Merge branch 'dev' of https://github.com/maks-sh/scikit-uplift into dev

sklift/datasets/datasets.py

@@ -228,7 +228,7 @@ def fetch_x5(data_home=None, dest_subdir=None, download_if_missing=True):
                                  dest_filename=file_clients,
                                  download_if_missing=download_if_missing)
     clients = pd.read_csv(csv_clients_path)
-    clients_features = list(clients.column)
+    clients_features = list(clients.columns)
 
     url_purchases = 'https://timds.s3.eu-central-1.amazonaws.com/purchases.csv.gz'
     file_purchases = url_purchases.split('/')[-1]

sklift/metrics/metrics.py

@@ -569,7 +569,7 @@ def uplift_by_percentile(y_true, uplift, treatment, strategy='overall',
         std (bool): If True, add columns with the uplift standard deviation and the response rate standard deviation.
             Default is False.
         total (bool): If True, add the last row with the total values. Default is False.
-            The total uplift is a weighted average uplift. See :func:`.weighted_average_uplift`.
+            The total uplift computes as a total response rate treatment - a total response rate control.
             The total response rate is a response rate on the full data amount.
         bins (int): Determines the number of bins (and the relative percentile) in the data. Default is 10.
         string_percentiles (bool): type of percentiles in the index: float or string. Default is True (string).

sklift/viz/base.py

@@ -28,7 +28,6 @@ def plot_uplift_preds(trmnt_preds, ctrl_preds, log=False, bins=100):
 
     # TODO: Add k as parameter: vertical line on plots
     check_consistent_length(trmnt_preds, ctrl_preds)
-    check_is_binary(treatment)
 
     if not isinstance(bins, int) or bins <= 0:
         raise ValueError(