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photo.py
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# coding: utf-8
import requests
import json
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
from scipy.interpolate import make_interp_spline
from datetime import datetime
print("本程序用独立图展示用户指定国家指定时间段指定相关数据的疫情变化图，并做了平滑处理")
query_url='https://api.inews.qq.com/newsqa/v1/automation/foreign/daily/list'
#为了防止数据后期被腾讯删除，我留了一份，可以取消国家选项，网址为：
#https://jadelike-wine.github.io/2019-nCoV/
country_list=["美国","巴西","俄罗斯","西班牙","英国","意大利","法国","德国","土耳其","印度","伊朗","秘鲁","加拿大","智利","沙特阿拉伯","墨西哥","巴基斯坦","比利时","卡塔尔","荷兰","白俄罗斯","孟加拉","厄瓜多尔","瑞典","新加坡","阿联酋","葡萄牙","瑞士","南非","爱尔兰","哥伦比亚","印度尼西亚","科威特","波兰","乌克兰","埃及","罗马尼亚","以色列","日本本土","奥地利","多米尼加","菲律宾","阿根廷","阿富汗","巴拿马","丹麦","韩国","塞尔维亚","巴林","哈萨克斯坦","捷克","阿尔及利亚","尼日利亚","挪威","阿曼","亚美尼亚","玻利维亚","马来西亚","摩洛哥","摩尔多瓦","加纳","澳大利亚","芬兰","喀麦隆","伊拉克","洪都拉斯","阿塞拜疆","苏丹","危地马拉","卢森堡","匈牙利","塔吉克斯坦","乌兹别克斯坦","几内亚","塞内加尔","泰国","希腊","吉布提","科特迪瓦","刚果（金）","保加利亚","波黑","加蓬","克罗地亚","萨尔瓦多","北马其顿","古巴","爱沙尼亚","冰岛","索马里","立陶宛","吉尔吉斯斯坦","斯洛伐克","新西兰","肯尼亚","斯洛文尼亚","斯里兰卡","马尔代夫","海地","委内瑞拉","几内亚比绍","黎巴嫩","马里","赞比亚","拉脱维亚","突尼斯","阿尔巴尼亚","赤道几内亚","哥斯达黎加","尼日尔","塞浦路斯","尼泊尔","巴拉圭","布基纳法索","乌拉圭","塞拉利昂","安道尔","尼加拉瓜","格鲁吉亚","埃塞俄比亚","约旦","乍得","钻石号邮轮","中非共和国","圣马力诺","马达加斯加","马耳他","刚果（布）","牙买加","坦桑尼亚","巴勒斯坦","多哥","佛得角","卢旺达","毛里求斯","越南","黑山","毛里塔尼亚","乌干达","斯威士兰","利比里亚","也门","莫桑比克","贝宁","缅甸","蒙古","文莱","圭亚那","津巴布韦","柬埔寨","叙利亚","特立尼达和多巴哥","马拉维","巴哈马","利比亚","摩纳哥","巴巴多斯","科摩罗","列支敦士登公国","安哥拉","布隆迪","厄立特里亚","马提尼克岛","博茨瓦纳","不丹","冈比亚","安提瓜和巴布达","东帝汶","格林纳达","纳米比亚","老挝","斐济","伯利兹","圣文森特和格林纳丁斯","圣卢西亚","多米尼克","圣基茨和尼维斯","梵蒂冈","苏里南","塞舌尔","巴布亚新几内亚","莱索托"]
print("请选择所想展示的国家（输入数字即可）：")
for i in range(len(country_list)):
print(str(i)+"."+country_list[i])
n=int(input())
shuju=['每日新增', '确诊病例', '治愈病例', '死亡人数']
print("请输入你想展现的数据（输入数字即可）：")
for i in range(len(shuju)):
print(str(i)+'.'+shuju[i])
n_shuju=int(input())
param = {"country": country_list[n]}
res = requests.post(query_url, param)
d=json.loads(res.content.decode())
data=pd.DataFrame(d['data'])
xs=pd.DataFrame(d['data']).date
for i in range(len(xs)):
xs[i]="2020-"+xs[i][0]+xs[i][1]+'-'+xs[i][3]+xs[i][4]
xs = [datetime.strptime(d, '%Y-%m-%d').date() for d in xs]
print("请输入你想展现的时间（输入数字，间隔空格即可）：")
for i in range(len(xs)):
print(str(i)+'.'+str(xs[i]))
start,end=map(int,input().split())
startDate=xs[start]
endDate=xs[end]
index = pd.date_range(startDate, endDate)
cols = ['value']
if n_shuju==0:
ys=data.confirm_add
elif n_shuju==1:
ys=data.confirm
elif n_shuju==2:
ys=data.heal
else:
ys=data.dead
y=list()
for i in range(start,end+1):
y.append(ys[i])
df = pd.DataFrame(y, index=index, columns=cols)
fig, axs = plt.subplots(1,1, figsize=(18,5))
index_hourly = pd.date_range(startDate, endDate, freq='1H')
df_smooth = df.reindex(index=index_hourly).interpolate('cubic')
df_smooth = df_smooth.rename(columns={'value':'smooth'})
df_smooth.plot(ax=axs, alpha=100)
df.plot(ax=axs, alpha=100)
plt.xlabel('date')
plt.ylabel('number')
plt.title("Added trend graph after smoothing the infected person data")
plt.show()
max=ys.max()
time=list()
for i in range(len(xs)):
if ys[i]==max:
time.append(data.date[i])
print("所选数据峰值为"+str(max))
print("出现时间为：")
for i in range(len(time)):
print(time[i])