@@ -56,16 +56,15 @@ def read_data(args):
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"""
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# Load datasets
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- occ = pd .read_csv (r '../data/occupancy .csv' , header = 0 , index_col = 0 )
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- duration = pd .read_csv (r '../data/duration .csv' , header = 0 , index_col = 0 )
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- volume = pd .read_csv (r '../data/volume .csv' , header = 0 , index_col = 0 )
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- e_price = pd .read_csv (r '../data/e_price .csv' , index_col = 0 , header = 0 ). values
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- s_price = pd .read_csv (r '../data/s_price .csv' , index_col = 0 , header = 0 ).values
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- adj = pd .read_csv ('../data/adj .csv' , header = 0 , index_col = 0 )
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- adj . columns = adj . columns . astype ( float ). astype ( int ). astype ( str )
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+ inf = pd .read_csv ('../data/inf .csv' , header = 0 , index_col = None )
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+ occ = pd .read_csv ('../data/occupancy .csv' , header = 0 , index_col = 0 )
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+ duration = pd .read_csv ('../data/duration .csv' , header = 0 , index_col = 0 )
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+ volume = pd .read_csv ('../data/volume .csv' , header = 0 , index_col = 0 )
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+ e_price = pd .read_csv ('../data/e_price .csv' , index_col = 0 , header = 0 ).values
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+ s_price = pd .read_csv ('../data/s_price .csv' , index_col = 0 , header = 0 ). values
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+ adj = pd . read_csv ( '../data/adj.csv' , header = 0 , index_col = None )
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adj .index = adj .columns
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- adj = adj .loc [occ .columns ,occ .columns ]
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- adj .to_csv ('../data/adj_filter.csv' )
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+
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time = pd .to_datetime (occ .index )
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feat = occ
@@ -74,7 +73,12 @@ def read_data(args):
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elif args .feat == 'volume' :
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feat = volume
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- # Normalize e_price and s_price data
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+ # Normalize
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+ charge_count_dict = dict (zip (inf ['TAZID' ].astype (str ), inf ['charge_count' ]))
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+ for col in occ .columns :
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+ charge_count = charge_count_dict [col ]
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+ occ [col ] = occ [col ] / charge_count
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+
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price_scaler = MinMaxScaler (feature_range = (0 , 1 ))
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e_price = price_scaler .fit_transform (e_price )
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s_price = price_scaler .fit_transform (s_price )
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