Examples of line, scatter, bar, histogram, and pie charts using Matplotlib

import  as plt
import random
from pylab import mpl
["-serif"] = ["SimHei"]   # Setting up the display of Chinese fonts
["axes.unicode_minus"] = False   # Setting the normal display symbols
# Data preparation
x = range(24)   
y = [(13, 20) for i in x]   # (): randomly generate floating point numbers in the range 13-20
(figsize=(10, 5), dpi=80)   # Create a canvas
(x, y, color='y', linestyle='-',label='Camphor')   # Plotting line graphs
x_ticks_label = ["{}:00".format(i) for i in x]   # Construct x-axis scale labels
y_ticks = range(40)   # Construct y-axis scales
# Modify the scale display for x,y axis coordinates.
(x[::2], x_ticks_label[::2])
(y_ticks[10:20:1])
(True, linestyle='-', alpha=0.9)   # Add grid
(loc=0)   # Show legend
# Description information
("Time.")
("Temperature.")
("Graph of temperature changes over a 24-hour period.", fontsize=18)
("./")  # Saved to a specified location
()  # Show image

import  as plt
import random
# Data preparation
x = range(100)   
y = [(13, 20) for i in x]   # (): randomly generate floating point numbers in the range 13-20
(figsize=(10, 5), dpi=80)   # Create a canvas
(x, y, color='r', linestyle='-',label='Camphor')   # Plotting line graphs
x_ticks_label = ["{}sky".format(i) for i in x]   # Construct x-axis scale labels
y_ticks = range(25)   # Construct y-axis scales
# Modify the scale display for x,y axis coordinates.
(x[::10], x_ticks_label[::10])
(y_ticks[10:22:2])
(True, linestyle='-', alpha=0.9)   # Add grid
(loc=0)   # Show legend
# Description information
("Time/day")
("Temperature.")
("Graph of temperature changes over a 24-hour period.", fontsize=18)
("./")  # Saved to a specified location
()  # Show image

import  as plt
import random
# Data preparation
x = range(0,10)   
y = [(35, 45) for i in x]   # (): randomly generate floating point numbers in the range 13-20
(figsize=(10, 5), dpi=80)   # Create a canvas
(x, y, width=0.5, color=['b','r','g','y','c','m','y','k','c','g'])   # Plotting line graphs
x_ticks_label = ["21{}classifier for school classes or grades".format(i) for i in x]   # Construct x-axis scale labels
y_ticks = range(55)   # Construct y-axis scales
# Modify the scale display for x,y axis coordinates.
(x[::1], x_ticks_label[::1])
(y_ticks[0:55:5])
(True, linestyle=':', alpha=0.3)   # Add grid
# Description information
("Class.")
("Number of persons")
("Class Size Bar Chart for Class of 2021.", fontsize=18)
("./")  # Saved to a specified location
()  # Show image

import  as plt
import numpy as np
('_mpl-gallery')
# Generate data
(1)   # Random number seed for generating random numbers
x = 4 + (0, 1.5, 200) 
# (loc=0.0, scale=1.0, size=None) for a normal distribution
# loc(float): the mean value, which corresponds to the center of the distribution. loc=0 indicates a normal distribution with the y-axis as the axis of symmetry.
# scale(float): standard deviation, corresponding to the width of the distribution, the larger the scale the shorter and fatter, the smaller the scale, the leaner and taller
# size(int or integer tuple): the value of the output is assigned to the shape, default is None.
# plot:
fig, ax = ()
(x, bins=8, linewidth=0.5, edgecolor="white")
(xlim=(0, 10), xticks=(1, 10),
       ylim=(0, 56), yticks=(0, 56, 9)) # 9, containing 0, spaced at 7, 7 x 8 = 56, i.e. [0,7,14,21,28,35,42,49,56]
# (): return a fixed-step permutation with an end and a start point
# (start, stop, num): used to create an isomorphic series, num is the number
()

import  as plt
# Pie chart where slices will be sorted and plotted in counterclockwise order:
labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'
sizes = [15, 30, 45, 20]
explode = (0, 0.1, 0, 0)  # Decompose only the second slice with a spacing of 0.1
fig1, ax1 = ()
(sizes, explode=explode, labels=labels, autopct='%1.3f%%',colors=['r','y','c','g'], 
        shadow=True, startangle=90)
('equal')  # Equal aspect ratios ensure that the pie is drawn in a circle
()