This is my participation 11 The fourth of the yuegengwen challenge 25 God , Check out the activity details ：2021 One last more challenge

Review

matplotlib yes Python A library dedicated to rendering , We also learned before pyplot Provides drawing polylines 、 Scatter 、 Columnar 、 Square 、 Pie charts and other common images , Also provide animation Class to draw dynamic graph . At the same time, for special charts, such as quantum field diagrams applied in Physics 、 Pay attention to the box diagram of data distribution, etc . Examples of previous articles mentioned above are as follows .

• pyplot.boxplot() Method draw box diagram , Used to show the distribution of data ：matplotlib Draw a box diagram

• pyplot.quiver() Method to draw the quantity field diagram , Commonly used in electromagnetic field analysis ：matplotlib Plot the quantity field

• pyplot.ion() Interaction mode combination for Loops can draw dynamic graphs ：matplotlib Draw a dynamic diagram

• Use animation Class to draw data dynamic graph ：matplotlib Animation class

Following the last time we learned that we can quickly display the median of a set of data 、 The upper and lower quartiles 、 Box diagram of maximum and minimum value pyplot.boxplot() Method . There is also a graphical violin diagram showing the data distribution .

In this issue , We learn matplotlib.pyplot.violinplot Draw violin chart and learn related attributes ,Let's go~

1. Violin overview

• What is the violin picture ？

  • The picture of violin is similar to the shape of violin , It has the characteristics of box diagram and density diagram
  • Violin chart is used to show the density of data distribution and occurrence probability
  • The violin chart shows the median of the same set of data 、 Quartile range 、 density 、95% confidence interval

  

• Violin diagram application scenario

  • The violin diagram can be used to compare the density distribution between different samples
  • The violin chart can be used to show the complete distribution of data
  • Violin charts are often used to sort out discrete data before making accurate charts
  • Cello charts are usually used for gene sample distribution 、 Population age distribution, etc

• How to get violin diagram

import matplotlib.pyplot as plt 
plt.violinplot(dataset)
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2. Violin chart properties

• Set the violin map position

  • keyword ：vert
  • The default value is ：True
  • When vert by True Create a vertical violin diagram
  • When vert by False Create a horizontal violin diagram

• Set the violin width

  • keyword ：width
  • The default value is ：0.5

• Set violin data

  • Set the keyword to display the mean value ：showmeans, The default is False
  • Set the keyword to display extreme value ：showextrema, The default is True
  • Set the keyword to display the median ：showmedians, The default is False

• Set violin style

  • Need to use pyplot.violinplot() Return field “bodies”
  • combination for Loop traversal pyplot.violinplot()["bodies"]
  • call set_facecolor Set the violin color
  • call set_edgecolor Set the violin border color
  • call set_alpha Set the transparency of the violin chart
  • call set_linestyle Set the violin border style

3. To draw a violin diagram

• Import matplotlib.pyplot class

import matplotlib.pyplot as plt
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• Use numpy In the database normal(),random(),randint() And so on data Array vector sequence

data = [np.random.normal(0,2,100)]
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• call pyplot.violinplot(data) Method to draw the violin

part = plt.violinplot(data,showmedians=True)
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• call pyplot.show() Method to render and display the violin chart

plt.show()
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• By using yplot.violinplot() Method return value , Set the color of the violin chart 、 Border styles, etc

for pc in part["bodies"]:
    print(pc)
    pc.set_facecolor("pink")
    pc.set_edgecolor("black")
    pc.set_alpha(1)
    pc.set_linestyle("--")
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4. A profound

We learn to matplotlib The drawing of violin provided violinplot() After the method , Let's practice with scatter combination

• call pyplot.grid() Method to add a mesh to the canvas
• call numpy.percentile() Calculate the next quarter into numbers , Mean number , The upper quarter is divided into numbers
• call pyplot.scatter() Mark the sign of the mean on the violin chart
• call pyplot.vline() Mark the quartile on the violin chart

data = [np.random.normal(0,i,100) for i in range(2,6)]
plt.grid()
part = plt.violinplot(data,showmedians=True,widths=[0.3,0.4,0.5,0.6])
for pc in part["bodies"]:
    print(pc)
    pc.set_facecolor("orange")
    pc.set_edgecolor("black")
    pc.set_alpha(1)
    pc.set_linestyle("--")

q1,me,q3 = np.percentile(data,[25,50,75],axis=1)
ind = np.arange(1,len(me)+1)

plt.scatter(ind,me,marker="o",color="r",s=50,zorder=3)
plt.vlines(ind,q1,q3,color="k",linestyles="-",lw=5)
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summary

In this issue , We are right. matplotlib.pyplot.violinplot() Method to draw violin diagram related attributes . Violin diagram combines the characteristics of box diagram and density diagram , Not only show the distribution of data , It also shows the density of the data .

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