read and write daily stock data
Project description
This is for reading and writing stock data
Data storage
-path --files filename_20180102.csv filename_20180103.csv . . . filename_20181231.csv
This new version package (still under construction) would also support data stored like below
-path --files filename_A.csv filename_B.csv . . .
Read csv with different structures
example1
ticker1,value1
ticker2,value2
ticker3,value3
ticker4,value4
to read this type of csv file, use
read_df(path='path',file_pattern='filename')
example2
stkid,open,high,low,close
ticker1,o1,h1,l1,c1
ticker2,o2,h2,l2,c2
ticker3,o3,h3,l3,c3
to read open, use
Open=read_df(path='path',file_pattern='filename',dat_col='open')
to read open and close, use
Open,Close=read_df(path='path',file_pattern='filename',dat_col=['open','close'])
to return a multi index dataframe, use
Price=read_mdf(path='path',file_pattern='filename',dat_col=['open','close'])
Write
dataframe example
ticker1 ticker2 ticker3
20180101 10.32 20.22 12.35
20180102 NaN 20.10 13.31
20180105 NaN 20.10 12.12
use write_df to write data of each date to one csv file
dictionary example
each value in the dictionary should be a dataframe and be like the example showed above
write_factors(path='path',file_pattern='filename',**dictionary)
Notice
Default reading trading calendar is Chinese market trading calendar, to change the calendar use dt_range option to input all dates.
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