diff --git a/src/predictive_variable.py b/src/predictive_variable.py
index cc17aee7..613919ca 100644
--- a/src/predictive_variable.py
+++ b/src/predictive_variable.py
@@ -1,14 +1,15 @@
 import pandas as pd
 
+
 def shift_by_strata_period(
-        df: pd.DataFrame,
-        target: str,
-        period: str,
-        strata: str,
-        reference: str,
-        time_difference: int,
-        new_col: str,
-        **kwargs
+    df: pd.DataFrame,
+    target: str,
+    period: str,
+    strata: str,
+    reference: str,
+    time_difference: int,
+    new_col: str,
+    **kwargs
 ) -> pd.DataFrame:
     """
     It will perform the usual shift by desired time_difference for each value
@@ -40,19 +41,15 @@ def shift_by_strata_period(
         Pandas dataframe of original data with a new column containing the
         shifted values.
     """
-    
-    df.sort_values([reference,strata, period], inplace=True)
-
-    df[new_col] = (
-      df.groupby((
-             (
-                 df[period] - pd.DateOffset(months=1)
-                 != df.shift(1)[period]
-             )
-             | (df[strata].diff(1) != 0)
-             | (df[reference].diff(1) != 0)
-         )
-         .cumsum())
-      .shift(time_difference)[target])
-    
-    return df
\ No newline at end of file
+
+    df.sort_values([reference, strata, period], inplace=True)
+
+    df[new_col] = df.groupby(
+        (
+            (df[period] - pd.DateOffset(months=1) != df.shift(1)[period])
+            | (df[strata].diff(1) != 0)
+            | (df[reference].diff(1) != 0)
+        ).cumsum()
+    ).shift(time_difference)[target]
+
+    return df
diff --git a/tests/test_predictive_variable.py b/tests/test_predictive_variable.py
index 0b3672c0..83a238ef 100644
--- a/tests/test_predictive_variable.py
+++ b/tests/test_predictive_variable.py
@@ -1,34 +1,37 @@
-from src.predictive_variable import shift_by_strata_period
 from pathlib import Path
+
+import pytest
 from helper_functions import load_and_format
 from pandas.testing import assert_frame_equal
 
-import pytest
+from src.predictive_variable import shift_by_strata_period
+
 
 @pytest.fixture(scope="class")
 def predictive_variable_test_data():
     return load_and_format(Path("tests") / "predictive_variable.csv")
 
+
 class TestPredictiveVariable:
     def test_predictive_variable_forward(self, predictive_variable_test_data):
         expected_output = predictive_variable_test_data[
-            ['identifier', 'period', 'group', 'question', 'other',"f_predictive"
-        ]]
+            ["identifier", "period", "group", "question", "other", "f_predictive"]
+        ]
         input_data = expected_output.drop(columns="f_predictive")
         actual_output = shift_by_strata_period(
-            input_data, "question", "period", "group","identifier",1,"f_predictive"
+            input_data, "question", "period", "group", "identifier", 1, "f_predictive"
         )
-        actual_output.sort_index(ascending=True,inplace=True)
+        actual_output.sort_index(ascending=True, inplace=True)
         assert_frame_equal(actual_output, expected_output)
 
     def test_predictive_variable_backward(self, predictive_variable_test_data):
 
         expected_output = predictive_variable_test_data[
-            ['identifier', 'period', 'group', 'question', 'other',"b_predictive"
-        ]]
+            ["identifier", "period", "group", "question", "other", "b_predictive"]
+        ]
         input_data = expected_output.drop(columns="b_predictive")
         actual_output = shift_by_strata_period(
-            input_data, "question", "period", "group","identifier",-1,"b_predictive"
+            input_data, "question", "period", "group", "identifier", -1, "b_predictive"
         )
-        actual_output.sort_index(ascending=True,inplace=True)
-        assert_frame_equal(actual_output, expected_output)
\ No newline at end of file
+        actual_output.sort_index(ascending=True, inplace=True)
+        assert_frame_equal(actual_output, expected_output)