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[Python] Python 学习 - 可视化数据操作(一)

Python 学习 - 可视化数据操作(一)

  GitHub:https://github.com/liqingwen2015/my_data_view

 

目录

  • 折线图
  • 散点图
  • 随机漫步
  • 骰子点数概率
  • 文件目录

 

折线图

  cube_squares.py

import matplotlib.pyplot as pltx_values=list(range(1, 5000))y_values=[pow(x, 3) for x in x_values]plt.scatter(x_values, y_values, c=y_values, cmap=plt.cm.Blues, edgecolor=none, s=40)# 设置标题和样式plt.title("Square Numbers", fontsize=24)plt.xlabel("Value", 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()

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  mpl_squares.py

# 简单的折线图
import matplotlib.pyplot as pltinput_values=[1, 2, 3, 4, 5 ]squares = [1, 4, 9, 16, 25]# 绘制线条的粗细plt.plot(input_values, squares, linewidth=5)# 设置图表标题,并给坐标轴加上标签plt.title("Square Numbers", fontsize=24)plt.xlabel("Value", fontsize=14)plt.ylabel("Square of Value", fontsize=14)# 设置刻度标记的大小,axis=‘both‘ 表示指定的实参影响 x 轴和 y 轴上的刻度plt.tick_params(axis=both, labelsize=14)plt.show()

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散点图

  scatter_squares.py

# 散点图import matplotlib.pyplot as pltx_values = list(range(1, 1001))y_values = [x**2 for x in x_values]# c:颜色#plt.scatter(x_values, y_values, c=‘red‘, edgecolor=‘none‘, s=40)#plt.scatter(x_values, y_values, c=(0, 0, 8), edgecolor=‘none‘, s=40)plt.scatter(x_values, y_values, c=y_values, cmap=plt.cm.Blues, edgecolor=none, s=40)# 设置标题和样式plt.title("Square Numbers", fontsize=24)plt.xlabel("Value", 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()# 保存图表#plt.savefig(‘squared_plot.png‘, bbox_inches=‘tight‘)

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随机漫步

  random_walk.py

from random import choiceclass RandomWalk():    def __init__(self, num_points=5000):        # 初始化随机漫步的属性        self.num_points = num_points        # 所有随机漫步都始于(0, 0)        self.x_values = [0]        self.y_values = [0]    def fill_walk(self):        # 不断漫步,直到列表达到指定的长度        while len(self.x_values) < self.num_points:            x_step = self.get_step();            y_step = self.get_step();            # 拒绝原地踏步            if x_step == 0 and y_step == 0:                continue            # 计算下一个点的 x 和 y 值            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)    def get_step(self):        # 决定前进方向以及沿这个方向前进的距离        direction = choice([1, -1])  # 随机选 1 或 -1        distance = choice([0, 1, 2, 3, 4])  # 随机选 0, 1, 2, 3, 4        return direction * distance  # 正数:右移,负数:左移

   rw_visual.py

import matplotlib.pyplot as pltfrom 随机漫步.random_walk import RandomWalkwhile True:    # 创建一个 RandomWalk 实例,并将其包含的点都绘制出来    rw = RandomWalk(5000)    rw.fill_walk()    point_numbers = list(range(rw.num_points))    plt.scatter(rw.x_values, rw.y_values, c=point_numbers, cmap=plt.cm.Blues, edgecolors=none, s=1)    # 设置绘图窗口的尺寸    #plt.figure(dpi=128, figsize=(10, 6))    # 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)    #plt.plot(rw.x_values, rw.y_values, linewidth=10)    # 隐藏坐标轴    plt.axes().get_xaxis().set_visible(False)    plt.axes().get_yaxis().set_visible(False)    plt.show()    keep_running = input("继续?(y/n):")    if keep_running == n:        break

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骰子点数概率

  die.py

from random import randintclass Die():    # 表示一个骰子类    def __init__(self, num_sides=6):        # 6 面        self.num_sides = num_sides    def roll(self):        # 返回 1~6        return randint(1, self.num_sides)

  

  die_visual.py

import pygalfrom 骰子.die import Die# 创建一个 D6die = Die()results = []for roll_num in range(1000):    result = die.roll()    results.append(result)frequencies = []for value in range(1, die.num_sides+1):    # 计算某个值出现同样的次数    frequency = results.count(value)    frequencies.append(frequency)# 对结果进行可视化hist = pygal.Bar()hist.title = "D6 1000次:"hist.x_labels = [str(num) for num in range(1, 7)] #[‘1‘, ‘2‘, ‘3‘, ‘4‘, ‘5‘, ‘6‘]hist.x_title = "结果"hist.y_title = "概率"hist.add(D6, frequencies)hist.render_to_file(images/die_visual.svg)

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  dice_visual.py

import pygalfrom 骰子.die import Die# 创建 2 个 D6die_1 = Die()die_2 = Die()results = []for roll_num in range(1000):    result = die_1.roll() + die_2.roll()    results.append(result)frequencies = []max_results = die_1.num_sides + die_2.num_sidesfor value in range(2, max_results+1):    # 计算某个值出现同样的次数    frequency = results.count(value)    frequencies.append(frequency)# 对结果进行可视化hist = pygal.Bar()hist.title = "D6 100次:"hist.x_labels = [str(num) for num in range(1, 13)] #[‘1‘, ‘2‘, ‘3‘, ‘4‘, ‘5‘, ‘6‘, ‘7‘, ‘8‘, ‘9‘, ‘10‘, ‘11‘, ‘12‘]hist.x_title = "结果"hist.y_title = "出现的次数"hist.add(D6 + D6, frequencies)hist.render_to_file(images/dice_visual.svg)

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  different_dice.py

import pygalfrom 骰子.die import Die# 创建一个 D6 和 D10die_1 = Die()die_2 = Die(10)results = []for roll_num in range(5000):    result = die_1.roll() + die_2.roll()    results.append(result)frequencies = []max_results = die_1.num_sides + die_2.num_sidesfor value in range(2, max_results+1):    # 计算某个值出现同样的次数    frequency = results.count(value)    frequencies.append(frequency)# 对结果进行可视化hist = pygal.Bar()hist.title = "5000 次:D6 + D10 的结果。"hist.x_labels = [str(num) for num in range(2, 17)]hist.x_title = "结果"hist.y_title = "重复出现的次数"hist.add(D6 + D10, frequencies)hist.render_to_file(images/different_visual.svg)

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文件目录

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  GitHub:https://github.com/liqingwen2015/my_data_view

[Python] Python 学习 - 可视化数据操作(一)