matplotlib is inspired by MATLAB. Matlab is a widely used language and tool in the field of data drawing. MATLAB language is process oriented. Using function call, matlab can easily use a line of command to draw lines, and then use a series of functions to adjust the results.

Matplotlib has a set of drawing interface which completely imitates the function form of MATLAB in the matplotlib.pyplot module. This set of function interface is convenient for matlab users to transition to Matplotlib package

Official website
Learning method: start from the official website examples
learn
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• http://matplotlib.org/examples/index.html
• http://matplotlib.org/gallery.html

import matplotlib.pyplot as plt

Figure: panel (Figure). All the images in matplotlib are located in Figure object. An image can only have one figure object.
Plot: sub plot. One or more plot objects (axes) are created under the figure object to draw the image.

• Configuration parameters:

• Line related property tag settings

• Line marking

• colour

• Background color

By providing an axis BG parameter to methods such as matplotlib.pyplot.axes() or matplotlib.pyplot.subplot(), you can specify the background color of the coordinate.
subplot(111,axisbg=(0.1843,0.3098,0.3098))

pi**

Drawing operation steps (take point drawing and line drawing as examples)

# Import into storage
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator

# Using numpy to generate data
x = np.arange(-5, 5, 0.1)
y = x*3

# Create windows, subgraphs
# Method 1: create a window first, and then create a sub graph. (must be drawn)
fig = plt.figure(num=1, figsize=(15, 8), dpi = 80)
ax1 = fig.add_subplot(2, 1, 1)   # Add the subgraph through fig. parameters: number of rows, number of columns, the first few.
ax2 = fig.add_subplot(2, 1, 2)
print(fig, ax1, ax2)

# Method 2: create windows and multiple subgraphs at once. (blank not drawn)
fig, axarr = plt.subplots(4, 1)  # Open a new window, add 4 subgraphs and return to the array of subgraphs
ax1 = axarr[0] # Get a subgraph from the subgraph array
print(fig, ax1)

# Method 3: create a window and a subgraph at once. (blank not drawn)
ax1 = plt.subplot(1, 1, 1, facecolor='white')  # Open a new window and create a sub graph. facecolor sets the background color
print(ax1)

# Get the reference to the window, which is applicable to the above three methods
# fig = plt.gcf()   # Get the current figure
# fig=ax1.figure   #Get the window to which the specified sub graph belongs

# fig.subplots_adjust(left=0)                         #Set the left inner margin of the window to 0, that is, leave the left blank to 0

# Set the basic elements of the subgraph
ax1.set_title("python-drawing")  # Set up body, plt.title
ax1.set_xlabel("X—name")         # Set x-axis name, plt.xlabel
ax1.set_ylabel('y-name')         # Set y-axis name, plt.ylabel
plt.axis([-6, 6, -10, 10])       # Set the range of abscissa and ordinate axis, which is divided into the following two functions in the subgraph
ax1.set_xlim(-5, 5)              # Setting the horizontal axis range will cover the above horizontal coordinate, plt.xlim
ax1.set_ylim(-10, 10)            # Setting the vertical axis range will cover the above vertical coordinate, plt.ylim

xmajorLocator = MultipleLocator(2)   # Defines the scale difference of the horizontal major scale label as a multiple of 2. It's just a few ticks apart to display a label text
ymajorLocator = MultipleLocator(3)   # Defines the scale difference of the vertical major scale label as a multiple of 3. It's just a few ticks apart to display a label text

ax1.xaxis.set_major_locator(xmajorLocator)  # The x axis applies the defined horizontal major scale format. Default scale format if not applied
ax1.yaxis.set_major_locator(ymajorLocator)  # The y-axis applies the defined vertical major scale format. Default scale format if not applied

ax1.xaxis.grid(True, which='major')      # Grid of x axis uses defined major scale format
ax1.yaxis.grid(True, which='major')      # Grid of y axis uses defined major scale format

ax1.set_xticks([])     # Remove axis scale
ax1.set_xticks((-5,-3,-1,1,3,5))  # Set axis scale
ax1.set_xticklabels(labels=['x1','x2','x3','x4','x5'],rotation=-30,fontsize='small')  # Set the display text of scale, rotation angle, font size

plot1=ax1.plot(x, y, marker='o', color='g', label='legend1')   # Point drawings: marker icons
plot2=ax1.plot(x, y, linestyle='--', alpha=0.5, color='r', label='legend2')   # Line chart: linestyle linear, alpha transparency, color color, label legend text

ax1.legend(loc='upper left')              # Display legend, plt.legend()
ax1.text(2.8, 7, r'y=3*x')                # Display text at specified position, plt.text()
ax1.annotate('important point', xy=(2, 6), xytext=(3, 1.5),  # Add dimensions, parameters: annotation text, pointing point, text position, arrow attribute
            arrowprops=dict(facecolor='black', shrink=0.05),
            )
# Displays the grid. The values of which parameter are major (only draw large scale), minor (only draw small scale), and both. The default value is major. axis is' x','y','both '
ax1.grid(b=True, which='major', axis='both', alpha= 0.5, color='skyblue', linestyle='--', linewidth=2)

axes1 = plt.axes([.2, .3, .1, .1], facecolor='y')  # Add a subgraph in the current window, rect = [left, bottom, width, height], which is the absolute layout used, and do not occupy space with the existing window
axes1.plot(x, y)  # Draw a picture on a subgraph
plt.savefig('aa.jpg',dpi=400,bbox_inches='tight')   # savefig saves the picture, dpi resolution, and the size of white space around bbox  includes subgraph
plt.show()    #Open the window. For the window created by method 1, the drawing must be done. For the window created by method 2, method 3, if all coordinate systems are blank, the drawing will not be done

