利用python绘制数据曲线图的实现

时间：2020-07-21 数据分析查看: 1148

”在举国上下万众一心、众志成城做好新冠肺炎疫情防控工作的特殊时刻，我们不能亲临主战场，但我们能坚持在大战中坚定信心、不负韶华。“

1、爬取新闻保存为json文件，并将绘图所需数据保存至数据库

数据库表结构：

代码部分：

import pymysql
import re
import sys,urllib,json
from urllib import request
from datetime import datetime
import pandas as pd
Today=datetime.now().strftime(r"%Y-%m-%d")
#Today='2020-02-14'
def pachong():
  url='http://api.tianapi.com/txapi/ncov/index?key=xxx&date={}'.format(Today)
  req = request.Request(url)
  resp = request.urlopen(req)
  content = resp.read().decode()
  data=json.loads(content)
  with open('/Users/zhangyuchen/Desktop/latestTrends.json','w') as fp:#将所得的数据存储为json文件
    json.dump(data,fp = fp,ensure_ascii = False,indent = 4,sort_keys=True)
  #dump函数有很多参数，第一个是目标object，第二个是要写入的文件对象
  print("成功保存为json文件！")
  return(re.findall(r'"confirmedCount":(.+?),"',content),re.findall(r'"currentConfirmedCount":(.+?),"',content),re.findall(r'"curedCount":(.+?),"',content))
def connectMysql(cc): 
  #/usr/local/mysql/bin/mysql -u root -p
  db = pymysql.connect("localhost", "root", "密码", "dbname",charset='utf8' )
  cursor = db.cursor()
  sql="""insert into {0} (DATE,SICK,SICK_NOW,RECOVER)values('{1}','{2}','{3}','{4}')"""
  cursor.execute(sql.format('db1',Today,int(cc[0][0]),int(cc[1][0]),int(cc[2][0])))
  cursor.execute(sql.format('db2',Today,int(cc[0][1]),int(cc[1][1]),int(cc[2][1])))
  db.commit()
  print(("成功将{}数据存入数据库！").format(Today))
  db.close()
cc=pachong()
connectMysql(cc)

json文件：

2、利用matplotlib库函数绘制图表

import numpy as np
import matplotlib.pyplot as plt
import matplotlib
import pymysql
import re
import sys, urllib,json
from urllib import request
#/usr/local/mysql/bin/mysql -u root -p
date=[]
cSick=[]
aSick=[]
cNowSick=[]
aNowSick=[]
cRecover=[]
aRecover=[]
db = pymysql.connect("localhost", "root", "密码", "trends")
sql="select * from db1 ORDER BY DATE"
cursor = db.cursor()
cursor.execute(sql)
results = cursor.fetchall()
while results:
  for row in results:
    date.append(row[0].strftime("%d"))
    cSick.append(row[1])
    cNowSick.append(row[2])
    cRecover.append(row[3])
  results=cursor.fetchone()
#查询Abroad Table
sql="select * from db2"
cursor.execute(sql)
results = cursor.fetchall()
while results:
  for row in results:
    aSick.append(row[1])
    aNowSick.append(row[2])
    aRecover.append(row[3])
  results=cursor.fetchone()
cursor.close()
db.close()
def DrawLineChart(ySick,yNowSick):
  plt.plot(x,ySick,color='y',label="Cumulative number of cases",linewidth=3,linestyle="--")
  plt.plot(x,yNowSick,color='r',label="Current number of cases",linewidth=3,linestyle="-")
def DrawBarChart(yRecover):
  width=0.45#柱子宽度
  p2 = plt.bar(x,yRecover,width,label="Cured Count",color="#87CEFA")
Days=len(aSick)
plt.figure(figsize=(16,12), dpi=80)#设置分辨率为80像素/每英寸
x=np.arange(Days)
#创建两个子图
plt.subplot(322)
plt.title("Trends of March")
DrawLineChart(cSick,cNowSick)
DrawBarChart(cRecover)
plt.figlegend()
plt.xticks(x,date)
plt.ylabel('Number')
plt.subplot(324)
#plt.title("Trends of March")
DrawLineChart(aSick,aNowSick)
DrawBarChart(aRecover)
plt.xticks(x,date,rotation=0)
plt.xlabel('Date')
plt.ylabel('Number')
plt.show()

到此这篇关于利用python绘制数据曲线图的实现的文章就介绍到这了,更多相关python 数据曲线图内容请搜索python博客以前的文章或继续浏览下面的相关文章希望大家以后多多支持python博客！

展开全文