Metadata-Version: 1.0
Name: data_box
Version: 0.0.0a1
Summary: clean factor data
Home-page: UNKNOWN
Author: Yili Peng
Author-email: yili_peng@outlook.com
License: UNKNOWN
Description: Data_Box
        ========
        
        This project is to clean factor data and to prepare for back test.
        
        Dependencies
        ------------
        
        -  python 3.5
        -  pandas 0.22.0
        -  numpy 1.14.3
        -  pickle
        -  sklearn 0.19.1 (for pca only)
        
        Example
        -------
        
        .. code:: bash
        
           from data_box import data_box
        
           db=data_box()\
               .set_lag(freq='d',day_lag=0)\
               .load_adjPrice(price)\ # 'price' is a pd.DataFrame with dates(20190101 int type) as its index and tickers as its column
               .load_indestry(ind)\
               .load_suspend(sus)\ 
               .load_indexWeight(index_weight)\
               .calc_indweight()\ # calculate industry weight based on index weight and stocks' industry in this index
               .load_cap(cap)\ 
               .add_factor('f1',factor1)\
               .add_factor('f2',factor2)\
               .add_factor('f3',factor3)\
               .align_data()\
               .factor_pca()\
               .factor_ind_neutral()\
               .factor_size_neutral()\
               .factor_zscore()
        
           print(db.Factor)
           print(db.Price)
           print(db.Sus)
           print(db.Cap)
        
           # save and reload
           db.save(path)
           db2=databox().load(path)
        
Platform: UNKNOWN
