diff --git a/tests/test_utils.py b/tests/test_utils.py
index 9be26ab..a37c641 100644
--- a/tests/test_utils.py
+++ b/tests/test_utils.py
@@ -1,7 +1,9 @@
 import unittest
 
+import pandas as pd
+
 from tests import d1_path
-from valentine.data_sources.utils import get_encoding, get_delimiter, is_date
+from valentine.data_sources.utils import get_encoding, get_delimiter, is_date, add_noise_to_df_column
 from valentine.utils.utils import is_sorted, convert_data_type
 
 
@@ -30,3 +32,14 @@ def test_get_delimiter(self):
     def test_is_date(self):
         date_str = "2019-04-26 18:03:50.941332"
         assert is_date(date_str)
+
+    def test_add_noise_to_df_column(self):
+        # Tiny chance that this test will fail due to the random nature of the noise
+        test_df = pd.DataFrame({'a': [1.0, 2.0, 3.0], 'b': ['abcdefg', 'hijklmn', 'opqrst']})
+        assert_df = pd.DataFrame({'a': [1.0, 2.0, 3.0], 'b': ['abcdefg', 'hijklmn', 'opqrst']})
+        assert add_noise_to_df_column(test_df, 'a', 0.0)['a'].equals(assert_df['a'])
+        assert add_noise_to_df_column(test_df, 'b', 0.0)['b'].equals(assert_df['b'])
+        assert not add_noise_to_df_column(test_df, 'a', 0.5)['a'].equals(assert_df['a'])
+        assert not add_noise_to_df_column(test_df, 'b', 0.5)['b'].equals(assert_df['b'])
+        assert not add_noise_to_df_column(test_df, 'a', 0.99999)['a'].equals(assert_df['a'])
+        assert not add_noise_to_df_column(test_df, 'b', 0.99999)['b'].equals(assert_df['b'])
diff --git a/valentine/data_sources/utils.py b/valentine/data_sources/utils.py
index 03d5a0a..28c9686 100644
--- a/valentine/data_sources/utils.py
+++ b/valentine/data_sources/utils.py
@@ -65,7 +65,4 @@ def add_noise_to_df_column(df, column_name, noise_level):
         for _ in range(df[column_name].shape[0]):
             if np.random.rand() < noise_level:
                 df[column_name] = df[column_name].apply(lambda x: ''.join(np.random.permutation(list(str(x)))))
-    return df
-
-# if __name__ == "__main__":
-#     add_noise_to_df_column(pd.DataFrame({'a': [1, 2, 3], 'b': ['abcdefg', 'hijklmn', 'opqrst']}), 'b', 0.99)
+    return df
\ No newline at end of file