This is my participation 11 The fourth of the yuegengwen challenge 16 God , Check out the activity details ：2021 One last more challenge

Preface

as everyone knows ,matplotlib.pyplot Provide different table drawing methods , If you use plot() Method to draw a polyline ,bar() Draw a histogram ,hist() Draw histogram, etc , For details on their use, please see the following link .

• matplotlib Draw line chart ： Summarize and explain the related attributes of line chart

• matplotlib Draw a histogram ： Summarize and explain the relevant attributes of the histogram

• matplotlib Draw histogram ： Summarize and explain the histogram related attributes

• matplotlib Draw a scatter plot ： Summarize and explain the relevant attributes of scatter chart

• matplotlib Draw contour map ： Summarize and explain the relevant attributes of contour map

stay matplotlib.pyplot There is also a pie chart in which the proportion is visually represented , stay matplotlib The official website also lists many cases about pie charts .

In this issue , We will study in detail matplotlib Drawing pie chart related attributes of learning ,let's go~

1. Contour map Overview

• What is a pie chart ？

  • The pie chart shows the ratio of the size of each item to the sum of the total items in a circle
  • Pie charts are displayed through different sizes , To determine the proportion of each item
  • Data markers of the same color in the pie chart form a data series
  • Pie charts can be divided into three-dimensional pie charts 、 Composite pie chart 、 Split pie chart

• Pie chart common scenarios

  • The pie chart can be used to determine the composition ratio of each part temporarily
  • The pie chart can reflect the proportion of various indicators in a dimension in the overall
  • Pie chart is suitable for only looking at the general proportion , Don't worry about data accuracy

• To draw an isopach

  1. Import matplotlib.pyplot modular
  2. Prepare the data , have access to numpy/pandas Collating data
  3. call pyplot.pie() Draw the pie chart
  4. call axis Method adjustment x/y The shaft spacing is equal

• The case shows

  In this issue , We will apply pie chart to analyze the market share of operating system

  • Case data preparation ： Use random.randint produce 5 A numerical

    import numpy as np
    size = np.random.randint(0,100,5)
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  • Draw the pie chart

    import matplotlib.pyplot as plt\
    
    plt.pie(size,labels=["Windows","MAC","Linux","Android","Other"])
    
    plt.title(" Analysis on the proportion of mobile phone system ")
    
    plt.show()
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2. Pie chart properties

• Set the color of the pie chart

  • keyword ：colors
  • Optional values ：None Or a list of colors
  • The color list can consist of the following ：
    • English words for color ： Like red "red"
    • Abbreviations of words indicating color, such as ： Red "r", yellow "y"
    • RGB Format ： Hexadecimal format, such as "#88c999";(r,g,b) Tuple form

• Set the label

  • keyword ：labels
  • The default is ：None
  • You need to pass in a value in the form of a list

• Set the protrusion

  • keyword ：explode
  • The default is ：None
  • Need to pass in list data
  • If the value is set , The specified part is highlighted

• Set the fill percentage value

  • keyword ：autopct
  • The default is ：None
  • Optional value form ：
    • Format string, such as ：'%1.1f%%'
    • function ： You can call the function content

• Pie chart rotation

  • from x The shaft rotates counterclockwise ：startangle; The default is 0, Floating point type
  • Specify the fractional direction clockwise ：counterclock; The default is True,bool type

• Set shadow

  • keyword ：shadow
  • The default is False
  • Draw a shadow under the pie chart

• Let's add some attributes in combination with the case in Section 1 , The proportion value needs to be displayed , Color displays the specified color , prominent MAC Proportion

  plt.pie(size,labels=["Windows","MAC","Linux","Android","Other"],
  autopct="%1.1f%%",
  explode=[0,0.1,0,0,0],
  colors=("r","blue","#88c999",(1,1,0),"0.5"))
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3. Resize the pie chart

When we actually make pie charts , You will encounter changing the size of the pie chart , This is what we can do with the pie chart attribute keyword radius

• radius: Set the pie chart radius size

besides , We also need to use textprops To control the size of the displayed labels

plt.pie(size,labels=["Windows","MAC","Linux","Android","Other"],autopct="%1.1f%%",
explode=[0,0.1,0,0,0],
colors=("r","blue","#88c999",(1,1,0),"0.5"),radius=0.5,textprops={'size':"smaller"})
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4. Add legend

When we show the proportion of each item in the pie chart , A set of legends will be added next to the chart .

• pyplot.pie() Method will return patchee.Wedge list 、 Text list and other data
• pyplot.legend() Methods the incoming wedge Element and specified labels label
• At the same time, you can work with legend() Method bbox_to_anchor To set the location of the legend

La = ["Windows","MAC","Linux","Android","Other"]

def f(pct,n):
    num = int(round(pct*np.sum(n)))
    return "{:.1f}%\n{:d}w".format(pct,num)

wedges ,text,autotexts =plt.pie(size,autopct=lambda pct: f(pct,size),
        colors=("r","blue","#88c999",(1,1,0),"0.5"),textprops=dict(color='w'))

plt.legend(wedges,La,loc="right",bbox_to_anchor=(1,0,0.3,1))
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5. Hollowed out pie chart

In the pie chart , We sometimes use nested hollowed out pie charts .

• Nesting can be called multiple times pyplot.pie() Method
• Hollowing out can be done with the help of pyplot.pie() attribute wedgeprops To set it up
• wedgeprops={"width":0.3,"edgecolor":'w'}

cmap = plt.get_cmap("tab20c")
plt.pie(size,
         colors=("r","blue","#88c999",(1,1,0),"0.5"),textprops=dict(color='w'),wedgeprops=dict(width=0.3,edgecolor='w'))
plt.pie(size,
         colors= cmap(np.arange(3)*5),radius=0.7,wedgeprops=dict(width=0.3,edgecolor='w'),textprops={'size':"smaller"})
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summary

In this issue , Yes matplotlib.pyplot Draw the pie chart pie() Learning related attributes . When drawing pie charts , We will change the size of the pie chart according to the actual needs , Nesting pie charts 、 Add graphics such as histogram to assist in viewing

The above is the content of this issue , Welcome big guys to praise and comment , See you next time ~