for you every day. If you want to learn more knowledge, please pay attention to the industry information channel.

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