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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