added xai

xai/__init__.py

@@ -70,7 +70,7 @@ def convert_categories(
     tmp_df = df.copy()
 
     if not len(categorical_cols):
-        categorical_cols = df.select_dtypes(include=[np.object]).columns
+        categorical_cols = df.select_dtypes(include=[np.object, np.bool]).columns
 
     tmp_df[categorical_cols] = tmp_df[categorical_cols].astype('category')
     tmp_df[categorical_cols] = tmp_df[categorical_cols].apply(lambda x: x.cat.codes)
@@ -113,7 +113,7 @@ def group_by_columns(
     """
 
     if not len(categorical_cols):
-        categorical_cols = df.select_dtypes(include=[np.object]).columns
+        categorical_cols = df.select_dtypes(include=[np.object, np.bool]).columns
 
     group_list = []
     for c in columns:
@@ -175,7 +175,7 @@ def show_imbalance(
     """
 
     if not len(categorical_cols):
-        categorical_cols = df.select_dtypes(include=[np.object]).columns
+        categorical_cols = df.select_dtypes(include=[np.object, np.bool]).columns
 
     cols = cross + [column_name]
     grouped = group_by_columns(
@@ -249,7 +249,7 @@ def show_imbalances(
         columns = df.columns
 
     if not len(categorical_cols):
-        categorical_cols = df.select_dtypes(include=[np.object]).columns
+        categorical_cols = df.select_dtypes(include=[np.object, np.bool]).columns
 
     if cross and any([x in columns for x in cross]):
         raise("Error: Columns in 'cross' are also in 'columns'")
@@ -318,7 +318,7 @@ def balance(
     """
 
     if not len(categorical_cols):
-        categorical_cols = df.select_dtypes(include=[np.object]).columns
+        categorical_cols = df.select_dtypes(include=[np.object, np.bool]).columns
 
     cols = cross + [column_name]
     grouped = group_by_columns(
@@ -407,7 +407,7 @@ def correlations(
     else:
 
         if not len(categorical_cols):
-            categorical_cols = df.select_dtypes(include=[np.object]).columns
+            categorical_cols = df.select_dtypes(include=[np.object, np.bool]).columns
 
         cols = [c for c in df.columns if c not in categorical_cols]
 
@@ -451,7 +451,7 @@ def balanced_train_test_split(
         cross = ["target"] + cross
 
     if not len(categorical_cols):
-        categorical_cols = list(tmp_df.select_dtypes(include=[np.object]).columns)
+        categorical_cols = list(tmp_df.select_dtypes(include=[np.object, np.bool]).columns)
 
     # TODO: Enable for non-categorical targets
     categorical_cols = ["target"] + categorical_cols
@@ -593,7 +593,7 @@ def metrics_imbalances(
         columns = x_test.columns
 
     if not len(categorical_cols):
-        categorical_cols = x_test.select_dtypes(include=[np.object]).columns
+        categorical_cols = x_test.select_dtypes(include=[np.object, np.bool]).columns
 
     results = []
     for col in columns:
@@ -678,7 +678,7 @@ def roc_imbalances(
         columns = x_test.columns
 
     if not len(categorical_cols):
-        categorical_cols = x_test.select_dtypes(include=[np.object]).columns
+        categorical_cols = x_test.select_dtypes(include=[np.object, np.bool]).columns
 
     results = []
     for col in columns:
@@ -761,7 +761,7 @@ def pr_imbalances(
         columns = x_test.columns
 
     if not len(categorical_cols):
-        categorical_cols = x_test.select_dtypes(include=[np.object]).columns
+        categorical_cols = x_test.select_dtypes(include=[np.object, np.bool]).columns
 
     results = []
     for col in columns: