Example #1
0
    def test_len_to_should_return_the_number_of_records_where_outcome_and_treatment_are_different(
        self, ):
        df = pd.DataFrame(data=np.random.rand(12, 2), columns=["var1", "var2"])
        df["Outcome"] = [random.sample(range(2), 1)[0] for i in range(12)]
        df["Treatment"] = [random.sample(range(2), 1)[0] for i in range(12)]

        length = df[(df["Treatment"] == 1) & (df["Outcome"] == 0)].shape[0]
        result = utils.len_to(df, outcome=0)

        self.assertEqual(length, result)
Example #2
0
    def test_len_to_should_return_the_number_of_records_where_outcome_and_treatment_is_1(
            self):
        df = pd.DataFrame(data=np.random.rand(12, 2), columns=['var1', 'var2'])
        df['Outcome'] = [random.sample(range(2), 1)[0] for i in range(12)]
        df['Treatment'] = [random.sample(range(2), 1)[0] for i in range(12)]

        length = df[(df['Treatment'] == 1) & (df['Outcome'] == 1)].shape[0]
        result = utils.len_to(df)

        self.assertEqual(length, result)
Example #3
0
    def test_len_to_should_return_the_number_of_records_where_outcome_and_treatment_are_different_with_custom_column_names(
        self
    ):
        df = pd.DataFrame(data=np.random.rand(12, 2), columns=["var1", "var2"])
        df["result"] = [random.sample(range(2), 1)[0] for i in range(12)]
        df["marketed_to"] = [random.sample(range(2), 1)[0] for i in range(12)]

        length = df[(df["marketed_to"] == 1) & (df["result"] == 0)].shape[0]
        result = utils.len_to(
            df, outcome=0, col_outcome="result", col_treatment="marketed_to"
        )

        self.assertEqual(length, result)