Python3 数据可视化之matplotlib、Pygal、requests

matplotlib的学习和使用

matplotlib的安装

pip3 install matplotlib

简单的折线图

import  matplotlib.pyplot as plt#绘制简单的图表input_values = [1,2,3,4,5]squares = [1,4,9,16,25]plt.plot(input_values,squares,linewidth=5)#设置图表的标题 并给坐标轴加上标签plt.title("Square Number",fontsize=24)plt.xlabel("Value",fontsize=24)plt.ylabel("Square of Value",fontsize=14)#设置刻度标记的大小plt.tick_params(axis='both',labelsize=14)#显示图表plt.show()#保存在当前的目录下，文件名为squares_plot.png#plt.savefig('squares_plot.png', bbox_inches='tight')

绘制简单的散点图

import matplotlib.pyplot as pltx_values = [1, 2, 3, 4, 5]y_values = [1, 4, 9, 16, 25]plt.scatter(x_values, y_values, s=100)#设置图表的标题 并给坐标轴加上标签plt.title("Square Number",fontsize=24)plt.xlabel("Value",fontsize=24)plt.ylabel("Square of Value",fontsize=14)#设置刻度标记的大小plt.tick_params(axis='both',labelsize=14)plt.show()

import  matplotlib.pyplot as plt#绘制散点图并设置其样式x_value = list(range(1,1001))y_value = [x**2 for x in x_value]#点的颜色 c=(0,0,1,0.5) edgecolors = 'red'  点的边缘颜色plt.scatter(x_value,y_value,c=y_value,cmap=plt.cm.Blues,edgecolors='none',s=40)# plt.scatter(2,4,s=200)#设置图表的标题 并给坐标轴加上标签plt.title("Square Number",fontsize=24)plt.xlabel("Value",fontsize=24)plt.ylabel("Square of Value",fontsize=14)#设置刻度标记的大小plt.tick_params(axis='both',labelsize=14)#设置每个坐标系的取值范围# plt.axis([0,110,0,110000])#显示plt.show()#显示并保存#plt.savefig('pyplot_scatter.png',bbox_inches='tight')

绘制随机漫步图

random_walk.py

from  random import choiceclass RandomWalk():    """一个生成随机漫步数据的类"""    def __init__(self,num_points=5000):        """一个生成随机漫步的数据的类"""        self.num_points = num_points;        #所有的随机漫步都始于（0，0）        self.x_value = [0]        self.y_value = [0]    def fill_walk(self):        """计算随机漫步包含的点"""        #不断漫步，直到列表达到指定的长度        while len(self.x_value) < self.num_points:            #决定前进的方向以及沿这个方向前进的距离            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            #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_value[-1] + x_step            next_y = self.y_value[-1] + y_step            self.x_value.append(next_x)            self.y_value.append(next_y)

rw_visual.py

import  matplotlib.pyplot as plt#引用同级目录下的文件from Random_Walk.random_walk import RandomWalk#创建一个RandomWalk的实例 并将其包含的点都绘制出来rw = RandomWalk()rw.fill_walk()print("test")point_numbers = list(range(rw.num_points))plt.scatter(rw.x_value,rw.y_value,c=point_numbers, cmap=plt.cm.Blues,edgecolor='none',s=15)# 突出起点和终点plt.scatter(0, 0, c='green',edgecolors='none',s=100)plt.scatter(rw.x_value[-1], rw.y_value[-1],c='red',edgecolors='none',s=100)# 设置绘图窗口的尺寸# plt.figure(figsize=(10, 6))plt.figure(dpi=128, figsize=(10, 6))# 隐藏坐标轴# plt.axes().get_xaxis().set_visible(False)# plt.axes().get_yaxis().set_visible(False)plt.show()

Pygal的学习和使用

安装Pygal

pip3 install pygal

绘制简单的直方图

创建骰子类 die.py

from  random import  randintclass Die():    """表示一个骰子的类"""    def __init__(self,num_sides=6):        """骰子默认为6面"""        self.num_sides = num_sides    def roll(self):        """返回一个位于1和骰子面数之间的随机值"""        return  randint(1,self.num_sides)

掷骰子die_visual.py

from  Pygal_learn.die import  Dieimport  pygal#创建一个D6die = Die()#掷几次骰子 并将结果存储在一个列表中results = []for roll_num in range(1000):    result = die.roll()    results.append(result)frequencies = []#分析结果for value in range(1,die.num_sides+1):    frequency = results.count(value)    frequencies.append(frequency)#对结果进行可视化hist = pygal.Bar()hist.title = "Result of rolling one d6 1000 times"hist.x_labels = ['1','2','3','4','5','6']hist.x_title = "Result"hist.y_title = "Frequency of result"hist.add("D6",frequencies)hist.render_to_file("die_visual.svg")

使用Web API

安装requests

pip3 install requests

绘制图表

通过抓取GitHub上受欢迎程度最高的Python项目，绘制出图表

import  requestsimport  pygalfrom pygal.style  import  LightColorizedStyle as LCS,LightenStyle as LS#执行API调用并存储响应url = 'https://api.github.com/search/repositories?q=language:python&sort=stars'r = requests.get(url)print("Staus code:",r.status_code)response_dict = r.json()print("Total repositories:", response_dict['total_count'])#探索有关仓库的信息repo_dicts = response_dict['items']print('Repositories returned:',len(repo_dicts))#研究第一个仓库# repo_dict = repo_dicts[0]# for key in sorted(repo_dict.keys()):#     print(key)#研究仓库有关的信息# Name: macOS-Security-and-Privacy-Guide# Owner: drduh# Stars: 12348# Repository: https://github.com/drduh/macOS-Security-and-Privacy-Guide# Description: A practical guide to securing macOS.names,plot_dicts = [],[]for repo_dict in repo_dicts:    names.append(repo_dict["name"])    # stars.append(repo_dict["stargazers_count"])    plot_dict = {        'value': repo_dict['stargazers_count'],        'label': str(repo_dict['description']),        'xlink': repo_dict['html_url']    }    plot_dicts.append(plot_dict)#可视化数据my_config = pygal.Config()my_config.x_label_rotation = 45my_config.show_legend = Falsemy_config.title_font_size = 24my_config.label_font_size = 14my_config.major_label_font_size = 18my_config.truncate_label = 15my_config.show_y_guides = Falsemy_config.width = 1000my_style = LS('#333366',base_style=LCS)chart = pygal.Bar(my_config,style=my_style)chart.title = "Most-Stared Python Project on Github"chart.x_labels = namesprint(plot_dicts)chart.add('',plot_dicts)chart.render_to_file('python_repos.svg')

监视API的速率限制

大多数API都存在速率限制，即你在特定时间内可执行的请求数存在限制。要获悉你是否接近了GitHub的限制，请在浏览器中输入https://api.github.com/rate_limit ，你将看到类似于下 面的响应:

参考内容:《Python编程：从入门到实践》