生成数据

绘　　图

参考：https://blog.csdn.net/anneqiqi/article/details/64125186

折线图

import matplotlib.pyplot as plt

squares = [1, 4, 9, 16, 25]
plt.plot(squares)
plt.show()

修改标签文字、线条粗细

import matplotlib.pyplot as plt

squares = [1, 4, 9, 16, 25]
plt.plot(squares, linewidth = 5)

# 设置标签
plt.title("Square Number", fontsize = 24)
plt.xlabel("Value", fontsize = 14)
plt.ylabel("Square of Value", fontsize = 14)

# 设置刻度大小
plt.tick_params(axis = 'both', labelsize = 14)

plt.show()

校正图形

import matplotlib.pyplot as plt

input_values = [1, 2, 3, 4, 5]
squares = [1, 4, 9, 16, 25]
plt.plot(input_values, squares, linewidth = 5)  # 第一个参数为x轴的值即输入值
"""
plot()函数默认第一个数据点为(0, 0)
"""

# 设置标签
plt.title("Square Number", fontsize = 24)
plt.xlabel("Value", fontsize = 14)
plt.ylabel("Square of Value", fontsize = 14)

# 设置刻度大小
plt.tick_params(axis = 'both', labelsize = 14)

plt.show()

使用 scatter() 函数绘制散点图、设置其样式

import matplotlib.pyplot as plt

plt.scatter(2, 4)   # 设置一个坐标
plt.show()

import matplotlib.pyplot as plt

plt.scatter(2, 4, s = 200)   # 设置一个坐标

plt.title("Square Numbers", fontsize = 24)
plt.xlabel("Valve", fontsize = 14)
plt.ylabel("Square of Value", fontsize = 14)

# 设置刻度标记的大小
plt.tick_params(axis = 'both', which = 'major', labelsize = 14)

plt.show()

使用 scatter() 绘制一系列的点

import matplotlib.pyplot as plt

x_values = [1, 2, 3, 4, 5]
y_values = [1, 4, 9, 16, 25]

plt.scatter(x_values, y_values, s = 100)    # s参数表示点的直径

plt.title("Square Numbers", fontsize = 24)
plt.xlabel("Values", fontsize = 14)
plt.ylabel("Square of Value", fontsize = 14)

# 刻度设置
plt.tick_params(axis = 'both', which = 'major', labelsize = 14)

plt.show()

自动计算数据

"""自动计算数据"""

import matplotlib.pyplot as plt

x_values = list(range(1, 1001))
y_values = [x**2 for x in x_values]

plt.scatter(x_values, y_values, s = 4)


plt.title("Square Numbers", fontsize = 24)
plt.xlabel("Values", fontsize = 14)
plt.ylabel("Square of Value", fontsize = 14)

# 设置每个坐标轴的取值范围
plt.axis([0, 1100, 0, 1100000])

plt.show()

删除数据点的轮廓

"""自动计算数据"""

import matplotlib.pyplot as plt

x_values = list(range(1, 1001))
y_values = [x**2 for x in x_values]

plt.scatter(x_values, y_values, edgecolor = 'none', s = 4)
# edgecolor 参数蓝色点黑色轮廓，去掉黑色轮廓后显示为蓝色实心点


plt.title("Square Numbers", fontsize = 24)
plt.xlabel("Values", fontsize = 14)
plt.ylabel("Square of Value", fontsize = 14)

# 设置每个坐标轴的取值范围
plt.axis([0, 1100, 0, 1100000])

plt.show()

自定义颜色

"""自动计算数据"""

import matplotlib.pyplot as plt

x_values = list(range(1, 1001))
y_values = [x**2 for x in x_values]

plt.scatter(x_values, y_values, c = 'red', edgecolor = 'none', s = 4)
# edgecolor 参数蓝色点黑色轮廓，去掉黑色轮廓后显示为蓝色实心点
# c 参数表示颜色，可以用元组 RGB 值表示颜色


plt.title("Square Numbers", fontsize = 24)
plt.xlabel("Values", fontsize = 14)
plt.ylabel("Square of Value", fontsize = 14)

