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 plt
x_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 choice
class 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 randint
class 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 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(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 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 = 45
my_config.show_legend = False
my_config.title_font_size = 24
my_config.label_font_size = 14
my_config.major_label_font_size = 18
my_config.truncate_label = 15
my_config.show_y_guides = False
my_config.width = 1000
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')
4 从json文件中提取数据，并进行可视化
4.1 数据来源：population_data.json。
4.2 一个简单的代码段：
- import json #导入json模版
- filename = 'population_data.png'
- with open(filename) as f:
- pop_data = json.load(f) #加载json文件数据
通过小的代码段了解最基本的原理，具体详情还要去查看手册。
4.3制作简单的世界地图（代码如下）
- import pygal #导入pygal
- wm = pygal.maps.world.World() #正确导入世界地图模块
- wm.title = 'populations of Countries in North America'
- wm.add('North America',{'ca':34126000,'us':309349000,'mx':113423000})
- wm.render_to_file('na_populations.svg') #生成svg文件
结果：
4.4 制作世界地图
代码段：
- import json
- import pygal
- from pygal.style import LightColorizedStyle as LCS, RotateStyle as RS
- from country_codes import get_country_code
- # Load the data into a list.
- filename = 'population_data.json'
- with open(filename) as f:
- pop_data = json.load(f)
- # Build a dictionary of population data.
- cc_populations = {}
- for pop_dict in pop_data:
- if pop_dict['Year'] == '2010':
- country_name = pop_dict['Country Name']
- population = int(float(pop_dict['Value']))
- code = get_country_code(country_name)
- if code:
- cc_populations[code] = population
- # Group the countries into 3 population levels.
- cc_pops_1, cc_pops_2, cc_pops_3 = {}, {}, {}
- for cc, pop in cc_populations.items():
- if pop < 10000000: #分组
- cc_pops_1[cc] = pop
- elif pop < 1000000000:
- cc_pops_2[cc] = pop
- else:
- cc_pops_3[cc] = pop
- # See how many countries are in each level.
- print(len(cc_pops_1), len(cc_pops_2), len(cc_pops_3))
- wm_style = RS('#336699', base_style=LCS)
- wm = pygal.maps.world.World(style=wm_style) #已修改，原代码有错误！
- wm.title = 'World Population in 2010, by Country'
- wm.add('0-10m', cc_pops_1)
- wm.add('10m-1bn', cc_pops_2)
- wm.add('>1bn', cc_pops_3)
- wm.render_to_file('world_population.svg')
辅助代码段country_code.py如下：
- from pygal.maps.world import COUNTRIES
- from pygal_maps_world import i18n #原代码也有错误，现已订正
- def get_country_code(country_name):
- """Return the Pygal 2-digit country code for the given country."""
- for code, name in COUNTRIES.items():
- if name == country_name:
- return code
- # If the country wasn't found, return None.
- return None
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:
