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 = [,,,,]
squares = [,,,,]
plt.plot(input_values,squares,linewidth=)
#设置图表的标题 并给坐标轴加上标签
plt.title("Square Number",fontsize=)
plt.xlabel("Value",fontsize=)
plt.ylabel("Square of Value",fontsize=)
#设置刻度标记的大小
plt.tick_params(axis='both',labelsize=)
#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 plt
x_values = [, , , , ]
y_values = [, , , , ]
plt.scatter(x_values, y_values, s=)
#设置图表的标题 并给坐标轴加上标签
plt.title("Square Number",fontsize=)
plt.xlabel("Value",fontsize=)
plt.ylabel("Square of Value",fontsize=)
#设置刻度标记的大小
plt.tick_params(axis='both',labelsize=)
plt.show()
import matplotlib.pyplot as plt
#绘制散点图并设置其样式
x_value = list(range(,))
y_value = [x** 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=)
# 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=)
plt.xlabel("Value",fontsize=)
plt.ylabel("Square of Value",fontsize=)
#设置刻度标记的大小
plt.tick_params(axis='both',labelsize=)
#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 choice
class RandomWalk():
"""一个生成随机漫步数据的类"""
def __init__(self,num_points=):
"""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 = []
self.y_value = []
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([,-])
x_distance = choice([,,,,])
x_step = x_direction*x_distance
y_direction = choice([,-])
y_distance = choice([, , , , ])
y_step = y_direction * y_distance
#拒绝原地踏步
if x_step == and y_step == :
continue
#计算下一个点的x和y值
next_x = self.x_value[-] + x_step
next_y = self.y_value[-] + 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=)
# 突出起点和终点
plt.scatter(, , c='green',edgecolors='none',s=)
plt.scatter(rw.x_value[-], rw.y_value[-],c='red',edgecolors='none',s=)
# 设置绘图窗口的尺寸
# plt.figure(figsize=(10, 6))
plt.figure(dpi=, figsize=(, ))
# 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 randint
class Die():
"""表示一个骰子的类"""
def __init__(self,num_sides=):
"""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(,self.num_sides)
掷骰子die_visual.py
from Pygal_learn.die import Die
import pygal
#创建一个D6
die = Die()
#掷几次骰子 并将结果存储在一个列表中
results = []
for roll_num in range():
result = die.roll()
results.append(result)
frequencies = []
#分析结果
for value in range(,die.num_sides+):
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 requests
import pygal
from 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 =
my_config.show_legend = False
my_config.title_font_size =
my_config.label_font_size =
my_config.major_label_font_size =
my_config.truncate_label =
my_config.show_y_guides = False
my_config.width =
my_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 = names
print(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: