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This article mainly introduces "how to use Python matplotlib to achieve a broken line chart". In daily operation, I believe many people have doubts about how to use Python matplotlib to achieve a broken line chart. Xiaobian consulted all kinds of materials and sorted out simple and easy to use operation methods. I hope to help you answer the doubts about "how to use Python matplotlib to achieve a broken line chart"! Next, please follow the small series to learn together!

I. Version # 01 matplotlib installation import matplotlib matplotlib.__ version__II. Chart theme setting

Please click: Chart Theme Settings

import numpy as np from matplotlib import pyplot as plt #How to use Chinese title plt.rcParams <$'font.sans-serif']=<$'Microsoft YaHei']#Use Microsoft Yahei font x = np.arange(1,11) y = 2 * x + 5 #The picture shows this formula plt.title("Matplotlib display") plt.xlabel("x axis") plt.ylabel("y axis") plt.plot(x,y) plt.show ()

IV. Multiple linear functions

Create a chart about the movie box office:

films="'Embrace You Through Winter,'' G Storm (G) 5: Final Chapter','Li Mao Plays Crown Price',' Mistake 2','Love by Years',' Matrix: Matrix Restart ',' Lion Teen','Magic Full House',' Team Wang makes great contributions to big movie','Love Myth'] regions=[' China','Britain',' Australia ',' US','US',' China','Britain',' Australia ',' US','US'] bos=[' 61,181','44,303',' 42,439','22,984',' 13,979','61,181','44,303','41,439','20,984','19,979']persons=['31','23','56','17','9','31','23','56','17','9']prices=['51','43','56','57','49','51','43','56','57','49']showdate=['2022-12- 03','2022-12- 05','2022-12- 01','2022 -12- 02','2022-11- 05','2022 -12- 03','2022 -12- 05','2022-12- 01','2022 - 12- 02',' 2022-11- 05'] ftypes=['story','Action',' Comedy ',' Drama','Drama',' Love','Action',' Animation'] points=['8.1',' 9.0','7.9',' 6.7','3.8',' 8.1','9.0',' 7.9','6.7',' 3.8'] filmscript ={ 'ftypes':ftypes, 'bos':bos, 'prices':prices, 'persons':persons, 'regions':regions, 'showdate':showdate, 'points':points}import numpy as npimport pandas as pdcnbo2021top5=pd.DataFrame(filmdescript,index=films)cnbo2021top5[['prices','persons']]=cnbo2021top5[['prices','persons']].astype(int)cnbo2021top5['bos']=cnbo2021top5['bos'].str.replace(',','').astype(int)cnbo2021top5['showdate']=cnbo2021top5['showdate'].astype('datetime64')cnbo2021top5['points']=cnbo2021top5['points'].apply(lambda x:float(x) if x!= '' else 0)

About cnboo1.xlsx, I put it in my code cloud, friends who need it download it themselves: cnboo1.xlsx

#read and sort datasets import pandas as pd cnbodf=pd.read_excel ('cnboo1.xlsx') cnbodfsort=cnbodf.sort_values(by=['BO'],ascending=False)

def mkpoints(x,y): #Write points rating return len(str(x))*(y/25)-3cnbodfsort['points']=cnbodfsort.apply(lambda x:mkpoints(x.BO,x.PERSONS),axis=1)

cnbodfsort.to_excel("cnbodfsort.xlsx",index=False) #Create an Excel file from matplotlib import pyplot as plt.rcParams <$'font.sans-serif']=<$'Microsoft YaHei']#Use Microsoft YaHei fonts plt.title("Box Office 2021TOP5") plt.xlabel("x-axis") plt.ylabel("y-axis")x=cnbo2021top5.persons.sort_values()y=cnbo2021top5.prices.sort_values()plt.plot(x,y,marker=". ",markersize=20,color='red',linewidth=4,markeredgecolor='blue')plt.show()

#Line chart progression from matplotlib import pyplot as plt plt.rcParams <$'font.sans-serif']=<$'Microsoft YaHei']#Use Microsoft Yahei font plt.title ("China Box Office 2021TOP5") plt.plot (bo,prices,label ='box office vs. ticket prices') plt.plot (bo,persons,label='box office vs. visits') plt.plot(bo,points,label=' box office vs. evaluations') plt.legend() #display label plt.xlabel ('box office ') #abscissa plt.ylabel ('quotes') #ordinate plt.show()

Change the layout.

#Line chart progression from matplotlib import pyplot as plt plt.rcParams <$'font.sans-serif']=<$'Microsoft YaHei']#Use Microsoft Yahei font plt.title ("China Box Office 2021TOP5") plt.plot (bo,prices,'r^--', label=' box office vs. ticket prices') plt.plot (bo,persons,'g*-', label=' box office vs. persons') plt.plot (bo,points,color ='blue ',marker ='o',markersize=10,label ='box office & evaluation') plt.legend() #display label plt.xlabel ('box office')#abscissa title plt.ylabel ('quotation ') #ordinate title plt.show()

V. Fill the broken line chart

Fill line chart: When determining a point above a data line, you can fill the upper and lower parts of the point with different colors.

dev_x=[25,26,27,28,29,30] #Developer's age dev_y=[7567,8789,8900,11560,16789,25231] #Income py_dev_y=[5567,6789,9098,15560,20789,23231] # Python Developer js_dev_y=[6567,7789,8098,12356, 14789,20231] # java Developer devsalary=pd.DataFrame ([dev_x,dev_y,py_dev_y,js_dev_y])devsalaryT=pd.DataFrame (devsalary.values.T,columns=["Age","Dev","Python","Java"])#Draw shaded line charts from matplotlib import pyplot as plt plt.style. use ('classic')plt.figure (figsize=(7,4))plt.rcParams <$'font.sans-serif']=<$'Microsoft YaHei']#Use Microsoft Elegant Black font plt.title ("Developer Salary") baseline=10000plt.plot (devsalaryT["Age"],devsalaryT["Dev"],label="Total Salary")plt.plot (devsalaryT["Age"],devsalaryT["Python"],label="Python salary") #plt.fill_between that does not display the data label of legend if there is no label (devsalaryT["Age"],devsalaryT["Python"],baseline,where=(devsalaryT["Python"]>baseline),interpolate=True,color='yellow')plt.fill_between (devsalaryT["Age"],devsalaryT["Python"],baseline,where=(devsalaryT["Python"]baseline),interpolate=True,color='yellow',alpha=0.3)plt.fill_between (devsalaryT["Age"],devsalaryT["Python"],baseline,where=(devsalaryT["Python"]baseline),interpolate=True,color='pink',alpha=0.7,label="more than 10000 yuan")plt.fill_between (devsalaryT["Age"],devsalaryT["Python"],baseline,where=(devsalaryT["Python"]baseline),interpolate=True,color='green',alpha=0.7, label="Above Population")plt.fill_between(devsalaryT["Age"],devsalaryT["Python"],devsalaryT["Dev"],where=(devsalaryT["Python"]

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