历年G20大会前一个交易日涨跌幅|热门发帖

历年G20大会前一个交易日涨跌幅

作者/adasda 2019-06-25 08:44 0 来源: FX168财经网人物频道

import numpy as np
import pandas as pd
from jqdata import *

#G20大会前一交易日股票涨幅情况
df = get_price('000001.XSHG',start_date='2008-11-01',end_date='2019-01-31',frequency='daily')

date = ['2008-11-15','2009-04-02','2009-09-24','2010-06-26','2010-11-11','2011-11-03','2012-06-18',
        '2013-09-05','2014-11-15','2015-11-15','2016-09-04','2017-07-07','2018-11-30']
import datetime

def delta(j):
    return datetime.timedelta(days=j)
def strtodate(str1):
    return datetime.datetime.strptime(str1, '%Y-%m-%d').date()
def datetostr(date):
    return datetime.datetime.strftime(date,'%Y-%m-%d')

date_list =[str(i)[:10] for i in list(df.index)]
df1 = pd.DataFrame(columns=df.columns)
for i in date:
    
    j = 1
    
    while datetostr(strtodate(i)-delta(j)) not in date_list:
        
        j = j+1
#     delta = datetime.timedelta(days=j)

#     print(df.loc[datetostr(strtodate(i)-delta(j)),:])
    df1.loc[datetostr(strtodate(i)-delta(j))]=df.loc[datetostr(strtodate(i)-delta(j))]

df1

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	open	close	high	low	volume	money
2008-11-14	1943.96	1986.44	1987.26	1921.84	1.304395e+10	8.784996e+10
2009-04-01	2380.98	2408.02	2422.63	2380.98	1.798576e+10	1.665421e+11
2009-09-23	2897.81	2842.72	2924.20	2825.86	1.076264e+10	1.167867e+11
2010-06-25	2556.54	2552.82	2572.83	2534.27	5.007885e+09	5.168800e+10
2010-11-10	3120.44	3115.36	3124.26	3093.88	1.850524e+10	2.489743e+11
2011-11-02	2437.87	2504.11	2505.12	2433.72	1.054682e+10	1.020828e+11
2012-06-15	2299.78	2306.85	2314.24	2283.40	6.868758e+09	6.785591e+10
2013-09-04	2121.68	2127.62	2133.00	2115.75	1.420004e+10	1.164574e+11
2014-11-14	2477.97	2478.82	2481.03	2457.05	2.206076e+10	1.919250e+11
2015-11-13	3600.76	3580.84	3632.56	3564.81	3.458709e+10	4.686687e+11
2016-09-02	3057.49	3067.35	3072.53	3050.49	1.504469e+10	1.705921e+11
2017-07-06	3203.86	3212.44	3215.95	3188.77	1.758093e+10	2.022096e+11
2018-11-29	2613.78	2567.44	2617.55	2567.44	1.571687e+10	1.294724e+11

df1['change'] = (df['close']-df['open'])/df['open']

df1

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	open	close	high	low	volume	money	change
2008-11-14	1943.96	1986.44	1987.26	1921.84	1.304395e+10	8.784996e+10	NaN
2009-04-01	2380.98	2408.02	2422.63	2380.98	1.798576e+10	1.665421e+11	NaN
2009-09-23	2897.81	2842.72	2924.20	2825.86	1.076264e+10	1.167867e+11	NaN
2010-06-25	2556.54	2552.82	2572.83	2534.27	5.007885e+09	5.168800e+10	NaN
2010-11-10	3120.44	3115.36	3124.26	3093.88	1.850524e+10	2.489743e+11	NaN
2011-11-02	2437.87	2504.11	2505.12	2433.72	1.054682e+10	1.020828e+11	NaN
2012-06-15	2299.78	2306.85	2314.24	2283.40	6.868758e+09	6.785591e+10	NaN
2013-09-04	2121.68	2127.62	2133.00	2115.75	1.420004e+10	1.164574e+11	NaN
2014-11-14	2477.97	2478.82	2481.03	2457.05	2.206076e+10	1.919250e+11	NaN
2015-11-13	3600.76	3580.84	3632.56	3564.81	3.458709e+10	4.686687e+11	NaN
2016-09-02	3057.49	3067.35	3072.53	3050.49	1.504469e+10	1.705921e+11	NaN
2017-07-06	3203.86	3212.44	3215.95	3188.77	1.758093e+10	2.022096e+11	NaN
2018-11-29	2613.78	2567.44	2617.55	2567.44	1.571687e+10	1.294724e+11	NaN