@@ -70,7 +70,7 @@ class DataFrameMapper(BaseEstimator, TransformerMixin):
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"""
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def __init__ (self , features , default = False , sparse = False , df_out = False ,
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- input_df = False ):
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+ input_df = False , show_progress = False ):
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"""
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Params:
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@@ -111,6 +111,7 @@ def __init__(self, features, default=False, sparse=False, df_out=False,
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self .df_out = df_out
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self .input_df = input_df
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self .transformed_names_ = []
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+ self .show_progress = show_progress
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if (df_out and (sparse or default )):
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raise ValueError ("Can not use df_out with sparse or default" )
@@ -210,7 +211,7 @@ def fit(self, X, y=None):
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"""
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self ._build ()
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- pbar = tqdm (self .built_features )
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+ pbar = tqdm (self .built_features , disable = not self . show_progress )
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for columns , transformers , options in pbar :
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pbar .set_description ("[Fit] %s" % columns )
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input_df = options .get ('input_df' , self .input_df )
@@ -292,7 +293,7 @@ def _transform(self, X, y=None, do_fit=False):
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extracted = []
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self .transformed_names_ = []
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- pbar = tqdm (self .built_features )
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+ pbar = tqdm (self .built_features , disable = not self . show_progress )
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for columns , transformers , options in pbar :
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pbar .set_description ("[Transform] %s" % columns )
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input_df = options .get ('input_df' , self .input_df )
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