def test_df_sum(): test_df = sloth.dataframe(test_data) sum_list = test_df.sum() expected_sum_list = [ 'String col', 18, 2, 30, -0.5612979999999999, 'String col' ] assert sum_list == expected_sum_list
def test_df_mean(): test_df = sloth.dataframe(test_data) mean_list = test_df.mean() expected_mean_list = [ 'String col', 3.6, 0.4, 6.0, -0.11225959999999997, 'String col' ] assert mean_list == expected_mean_list
def check_df_sum(): test_df = dataframe(test_data) sum_list = test_df.sum() expected_sum_list = [ 'String col', 18, 2, 21, -0.8375299999999999, 'String col' ] assert sum_list == expected_sum_list
def check_df_mean(): test_df = dataframe(test_data) mean_list = test_df.mean() expected_mean_list = [ 'String col', 3.6000000000000005, 0.4, 4.2, -0.16750599999999993, 'String col' ] assert mean_list == expected_mean_list
def check_df_nparray(): test_df = dataframe(test_data) for array in test_df.columns: assert isinstance(test_df[array], np.ndarray)
def check_df_median(): test_df = dataframe(test_data) median_list = test_df.median() expected_median_list = ['String col', 4, 0, 2, 0.0, 'String col'] assert median_list == expected_median_list
def test_set_item(): test_df = sloth.dataframe(test_data) dfcolumns = test_df.columns expected_column2 = test_data.keys() assert dfcolumns == expected_column2
def test_set_item(): test_df = sloth.dataframe(test_data) dflen = len(test_df) expected_column2 = 5 assert dflen == expected_column2
def test_df_showrow(): test_df = sloth.dataframe(test_data) row_list = test_df.showrow(3) expected_row_list = ['fish', 0, 0, 8, 1.047249, False] assert row_list == expected_row_list
def check_df_showrow(): test_df = dataframe(test_data) row_list = test_df.showrow(3) expected_row_list = f"Row nº3: ['fish', 0, 0, 8, 1.047249, False]" assert row_list == expected_row_list
def test_df_min(): test_df = sloth.dataframe(test_data) min_list = test_df.min() expected_min_list = ['cat', 0, 0, 1, -1.509059, False] assert min_list == expected_min_list
def test_df_index(): test_df = sloth.dataframe(test_data) column2 = test_df["num_legs"] expected_column2 = np.array([2, 4, 8, 0, 4]) assert all(column2 == expected_column2)
def check_df_max(): test_df = dataframe(test_data) max_list = test_df.max() expected_max_list = ['monkey', 8, 2, 9, 1.047249, False] assert max_list == expected_max_list
def test_df_median(): test_df = sloth.dataframe(test_data) median_list = test_df.median() expected_median_list = ['String col', 4, 0, 8, 0.119209, 'String col'] assert median_list == expected_median_list
def test_set_item(): test_df = sloth.dataframe(test_data) test_df["num_legs"] = 2 expected_column2 = np.array([2, 2, 2, 2, 2]) assert all(test_df["num_legs"] == expected_column2)
def test_df_max(): test_df = sloth.dataframe(test_data) max_list = test_df.max() expected_max_list = ['spider', 8, 2, 10, 1.047249, True] assert max_list == expected_max_list
def test_set_item(): test_df = sloth.dataframe(test_data) dfindex = test_df.index expected_column2 = np.array([0, 1, 2, 3, 4]) assert all(dfindex == expected_column2)
def test_df_columns(): test_df = sloth.dataframe(test_data) col_list = list(test_df.columns) expect_col_list = ['species','num_legs','num_wings','num_specimen_seen','statistics','mammal'] assert col_list == expect_col_list