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- from datetime import datetime as dt
- import time
- import pandas as pd
- if __name__=='__main__':
- from xtquant import xtdata
- s = '000001.SZ'
-
-
-
- xtdata.download_history_data(s, '1d','','')
- xtdata.download_history_data('000001.SH', '1d','','')
- data = xtdata.get_market_data([], [s], '1d', end_time='', count=-1, dividend_type='back')
-
- print('data from get_local_data:\n')
- df = pd.DataFrame()
- for column in data:
- if column in ['time', 'open', 'high', 'low', 'close', 'volume', 'amount']:
-
- print(column, data[column].T)
- df=pd.concat([df, data[column].T],axis=1)
- df.columns = ['time', 'open', 'high', 'low', 'close', 'volume', 'amount']
- df['time']=df['time'].apply(lambda x: dt.fromtimestamp(x / 1000.0))
- print('!!!!!!!', df)
-
- df2 = pd.concat([data[i].T for i in ['time', 'open', 'high', 'low', 'close', 'volume', 'amount']], axis=1)
- df2.columns = ['time', 'open', 'high', 'low', 'close', 'volume', 'amount']
- df2['time']=df2['time'].apply(lambda x: dt.fromtimestamp(x / 1000.0))
- print('>>>>>>>>>>>', df2)
- print(df.index)
- exit()
-
-
-
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