The attributes that can be set during plot include the following:

Multiple graphs in one window

#One window, multiple graphs, multiple data
sub1=plt.subplot(211,facecolor=(0.1843,0.3098,0.3098))  #Divide the window into 2 lines and 1 column, draw in the first one, and set the background color
sub2=plt.subplot(212)   #Divide the window into 2 lines and 1 column, and draw in the second
sub1.plot(x,y)          #Drawing subgraph
sub2.plot(x,y)          #Drawing subgraph

axes1 = plt.axes([.2, .3, .1, .1], facecolor='y')  #Add a sub coordinate system, rect = [left, bottom, width, height]
plt.plot(x,y)           #Draw the sub coordinate system,
axes2 = plt.axes([0.7, .2, .1, .1], facecolor='y')  #Add a sub coordinate system, rect = [left, bottom, width, height]
plt.plot(x,y)
plt.show()

polar coordinates
Property settings are the same as in point and line drawings

fig = plt.figure(3)                                #Open a new window
ax1 = fig.add_subplot(1,2,1,polar=True)                  #Start a polar subgraph
theta=np.arange(0,2*np.pi,0.02)              #Angle series value
ax1.plot(theta,2*np.ones_like(theta),lw=2)   #Drawing, parameters: angle, radius, lw line width
ax1.plot(theta,theta/6,linestyle='--',lw=2)           #Drawing, parameters: angle, radius, linestyle style, lw line width

ax2 = fig.add_subplot(1,2,2,polar=True)                  #Start a polar subgraph
ax2.plot(theta,np.cos(5*theta),linestyle='--',lw=2)
ax2.plot(theta,2*np.cos(4*theta),lw=2)

ax2.set_rgrids(np.arange(0.2,2,0.2),angle=45)   #Distance from grid axis, axis scale and display position
ax2.set_thetagrids([0,45,90])                   #Angle grid axis, range 0-360 degrees

plt.show()Insert code piece here

Cylindrical graph
Property settings are the same as in point and line charts.

plt.figure(4)
x_index = np.arange(5)   #Column index
x_data = ('A', 'B', 'C', 'D', 'E')
y1_data = (20, 35, 30, 35, 27)
y2_data = (25, 32, 34, 20, 25)
bar_width = 0.35   #Define a number to represent the width of each individual column

rects1 = plt.bar(x_index, y1_data, width=bar_width,alpha=0.4, color='b',label='legend1')            #Parameters: left offset, height, column width, transparency, color, legend
rects2 = plt.bar(x_index + bar_width, y2_data, width=bar_width,alpha=0.5,color='r',label='legend2') #Parameters: left offset, height, column width, transparency, color, legend
#As for the left offset, it is not necessary to care about the centrality of each column, because it is only necessary to set the scale line in the middle of the column
plt.xticks(x_index + bar_width/2, x_data)   #x-axis tick mark
plt.legend()    #Show Legend
plt.tight_layout()  #This method can't control the space between images very well
plt.show()

iv>

* histogram
*

fig,(ax0,ax1) = plt.subplots(nrows=2,figsize=(9,6))     #Add 2 subgraphs to the window
sigma = 1   #standard deviation
mean = 0    #mean value
x=mean+sigma*np.random.randn(10000)   #Random number of normal distribution
ax0.hist(x,bins=40,normed=False,histtype='bar',facecolor='yellowgreen',alpha=0.75)   #Normalization, histogram type, facecolor, alpha transparency
ax1.hist(x,bins=20,normed=1,histtype='bar',facecolor='pink',alpha=0.75,cumulative=True,rwidth=0.8) #The number of bins columns, whether cumulative distribution is calculated, rwidth column width
plt.show()  #All Windows running

Scatter plot

fig = plt.figure(6)          #Add a window
ax =fig.add_subplot(1,1,1)   #Add a subgraph to the window
x=np.random.random(100)      #Generate random array
y=np.random.random(100)      #Generate random array
ax.scatter(x,y,s=x*1000,c='y',marker=(5,1),alpha=0.5,lw=2,facecolors='none')  #x abscissa, y ordinate, s image size, c color, marker picture, lw image border width
plt.show()  #All Windows running

Three dimensional graph

fig = plt.figure(5)
ax=fig.add_subplot(1,1,1,projection='3d')     #Draw 3D

x,y=np.mgrid[-2:2:20j,-2:2:20j]  #Get x-axis data, y-axis data
z=x*np.exp(-x**2-y**2)   #Get z-axis data

ax.plot_surface(x,y,z,rstride=2,cstride=1,cmap=plt.cm.coolwarm,alpha=0.8)  #Drawing 3D surfaces
ax.set_xlabel('x-name')     #x axis name
ax.set_ylabel('y-name')     #y axis name
ax.set_zlabel('z-name')     #z axis name

plt.show()

Draw rectangles, polygons, circles, and ellipses

fig = plt.figure(8)   #Create a window
ax=fig.add_subplot(1,1,1)   #Add a subgraph
rect1 = plt.Rectangle((0.1,0.2),0.2,0.3,color='r')  #Create a rectangle with parameters: (x,y),width,height
circ1 = plt.Circle((0.7,0.2),0.15,color='r',alpha=0.3)  #Create an ellipse. Parameters: center point, radius. By default, the circle will be compressed with the window size
pgon1 = plt.Polygon([[0.45,0.45],[0.65,0.6],[0.2,0.6]])  #Create a polygon, parameters: coordinates of each vertex

ax.add_patch(rect1)  #Add shapes to child diagrams
ax.add_patch(circ1)  #Add shapes to child diagrams
ax.add_patch(pgon1)  #Add shapes to child diagrams

fig.canvas.draw()  #Subgraph rendering
plt.show()