1. 首先我们需要找到数据,很多地方提供了api,比如:
https://www.wunderground.com/weather/api(但是这个网站不提供空气质量)
空气质量可参考:https://www.zhihu.com/question/20939327
2. 从api获取数据,使用python,代码粘出来:
# -*- coding: UTF-8 -*- import urllib2 import json from datetime import datetime import pandas as pd '''' 最终选择的特征有:气温tempm, 露点dewptm, 湿度humidity, 风力wspdm, 能见度vism, 气压pressurei, 降水precipm 其中,tempm:min max mean, dewptm:min max mean, humidity:humidity, wspdm: min max, vism: mean min max, pressurei: max min mean, precipm:precipm 目标:fog(雾霾) ''' def getdata(month,day,meant,meand,humi,maxw,meanv,meanp,preci,fo): date = datetime(2017, month, day) print day target = 'http://api.wunderground.com/api/{Your Key}/history_{}/q/CN/zmw:00000.1.54511.json?v=wuiapp' f = urllib2.urlopen(target.format(date.strftime('%Y%m%d'))) json_string = f.read() parsed_json = json.loads(json_string) day = parsed_json['history']['dailysummary'] temp = day[0]['meantempm'] #气温情况 dewptm = day[0]['meandewptm'] # 露点情况 hum = day[0]['humidity'] # 湿度情况 wspdm = day[0]['maxwspdm'] # 风力情况 vism = day[0]['meanvism'] # 能见度情况 press = day[0]['meanpressurei'] # 气压情况 prec = day[0]['precipm'] # 降水情况 fog = day[0]['fog'] #雾霾情况 meant.append(temp) meand.append(dewptm) humi.append(hum) maxw.append(wspdm) meanv.append(vism) meanp.append(press) preci.append(prec) fo.append(fog) f.close() if __name__ == '__main__': meantempm = [] meandewptm = [] humidity = [] maxwspdm = [] meanvism = [] meanpressurei = [] precipm = [] f = [] for day in range(1,31): getdata(4, day, meantempm, meandewptm, humidity, maxwspdm, meanvism, meanpressurei, precipm, f) print meantempm #head = [u'温度',u'露点',u'湿度',u'风力',u'能见度',u'气压',u'降水',u'雾霾'] value = [meantempm, meandewptm, humidity, maxwspdm, meanvism, meanpressurei, precipm, f] value = list(zip(*value)) dataframe = pd.DataFrame(value) dataframe.to_csv('/Users/purixingtei/Downloads/output-2.csv', index=False, encoding="utf-8")
其中的Your Key需要被替换成自己的app key,然后主函数的循环,需要根据自己的月-日进行选择。
特别注意一点就是:不要起csv.py的名!!!
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