Posted in Python onApril 09, 2020
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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()
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利用python绘制数据曲线图的实现
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