# 设置每个坐标轴的取值范围
plt.axis([0, 1100, 0, 1100000])

plt.show()

使用颜色映射

"""自动计算数据"""

import matplotlib.pyplot as plt

x_values = list(range(1, 1001))
y_values = [x**2 for x in x_values]

plt.scatter(x_values, y_values, c = y_values,cmap = plt.cm.Blues, edgecolor = 'none', s = 4)
# c 参数的值越大，blues 颜色的值越深，渐变


plt.title("Square Numbers", fontsize = 24)
plt.xlabel("Values", fontsize = 14)
plt.ylabel("Square of Value", fontsize = 14)

# 设置每个坐标轴的取值范围
plt.axis([0, 1100, 0, 1100000])

plt.show()

自动保存图表

"""自动计算数据"""

import matplotlib.pyplot as plt

x_values = list(range(1, 1001))
y_values = [x**3 for x in x_values]

plt.scatter(x_values, y_values, c = y_values,cmap = plt.cm.Blues, edgecolor = 'none', s = 4)
# c 参数的值越大，blues 颜色的值越深，渐变


plt.title("Square Numbers", fontsize = 24)
plt.xlabel("Values", fontsize = 14)
plt.ylabel("Square of Value", fontsize = 14)

# 设置每个坐标轴的取值范围
plt.axis([0, 1100, 0, 1100000])

plt.show()

plt.savefig('xieyi.png', bbox_inches = 'tight')
# 自动保存图表，第二个参数裁剪图表周围多余空白区域

随机漫步

from random import choice

import matplotlib.pyplot as plt

class RandomWalk():
    # 一个生成随机漫步数据的类

    def __init__(self, num_points = 500):
        self.num_points = num_points

        self.x_values = [0]
        self.y_values = [0]

    def fill_walk(self):

        while len(self.x_values) < self.num_points:

            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


            if x_step == 0 and y_step ==0:
                continue

            next_x = self.x_values[-1] + x_step
            next_y = self.y_values[-1] + y_step

            self.x_values.append(next_x)
            self.y_values.append(next_y)

rw = RandomWalk()
rw.fill_walk()
plt.scatter(rw.x_values, rw.y_values, s = 10)

plt.title("Numbers", fontsize = 24)
plt.xlabel("Values", fontsize = 20)
plt.ylabel("Numbers of Values", fontsize = 20)

plt.show()

模拟多次随机漫步

from random import choice

import matplotlib.pyplot as plt

class RandomWalk():
    # 一个生成随机漫步数据的类

    def __init__(self, num_points = 500):
        self.num_points = num_points

        self.x_values = [0]
        self.y_values = [0]

    def fill_walk(self):

        while len(self.x_values) < self.num_points:

            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


            if x_step == 0 and y_step ==0:
                continue

            next_x = self.x_values[-1] + x_step
            next_y = self.y_values[-1] + y_step

            self.x_values.append(next_x)
            self.y_values.append(next_y)

while True:
    rw = RandomWalk()
    rw.fill_walk()
    plt.scatter(rw.x_values, rw.y_values, s = 10)

    plt.title("Numbers", fontsize = 24)
    plt.xlabel("Values", fontsize = 20)
    plt.ylabel("Numbers of Values", fontsize = 20)

    plt.show()

    keep_runing = input("Make another walk?(y/n):")
    if keep_runing == 'n':
        break

设置随机漫步图的样式

from random import choice

import matplotlib.pyplot as plt

class RandomWalk():
    # 一个生成随机漫步数据的类

    def __init__(self, num_points = 500):
        self.num_points = num_points

        self.x_values = [0]
        self.y_values = [0]

    def fill_walk(self):

        while len(self.x_values) < self.num_points:

