parent
85e2b97736
commit
a73fbe197d
@ -0,0 +1,75 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Created on Thu May 23 22:35:58 2024
|
||||
|
||||
@author: Lenovo
|
||||
"""
|
||||
|
||||
import requests
|
||||
url = "https://www.bitpush.news/covid19/"
|
||||
headers = {"User-Agent":"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36 Edg/116.0.1938.54"}
|
||||
response = requests.get(url,headers=headers)
|
||||
html = response.text
|
||||
|
||||
from lxml import etree
|
||||
parse = etree.HTMLParser(encoding='gbk')
|
||||
doc = etree.HTML(html)
|
||||
|
||||
area = doc.xpath('//*[@id="main"]/div[2]/div/div/div/div/div[1]/table/tbody/tr/td[1]/span/text()')
|
||||
person = doc.xpath('//*[@id="main"]/div[2]/div/div/div/div/div[1]/table/tbody/tr/td[2]/text()')
|
||||
person = [x.replace(",", "") for x in person]
|
||||
death = doc.xpath('//*[@id="main"]/div[2]/div/div/div/div/div[1]/table/tbody/tr/td[3]/text()')
|
||||
death = [x.replace(",", "") for x in death]
|
||||
message = list(zip(area, person, death))
|
||||
|
||||
import csv
|
||||
with open("content.csv", "w") as f:
|
||||
w = csv.writer(f)
|
||||
w.writerows(message)
|
||||
|
||||
import pandas as pd
|
||||
df = pd.read_csv("content.csv", names=["area", "person", "death"],encoding='gbk')
|
||||
df.head()
|
||||
df.info()
|
||||
df1 = df.drop(0).head(15)
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
#确诊人数垂直图
|
||||
plt.rcParams['font.sans-serif'] = ['SimHei']
|
||||
plt.rcParams['figure.figsize'] = (10, 5)
|
||||
x = df1["area"].values
|
||||
y = df1["person"].values
|
||||
plt.bar(x, y)
|
||||
plt.xlabel("地区",fontsize=14)
|
||||
plt.ylabel("确诊人数",fontsize=14)
|
||||
plt.show()
|
||||
#确诊人数水平图
|
||||
x = df1["area"].values
|
||||
y = df1["person"].values
|
||||
colors=['red','green','cyan','blue']
|
||||
plt.barh(x, y,height=0.8,color=colors)
|
||||
plt.yticks(x)
|
||||
plt.xlabel("确诊人数",fontsize=14)
|
||||
plt.ylabel("地区",fontsize=14)
|
||||
for i,j in zip(x,y):
|
||||
plt.text(j,i,j)
|
||||
plt.legend()
|
||||
plt.show()
|
||||
#死亡人数垂直图
|
||||
plt.rcParams['font.sans-serif'] = ['SimHei']
|
||||
plt.rcParams['figure.figsize'] = (10, 5)
|
||||
x = df1["area"].values
|
||||
y = df1["death"].values
|
||||
plt.bar(x, y)
|
||||
plt.xlabel("地区",fontsize=14)
|
||||
plt.ylabel("死亡人数",fontsize=14)
|
||||
plt.show()
|
||||
#确诊人数饼图
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
labels = df1["area"].values
|
||||
sizes = df1["person"].values
|
||||
explode = (0.1,0,0,0,0,0,0,0,0,0,0,0,0,0,0)
|
||||
plt.pie(sizes,explode,labels=labels,autopct='%.1f%%')
|
||||
plt.title("美国疫情确诊人数排名 top15 地区情况")
|
||||
|
Loading…
Reference in new issue