Merge pull request #46 from UBC-MDS/scale-tests-add

Fix tests

tests/test_eda_utils_py.py

@@ -173,6 +173,14 @@ def test_cor_map():
 
 
 def test_scaler():
+    data = pd.DataFrame(
+        {
+            "SepalLengthCm": [5.1, 4.9, 4.7],
+            "SepalWidthCm": [1.4, 1.4, 1.3],
+            "PetalWidthCm": [0.2, 0.1, 0.2],
+            "Species": ["Iris-setosa", "Iris-virginica", "Iris-germanica"],
+        }
+    )
     mock_df_1 = pd.DataFrame(
         {"col1": [1, 0, 0, 3, 4], "col2": [4, 1, 1, 0, 1], "col3": [2, 0, 0, 2, 1]}
     )
@@ -227,19 +235,22 @@ def test_scaler():
 
     # Test if the imput is not dataFrame
     with raises(TypeError):
-        eda_utils_py.scale("A string")
+        eda_utils_py.scale("A string", ['one', 'two'])
 
     # Tests if contents of columns is not of type str
     with raises(TypeError):
-        eda_utils_py.scale(mock_df_1, (1, 2, 3, 4))
+        eda_utils_py.scale(mock_df_1, [1, 2, 3, 4])
+
+    with raises(TypeError):
+        eda_utils_py.scale(mock_df_1, [None])
 
     # Tests if columns do not exist in the dataframe
     with raises(Exception):
         eda_utils_py.scale(mock_df_1, ['one', 'two'])
 
     # Tests if if not all columns in columns are numeric
     with raises(Exception):
-        eda_utils_py.scale(mock_df_1, {'col1': "1", 'col2': "3"})
+        eda_utils_py.scale(data, ['Species'])
 
     # Tests whether data is not of type pd.Dataframe raises TypeError
     with raises(TypeError):