notebook.community

Edit and run



In [1]:

    
import requests
import pandas as pd



In [2]:

    
price = pd.read_csv('d:/data/price.txt', index_col=0)



In [3]:

    
price.head()



In [4]:

    
price.info()









    



<class 'pandas.core.frame.DataFrame'>
Index: 1000 entries, 2013-12-09 to 2018-01-09
Data columns (total 7 columns):
open      1000 non-null float64
close     1000 non-null float64
high      1000 non-null float64
low       1000 non-null float64
volume    1000 non-null float64
money     1000 non-null float64
change    999 non-null float64
dtypes: float64(7)
memory usage: 62.5+ KB



In [5]:

    
price.index









    Out[5]:





Index(['2013-12-09', '2013-12-10', '2013-12-11', '2013-12-12', '2013-12-13',
       '2013-12-16', '2013-12-17', '2013-12-18', '2013-12-19', '2013-12-20',
       ...
       '2017-12-26', '2017-12-27', '2017-12-28', '2017-12-29', '2018-01-02',
       '2018-01-03', '2018-01-04', '2018-01-05', '2018-01-08', '2018-01-09'],
      dtype='object', length=1000)



In [6]:

    
price.insert(0, 'code', '600111')



In [7]:

    
price.head()



In [14]:

    
txt = price.to_csv(header=None)
r = requests.post('http://140.143.195.110:9999/add', data=txt)



In [ ]:

	open	close	high	low	volume	money	change
2013-12-09	5.46	5.46	5.50	5.43	6209948.0	33837888.0	NaN
2013-12-10	5.47	5.42	5.51	5.40	7074551.0	38507928.0	-0.007326
2013-12-11	5.39	5.29	5.41	5.25	8341736.0	44297016.0	-0.023985
2013-12-12	5.28	5.29	5.31	5.23	6160861.0	32461552.0	0.000000
2013-12-13	5.23	5.25	5.29	5.22	4770927.0	25088916.0	-0.007561

	code	open	close	high	low	volume	money	change
2013-12-09	600111	5.46	5.46	5.50	5.43	6209948.0	33837888.0	NaN
2013-12-10	600111	5.47	5.42	5.51	5.40	7074551.0	38507928.0	-0.007326
2013-12-11	600111	5.39	5.29	5.41	5.25	8341736.0	44297016.0	-0.023985
2013-12-12	600111	5.28	5.29	5.31	5.23	6160861.0	32461552.0	0.000000
2013-12-13	600111	5.23	5.25	5.29	5.22	4770927.0	25088916.0	-0.007561