[song] rebirth of me in py introductory training (12): Matplotlib interface and common graphics

It's not easy to create , Before reference , Point a praise , Collection , You can't pay too much attention , Family

The first 1 Turn off ： Drawing interface

Task description

Our mission ： master matplotlib Basic tips for using , And can be used simply matplotlib Visualizing .-

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Programming requirements

On the right editor Begin-End Supplementary code , The incoming x,y Make a line chart with two arrays ,x Corresponding x Axis ,y Corresponding y Axis . And save to Task1/image1/T2.png, The specific requirements are as follows ：

• Line graph figsize by (10, 10);

• The file named Task1/image1/T2.png.

      # ********** Begin *********#
      fig = plt.figure(figsize=(10,10))
      plt.savefig("Task1/image1/T2.png")
      plt.show()
      # ********** End **********#

The first 2 Turn off ： Linear chart

Task description

Our mission ： Learn to master matplotlib The first graphic line graph of , And can use the commonly used linear configuration .

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Programming requirements

On the right editor Begin-End Supplementary code , According to the input data input_data,input_data1 Draw two line charts . Set the color style for the two groups of data in turn as --g,:r; Set legend to L1,L2, The specific requirements are as follows ：

• Line graph figsize by (10, 10);

• Save drawing to Task2/img/T1.png.

  def student(input_data,input_data1):
  
      # ********* Begin *********#
      fig = plt.figure(figsize=(10,10))
      plt.plot(input_data,'--g')
      plt.plot(input_data1,':r')
      plt.legend(['L1','L2'])
      plt.savefig("Task2/img/T1.png")
      plt.show()
  
      # ********* End *********#

The first 3 Turn off ： Scatter plot

Task description

Our mission ： Write a scatter chart with three different styles .

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Programming requirements

Add code to the editor on the right , According to the three groups of input data, draw three groups of scatter diagrams with different parameters , The specific requirements are as follows ：

• The first set of data parameters sets the tag size to area, Transparency is 0.5;

• The second set of data parameters sets the tag size to area, The marking color is green , Transparency is 0.6;

• The third set of data parameters sets the tag size to area, The marking color is area, The tag style is v, Transparency is 0.7;

• Graphic figsize by (10, 10);

• Save drawing to Task3/img/T1.png.

    :return: None
    '''
    # ********* Begin *********#
    fig = plt.figure(figsize=(10,10))
    plt.scatter(x,y,s = area, alpha = 0.5)
    plt.scatter(x2,y2,s = area, c = 'g', alpha = 0.6)
    plt.scatter(x3,y3,s = area, marker = 'v', alpha = 0.7)
    plt.savefig("Task3/img/T1.png")
    plt.show()

    # ********* End *********#

The first 4 Turn off ： Histogram

Task description

Our mission ： Draw a graph containing histogram and linear graph .

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Programming requirements

On the right editor Begin-End Add the code , According to the input data, the histogram and linear graph are drawn in the same panel , And set the histogram to red , The line graph is blue , The specific requirements are as follows ：

• Graphic figsize by (10, 10);

• The file named Task4/img/T1.png.

 :return: None
    '''
    # ********* Begin *********#
    fig = plt.figure(figsize=(10,10))
    plt.hist(data,facecolor="red")
    plt.plot(x,y,color="blue")
    plt.savefig("Task4/img/T1.png")
    plt.show()

    # ********* End *********#

The first 5 Turn off ： The pie chart

Task description

Our mission ： Draw a pie chart .

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Programming requirements

On the right editor Begin-End Add the code , According to the input data labels、quants Draw the pie chart , And set the second block to highlight 0.1 And display the percentage of each block , The specific requirements are as follows ：

• input data labels、quants For a length of 10 A list of

• Graphic figsize by (6, 6)

• The file named Task5/img/T1.png

• def student(labels,quants):
      # ********* Begin *********#
      fig=plt.figure(figsize=(6,6))
      sizes = quants
      plt.pie(sizes,labels=labels,explode=(0,0.1,0,0,0,0,0,0,0,0),autopct='%1.1f%%')
      plt.savefig("Task5/img/T1.png")
      plt.show()
      # ********* End *********#
  

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