            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


            if x_step == 0 and y_step ==0:
                continue

            next_x = self.x_values[-1] + x_step
            next_y = self.y_values[-1] + y_step

            self.x_values.append(next_x)
            self.y_values.append(next_y)

while True:
    rw = RandomWalk()
    rw.fill_walk()

    # 给点着色
    point_number = list(range(rw.num_points))
    plt.scatter(rw.x_values, rw.y_values, c = point_number, cmap = plt.cm.Blues,
                edgecolor = 'none', s = 20)

    
    plt.show()

    keep_runing = input("Make another walk?(y/n):")
    if keep_runing == 'n':
        break

重新绘制起点和重终点

隐藏坐标轴

增加点数

调整屏幕以合适的尺寸

from random import choice

import matplotlib.pyplot as plt

class RandomWalk():
    # 一个生成随机漫步数据的类

    def __init__(self, num_points = 500):
        self.num_points = num_points

        self.x_values = [0]
        self.y_values = [0]

    def fill_walk(self):

        while len(self.x_values) < self.num_points:

            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


            if x_step == 0 and y_step ==0:
                continue

            next_x = self.x_values[-1] + x_step
            next_y = self.y_values[-1] + y_step

            self.x_values.append(next_x)
            self.y_values.append(next_y)

while True:
    rw = RandomWalk(50000)  # 增加点数
    rw.fill_walk()

    # 设置绘图窗口的尺寸
    plt.figure(figsize = (10, 6))

    # 给点着色，绘制点并将图形显示出来
    point_number = list(range(rw.num_points))
    plt.scatter(rw.x_values, rw.y_values, c = point_number, cmap = plt.cm.Blues,
                edgecolor = 'none', s = 1)

    # 突出起点和终点
    plt.scatter(0, 0, c = 'green', edgecolors = 'none', s = 100)
    plt.scatter(rw.x_values[-1], rw.y_values[-1], c = 'red', edgecolors = 'none',
                s = 100)

    # 隐藏坐标轴
    plt.axes().get_xaxis().set_visible(False)
    plt.axes().get_yaxis().set_visible(False)

    plt.show()

    keep_runing = input("Make another walk?(y/n):")
    if keep_runing == 'n':
        break

使用 Pygal 包：生成矢量图像，不同屏幕自动调整大小

from random import randint

import pygal

class Die():

    def __init__(self, num_sides = 6):
        self.num_sides = num_sides

    def roll(self):
        return randint(1, self.num_sides)

die = Die()

results = []
for roll_num in range(100):
    result = die.roll()
    results.append(result)

print(results)

# 分析结果
frequencies = []
for value in range(1, die.num_sides+1):
    frequency = results.count(value)
    frequencies.append(frequency)
print(frequencies)

# 可视化数据
hist = pygal.Bar()

hist.title = "Results of rolling one D6 1000 times"
hist.x_values = ['1','2','3', '4', '5', '6']
hist.x_title = "Result"
hist.y_title = "Frequencies"

hist.add('D6', frequencies)
hist.render_to_file('xieyi.svg')    # 渲染为一个svg文件,svg用浏览器打开

from random import randint

import pygal

class Die():

    def __init__(self, num_sides = 6):
        self.num_sides = num_sides

    def roll(self):
        return randint(1, self.num_sides)

die_1 = Die()
die_2 = Die()

results = []
for roll_num in range(1000):
    result = die_1.roll() + die_2.roll()
    results.append(result)

print(results)

# 分析结果
frequencies = []
max_result = die_1.num_sides + die_2.num_sides
for value in range(2, max_result+1):
    frequency = results.count(value)
    frequencies.append(frequency)
print(frequencies)

# 可视化数据
hist = pygal.Bar()

hist.title = "Results of rolling one D6 1000 times"
hist.x_labels = ['2','3', '4', '5', '6', '7', '8', '9','10', '11', '12']
hist.x_title = "Result"
hist.y_title = "Frequencies"

hist.add('D6 + D6', frequencies)
hist.render_to_file('xieyi01.svg')    # 渲染为一个svg文件,svg用浏览器打开