2019年猪肉价格与猪饲料价格Python大数据分析.zip

# !/usr/bin/env python3 # -*- coding: utf-8 -*- #Author:Nicolas TU #Date:NOV.16,2019 20:57:07 # @Env: python 3.6 from pylab import mpl import matplotlib.pyplot as plt mpl.rcParams['font.sans-serif'] = ['SimHei'] # 指定默认字体 mpl.rcParams['axes.unicode_minus'] import pandas as pd import requests import time time_start=time.time()#计算时间开始 headers = {'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.120 Safari/537.36'} #生成出生当年所有日期 def dateRange(a,b): fmt = '%Y-%m-%d' bgn = int(time.mktime(time.strptime(a,fmt))) end = int(time.mktime(time.strptime(b,fmt))) list_date = [time.strftime(fmt,time.localtime(i)) for i in range(bgn,end+1,3600*24)] return list_date def get_json(url): try: response = requests.get(url,headers=headers) if response.status_code == 200: json_text=response.json() return json_text except Exception: print('此页有问题！') return None def get_comments(url): doc = get_json(url) dic = {} dic['pig_out'] = doc['pigprice'] dic['pig_in'] = doc['pig_in'] dic['pig_local'] = doc['pig_local'] dic['maize'] = doc['maizeprice'] dic['bean'] = doc['bean'] a = '-'.join(doc['time'][3]) b = time.strftime('%Y-%m-%d',time.localtime(time.time())) #print(dateRange(a,b)) dic['time'] = dateRange(a,b) return pd.DataFrame(dic) data =get_comments('http://zhujia.zhuwang.cc/index/api/chartData?areaId=-1&aa=1571997555296') print(data) #作图 plt.figure(figsize=(10,10), dpi=80) #plt.figure(1) ax1 = plt.subplot(311) plt.plot(data['time'],data['pig_out'], color="r",linestyle = "-") plt.xticks([]) plt.annotate(data['pig_in'][365], xy=(data['time'][365], 40), xytext=(data['time'][250], 35), arrowprops=dict(facecolor='blue', shrink=0.1, width=0.5)) plt.xlabel("生猪(内三元) 元/公斤") plt.title(u'2019年猪肉价格与猪饲料价格Python大数据分析，@Nicolas TU ') ax2 = plt.subplot(312) plt.plot(data['time'],data['maize'],color="y",linestyle = "-") plt.xticks([]) plt.xlabel("玉米(15%水分) 元/吨") ax3 = plt.subplot(313) plt.plot(data['time'],data['bean'],color="g",linestyle = "-") plt.xlabel("豆粕(43%蛋白) 元/吨") plt.xticks(data['time'][2::121], rotation=0) plt.show()#图像显示 time_end=time.time()#计算时间结束 print('-'*50) print('python3.6程序运行',time_end-time_start,'秒。') print('-'*50)