Data visualization

# Draw a simple line chart 

import matplotlib.pyplot as plt
squares = [1,4,9,16,25]
#  Draw one or more charts in a picture 
fig,ax = plt.subplots()
# print(fig,ax)
# >>>Figure(640x480) AxesSubplot(0.125,0.11;0.775x0.77)

#  According to Chinese 
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']

#  Charting 
ax.plot(squares,linewidth=3)  # linewidth Set the line thickness 

#  Set chart title , Horizontal and vertical axis description 
ax.set_title(' Square number ',fontsize=24)
ax.set_xlabel(' value ',fontsize=14)
ax.set_ylabel(' square ',fontsize=14)
#  Set the scale mark size 
ax.tick_params(axis='both',labelsize=14)
plt.show()

#  Correct the figure 
#  towards plot() Provide a series of hours , It assumes that the first data point corresponds to x Coordinate for 0, This will cause inaccurate graphics 
#  The solution is to provide both input and output values 
# mpl_squares.py

mpl_squares.py

import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']

input_values = [1,2,3,4,5]
squares = [1,4,9,16,25]

#  Use built-in styles 
plt.style.use('bmh')
fig,ax = plt.subplots()
ax.plot(input_values,squares,linewidth=3)

#  Set chart title , Horizontal and vertical axis description 
ax.set_title(' Square number ',fontsize=24)
ax.set_xlabel(' value ',fontsize=14)
ax.set_ylabel(' square ',fontsize=14)
#  Set the scale mark size 
ax.tick_params(axis='both',labelsize=14)

plt.show()

# Use built-in styles 
print(plt.style.available)

['Solarize_Light2', '_classic_test_patch', 'bmh', 'classic', 'dark_background', 'fast', 'fivethirtyeight', 'ggplot', 'grayscale', 'seaborn', 'seaborn-bright', 'seaborn-colorblind', 'seaborn-dark', 'seaborn-dark-palette', 'seaborn-darkgrid', 'seaborn-deep', 'seaborn-muted', 'seaborn-notebook', 'seaborn-paper', 'seaborn-pastel', 'seaborn-poster', 'seaborn-talk', 'seaborn-ticks', 'seaborn-white', 'seaborn-whitegrid', 'tableau-colorblind10']

#  Use scatter() Draw a scatter plot 
# catter_squares.py

catter_squares.py

import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']

plt.style.use('bmh')
fig,ax = plt.subplots()
ax.scatter(2,4,s=200)  # s=200  It refers to the size of the point 
ax.set_title(' Square number ',fontsize=24)
ax.set_xlabel(' value ',fontsize=14)
ax.set_ylabel(' square ',fontsize=14)

ax.tick_params(axis='both',which='major',labelsize=14)

plt.show()

#  Auto save chart 
# plt.savefig(" file name .png",bbox_inches='tight') # bbox_inches='tight' Whether to keep the extra blank area of the chart , Keep it without writing this parameter 

#  Random walk 
"""  establish RandomWalk class  random_walk.py  It randomly chooses the direction of travel   Three attributes   The variable of the number of random walks   Two lists , Store the... Of each point that the random walk passes through separately x Coordinates and y coordinate  fill_walk() Method calculate all points that random walk passes  """

'\n establish RandomWalk class  random_walk.py\n It randomly chooses the direction of travel \n Three attributes \n     The variable of the number of random walks \n     Two lists , Store the... Of each point that the random walk passes through separately x Coordinates and y coordinate \nfill_walk() Method calculate all points that random walk passes \n'

random_walk.py

from random import choice

class RandomWalk:
    """ A class that generates random walk data """
    def __init__(self,num_points=5000):
        """ Initialize random walk properties """
        self.num_points = num_points
        #  All random walks begin with (0,0)
        self.x_values = [0]
        self.y_values = [0]

    def fill_walk(self):
        """ Calculate all the points included in the random walk """
        #  Keep walking , Until the list reaches the specified length 
        while len(self.x_values) <self.num_points:
            #  Determine the direction and distance to go 
            x_direction = choice([1,-1])
            x_distance = choice([0,1,2,3,4])
            x_step = x_direction * x_distance

            y_direction = choice([1,-1])
            y_distance = choice([0,1,2,3,4])
            y_step = y_direction * y_distance

            #  Refuse to step in place 
            if x_step == 0 and y_step == 0 :
                continue

            #  Calculate the... Of the next point x, and y value 
            x = self.x_values[-1] + x_step
            y = self.y_values[-1] + y_step

            self.x_values.append(x)
            self.y_values.append(y)

#  Draw a random walk diagram 
# rw_visual.py

rw_visual.py

#  Draw a scatter diagram of random walk 

import matplotlib.pyplot as plt
from random_walk import RandomWalk
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']

plt.style.use('classic')
while True:
    rw = RandomWalk(50_000)
    rw.fill_walk()

    fig,ax = plt.subplots(figsize=(15,9))  # figsize=(15,9) Used to specify dimensions   In inches 
    point_numbers = range(rw.num_points)
    ax.scatter(rw.x_values,rw.y_values,c=point_numbers,  #  Apply color mapping and remove outline colors 
               cmap=plt.cm.Blues,edgecolors='none',s=1)

    #  Redraw the start and end points 
    ax.scatter(0,0,c='green',edgecolors='none',s=100)
    ax.scatter(rw.x_values[-1], rw.y_values[-1], c='red', edgecolors='none', s=100)
    #  Hide axis 
    ax.get_xaxis().set_visible(False)
    ax.get_yaxis().set_visible(False)
    # ax.plot(rw.x_values,rw.y_values)
    plt.show()

    keep_running = input(' Whether or not to continue  Y/N?')
    if keep_running.lower() == 'n':
        break

 Whether or not to continue  Y/N?n

#  Use plotly Simulate rolling dice 
#  When you need to create a chart displayed in the browser ,Plotly It is useful to ,
#  The charts it generates are interactive 

#  Create a class that represents dice  die.py
#  Visualization of dice  die_visual.py

die.py

from random import randint
class Die:
    """ Represents a class of dice """
    def __init__(self,num_sides=6):
        """ Dice default to 6 Noodles """
        self.num_sides = num_sides

    def roll(self):
        """ Return to one 1, To the random value of the number of dice faces """
        return randint(1,self.num_sides)

die_visual.py

from plotly.graph_objs import Bar,Layout
from plotly import offline
from die import Die

#  Create a D6
#  Simultaneous throw 2 Dice 
die_1 = Die()
die_2 = Die(10)
#  Roll the dice several times and save the results in a list 
results = []
for roll_num in range(10000):
    results.append(die_1.roll() + die_2.roll())

# print(results)
max_result = die_1.num_sides + die_2.num_sides
frequencies = [results.count(x) for x in range(2,max_result+1)]
# print(frequencies)
# print(1/6)

#  Visualize the results 
x_values = list(range(2,max_result+1))
data = [Bar(x=x_values,y=frequencies)]

x_axis_cofig = {
    'title':' result ','dtick':1}
y_axis_cofig = {
    'title':' The frequency of the results '}

my_layout=Layout(title=" throw 1 individual D6, One D10  dice  10000 Results of ",
                 xaxis=x_axis_cofig,yaxis=y_axis_cofig)

offline.plot({
    'data':data,'layout' : my_layout}, filename='d6.html')

'd6.html'

---

ref: 《python Programming from entry to practice 》（ The second edition ）