Merge branch 'tqdm'

Author: ragrawal

sklearn_pandas/dataframe_mapper.py

@@ -70,7 +70,7 @@ class DataFrameMapper(BaseEstimator, TransformerMixin):
     """
 
     def __init__(self, features, default=False, sparse=False, df_out=False,
-                 input_df=False, show_progress=False):
+                 input_df=False, show_progressbar=False):
         """
         Params:
 
@@ -102,6 +102,9 @@ def __init__(self, features, default=False, sparse=False, df_out=False,
         input_df    If ``True`` pass the selected columns to the transformers
                     as a pandas DataFrame or Series. Otherwise pass them as a
                     numpy array. Defaults to ``False``.
+
+        show_progressbar    if ``True`` a progress bar will be shown during fit
+                            and transform method. Defaults to ``False``
         """
         self.features = features
         self.built_features = None
@@ -111,7 +114,7 @@ def __init__(self, features, default=False, sparse=False, df_out=False,
         self.df_out = df_out
         self.input_df = input_df
         self.transformed_names_ = []
-        self.show_progress = show_progress
+        self.show_progressbar = show_progressbar
 
         if (df_out and (sparse or default)):
             raise ValueError("Can not use df_out with sparse or default")
@@ -211,7 +214,7 @@ def fit(self, X, y=None):
 
         """
         self._build()
-        pbar = tqdm(self.built_features, disable=not self.show_progress)
+        pbar = tqdm(self.built_features, disable=not self.show_progressbar)
         for columns, transformers, options in pbar:
             pbar.set_description("[Fit] %s" % columns)
             input_df = options.get('input_df', self.input_df)
@@ -299,10 +302,9 @@ def _transform(self, X, y=None, do_fit=False):
         if do_fit:
             self._build()
 
-
         extracted = []
         self.transformed_names_ = []
-        pbar = tqdm(self.built_features, disable=not self.show_progress)
+        pbar = tqdm(self.built_features, disable=not self.show_progressbar)
         for columns, transformers, options in pbar:
             pbar.set_description("[Transform] %s" % columns)
             input_df = options.get('input_df', self.input_df)

tests/test_dataframe_mapper.py

@@ -14,7 +14,7 @@
 import pandas as pd
 from scipy import sparse
 from sklearn import __version__ as sklearn_version
-from sklearn.cross_validation import cross_val_score as sklearn_cv_score
+from sklearn.model_selection import cross_val_score as sklearn_cv_score
 from sklearn.datasets import load_iris
 from sklearn.pipeline import Pipeline
 from sklearn.svm import SVC

tox.ini

@@ -1,20 +1,16 @@
 [tox]
-envlist = {py27,py36}-sklearn{17,18,19}-pandas{19,22}
+envlist = {py36}-sklearn{23}-pandas{1}
 
 [testenv]
 deps =
-    pytest==3.2.1
-    setuptools==39.0
-    wheel==0.24.0
-    flake8==2.4.1
-    numpy==1.14.3
-    scipy==0.18.1
-    pandas19: pandas==0.19.2
-    pandas22: pandas==0.22.0
-    sklearn17: scikit-learn==0.17.1
-    sklearn18: scikit-learn==0.18.1
-    sklearn19: scikit-learn==0.19.1
-    py27: mock==1.3.0
+    pytest==5.3.5
+    setuptools==45.2
+    wheel==0.34.2
+    flake8==3.7.9
+    numpy==1.18.1
+    scipy==1.4.1
+    pandas1: pandas==1.0.5
+    sklearn23: scikit-learn==0.23.1
 
 commands =
     flake8 --exclude build