#连接数据库
conn = pymysql.connect(host='localhost',user='root',password='1235', db='wind',charset="utf8")

#从数据库查询数据，构建dataframe
cur = conn.cursor()
cur.execute("select tradedate,secid,closeprice,volume from stockprice;") #调整sql字段顺序即可获得不同顺序的【】
cur.scroll(0,"absolute")
ohlc=[]
time=[]
for line in cur.fetchall():
    ohlc.append(line[-3:])
    time.append(line[0])


df=DataFrame(ohlc,index=time,columns=['windcode','close','volume'])
#对格式进行整理
df.index=df.index.to_datetime()
df[['close','volume']]=df[['close','volume']].astype(float)


#获取近三年收盘价的最低值
df['2015':'2017'].groupby('windcode')['close'].min()

#与现价进行比较
df.groupby('windcode')['close'].last()/df['2015':'2017'].groupby('windcode')['close'].min()-1