How to use the lifetimes.utils._find_first_transactions function in Lifetimes

def test_find_first_transactions_returns_correct_results(large_transaction_level_data):
    today = '2015-02-07'
    actual = utils._find_first_transactions(large_transaction_level_data, 'id', 'date', observation_period_end=today)
    expected = pd.DataFrame([[1, pd.Period('2015-01-01', 'D'), True],
                             [1, pd.Period('2015-02-06', 'D'), False],
                             [2, pd.Period('2015-01-01', 'D'), True],
                             [3, pd.Period('2015-01-01', 'D'), True],
                             [3, pd.Period('2015-01-02', 'D'), False],
                             [3, pd.Period('2015-01-05', 'D'), False],
                             [4, pd.Period('2015-01-16', 'D'), True],
                             [4, pd.Period('2015-02-02', 'D'), False],
                             [4, pd.Period('2015-02-05', 'D'), False],
                             [5, pd.Period('2015-01-16', 'D'), True],
                             [5, pd.Period('2015-01-17', 'D'), False],
                             [5, pd.Period('2015-01-18', 'D'), False],
                             [6, pd.Period('2015-02-02', 'D'), True]], columns=['id', 'date', 'first'])
    assert_frame_equal(actual, expected)

def test_find_first_transactions_with_monetary_values(large_transaction_level_data_with_monetary_value):
    today = '2015-02-07'
    actual = utils._find_first_transactions(large_transaction_level_data_with_monetary_value, 'id', 'date', 'monetary_value', observation_period_end=today)
    expected = pd.DataFrame([[1, pd.Period('2015-01-01', 'D'), 1, True],
                             [1, pd.Period('2015-02-06', 'D'), 2, False],
                             [2, pd.Period('2015-01-01', 'D'), 2, True],
                             [3, pd.Period('2015-01-01', 'D'), 3, True],
                             [3, pd.Period('2015-01-02', 'D'), 1, False],
                             [3, pd.Period('2015-01-05', 'D'), 5, False],
                             [4, pd.Period('2015-01-16', 'D'), 6, True],
                             [4, pd.Period('2015-02-02', 'D'), 3, False],
                             [4, pd.Period('2015-02-05', 'D'), 3, False],
                             [5, pd.Period('2015-01-16', 'D'), 3, True],
                             [5, pd.Period('2015-01-17', 'D'), 1, False],
                             [5, pd.Period('2015-01-18', 'D'), 8, False],
                             [6, pd.Period('2015-02-02', 'D'), 5, True]], columns=['id', 'date', 'monetary_value', 'first'])
    assert_frame_equal(actual, expected)

def test_find_first_transactions_with_monetary_values_with_specific_non_daily_frequency(large_transaction_level_data_with_monetary_value):
    today = '2015-02-07'
    actual = utils._find_first_transactions(large_transaction_level_data_with_monetary_value, 'id', 'date', 'monetary_value', observation_period_end=today, freq='W')
    expected = pd.DataFrame([[1, pd.Period('2014-12-29/2015-01-04', 'W-SUN'), 1, True],
                             [1, pd.Period('2015-02-02/2015-02-08', 'W-SUN'), 2, False],
                             [2, pd.Period('2014-12-29/2015-01-04', 'W-SUN'), 2, True],
                             [3, pd.Period('2014-12-29/2015-01-04', 'W-SUN'), 4, True],
                             [3, pd.Period('2015-01-05/2015-01-11', 'W-SUN'), 5, False],
                             [4, pd.Period('2015-01-12/2015-01-18', 'W-SUN'), 6, True],
                             [4, pd.Period('2015-02-02/2015-02-08', 'W-SUN'), 6, False],
                             [5, pd.Period('2015-01-12/2015-01-18', 'W-SUN'), 12, True],
                             [6, pd.Period('2015-02-02/2015-02-08', 'W-SUN'), 5, True]], columns=['id', 'date', 'monetary_value', 'first'])
    assert_frame_equal(actual, expected)

def test_find_first_transactions_with_specific_non_daily_frequency(large_transaction_level_data):
    today = '2015-02-07'
    actual = utils._find_first_transactions(large_transaction_level_data, 'id', 'date', observation_period_end=today, freq='W')
    expected = pd.DataFrame([[1, pd.Period('2014-12-29/2015-01-04', 'W-SUN'), True],
                             [1, pd.Period('2015-02-02/2015-02-08', 'W-SUN'), False],
                             [2, pd.Period('2014-12-29/2015-01-04', 'W-SUN'), True],
                             [3, pd.Period('2014-12-29/2015-01-04', 'W-SUN'), True],
                             [3, pd.Period('2015-01-05/2015-01-11', 'W-SUN'), False],
                             [4, pd.Period('2015-01-12/2015-01-18', 'W-SUN'), True],
                             [4, pd.Period('2015-02-02/2015-02-08', 'W-SUN'), False],
                             [5, pd.Period('2015-01-12/2015-01-18', 'W-SUN'), True],
                             [6, pd.Period('2015-02-02/2015-02-08', 'W-SUN'), True]],
                            columns=['id', 'date', 'first'],
                            index=actual.index)  # we shouldn't really care about row ordering or indexing, but assert_frame_equals is strict about it
    assert_frame_equal(actual, expected)