python+msql+pyecharts中国各省人口数量以及增长量的可视化分析中国各省人口数量以及增长量的可视化分析
【声明：因时间关系，爬虫部分代码有所借鉴，本人主要想将该三部分结合起来，供读者学习交流，如有冒犯，尽请原谅！】
一、本地环境：
1.python 3.7
2.mysql 8.0.17(Navicat)
3.beautifulsoup 4-4.8.0
4.pyecharts-0.5.11
！！！（若pyecharts导入过程之中遇到较难解决的问题，读者可尝试Anaconda3,其自带pyecharts）
二、爬取数据放置MySQL
import requests
from bs4 import BeautifulSoup
import re
import pymysql
db = pymysql.connect("localhost", "root", "123zwh", "zwh1")
cursor = db.cursor()
url = 'http://www.china-10.com/news/488659.html'
html = requests.get(url)
soup = BeautifulSoup(html.content, 'html.parser')
# 找到所有class为md_td的td元素
aaa = soup.find_all(name="td", attrs={"class": re.compile(r"md_td")})
# 检查索引，以便于后面爬取工作
# for n,i in enumerate(aaa):
# print(n,i.text)
demo_list = [] for i in aaa[4:128]:
demo_list.append(i.text)
while demo_list:
print(int(demo_list[0:4][0]), demo_list[0:4][1], int(float(demo_list[0:4][2]) * 10000),
int(float(demo_list[0:4][3]) * 10000))
# 测试数据类型
# print(type(demo_list[0:4][0]), type(demo_list[0:4][1]), type(demo_list[0:4][2]), type(demo_list[0:4][3]))
insert_message = ("INSERT INTO china_population VALUES(%s,%s,%s,%s)")
data = (int(demo_list[0:4][0]), demo_list[0:4][1], int(float(demo_list[0:4][2]) * 10000),
int(float(demo_list[0:4][3]) * 10000))
# 数据插入数据库
cursor.execute(insert_message, data)
db.commit()
del demo_list[0:4] # 关闭数据库
db.close()
数据库数据展示：
三、从MySQL获取数据，利用pyecharts绘制成图生成html
import pymysql
from pyecharts import Bar,Line
namelist = [] numlist = [] riselist=[]
db = pymysql.connect("localhost", "root", "123zwh", "zwh1")
cursor = db.cursor()
try:
sql_name = """ SELECT province FROM china_population """
cursor.execute(sql_name)
names = cursor.fetchall()
for name in names:
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