Add tests + remove duplicate checks in scale function

Author: fatse

eda_utils_py/eda_utils_py.py

@@ -333,7 +333,7 @@ def scale(dataframe, columns, scaler="standard"):
         if col not in list(dataframe.columns):
             raise Exception("The given column names must exist in the given dataframe.")
 
-    # Check if all input columns in num_col are numeric columns
+    # Check if all input columns in columns are numeric columns
     for col in columns:
         if not is_numeric_dtype(dataframe[col]):
             raise Exception("The given numerical columns must all be numeric.")
@@ -342,16 +342,6 @@ def scale(dataframe, columns, scaler="standard"):
     if not isinstance(scaler, str):
         raise TypeError("Scaler must be of type str")
 
-    # Check if all input columns exist in the input data
-    for col in columns:
-        if col not in list(dataframe.columns):
-            raise Exception("The given column names must exist in the given dataframe.")
-
-    # Check if all input columns in num_col are numeric columns
-    for col in columns:
-        if not is_numeric_dtype(dataframe[col]):
-            raise Exception("The given columns must all be numeric.")
-
     scaled_df = None
     if scaler == "minmax":
         scaled_df = _minmax(dataframe[columns])

tests/test_eda_utils_py.py

@@ -225,6 +225,22 @@ def test_scaler():
         mock_df_2, ["col1", "col2"], scaler="minmax"
     )
 
+    # Test if the imput is not dataFrame
+    with raises(TypeError):
+        eda_utils_py.outlier_identifier("A string")
+
+    # Tests if contents of columns is not of type str
+    with raises(TypeError):
+        eda_utils_py.cor_map(mock_df_1, (1, 2, 3, 4))
+
+    # Tests if columns do not exist in the dataframe
+    with raises(Exception):
+        eda_utils_py.cor_map(mock_df_1, ['one', 'two'])
+
+    # Tests if if not all columns in columns are numeric
+    with raises(Exception):
+        eda_utils_py.cor_map(mock_df_1, {'col1': "1", 'col2': "3"})
+
     # Tests whether data is not of type pd.Dataframe raises TypeError
     with raises(TypeError):
         eda_utils_py.scale([14, None, 3, 27])