def test_has_columns():
df_1 = pd.DataFrame(dict(a=[1, 2, 3]))
df_2 = pd.DataFrame(dict(b=[7, 8, 9], a=[1, 2, 3]))
assert has_columns(df_1, ["a"])
assert has_columns(df_2, ["a"])
assert has_columns(df_2, ["a", "b"])
assert not has_columns(df_2, ["a", "b", "c"])
def test_has_columns():
df_1 = pd.DataFrame(dict(a=[1, 2, 3]))
df_2 = pd.DataFrame(dict(b=[7, 8, 9], a=[1, 2, 3]))
assert has_columns(df_1, ['a'])
assert has_columns(df_2, ['a'])
assert has_columns(df_2, ['a', 'b'])
assert not has_columns(df_2, ['a', 'b', 'c'])
def test_has_columns():
df_1 = pd.DataFrame(dict(a=[1, 2, 3]))
df_2 = pd.DataFrame(dict(b=[7, 8, 9], a=[1, 2, 3]))
assert has_columns(df_1, ['a'])
assert has_columns(df_2, ['a'])
assert has_columns(df_2, ['a', 'b'])
assert not has_columns(df_2, ['a', 'b', 'c'])
def check_column_dtypes_wrapper(
rating_true,
rating_pred,
col_user=DEFAULT_USER_COL,
col_item=DEFAULT_ITEM_COL,
col_rating=DEFAULT_RATING_COL,
col_prediction=DEFAULT_PREDICTION_COL,
*args,
**kwargs
):
"""Check columns of DataFrame inputs
Args:
rating_true (pd.DataFrame): True data
rating_pred (pd.DataFrame): Predicted data
col_user (str): column name for user
col_item (str): column name for item
col_rating (str): column name for rating
col_prediction (str): column name for prediction
"""
if not has_columns(rating_true, [col_user, col_item, col_rating]):
raise ValueError("Missing columns in true rating DataFrame")
if not has_columns(rating_pred, [col_user, col_item, col_prediction]):
raise ValueError("Missing columns in predicted rating DataFrame")
if not has_same_base_dtype(
rating_true, rating_pred, columns=[col_user, col_item]
):
raise ValueError("Columns in provided DataFrames are not the same datatype")
return func(
rating_true=rating_true,
rating_pred=rating_pred,
col_user=col_user,
col_item=col_item,
col_rating=col_rating,
col_prediction=col_prediction,
*args,
**kwargs
)
def check_column_dtypes_wrapper(
rating_true,
rating_pred,
col_user=DEFAULT_USER_COL,
col_item=DEFAULT_ITEM_COL,
col_rating=DEFAULT_RATING_COL,
col_prediction=DEFAULT_PREDICTION_COL,
*args,
**kwargs
):
"""Check columns of DataFrame inputs
Args:
rating_true (pd.DataFrame): True data
rating_pred (pd.DataFrame): Predicted data
col_user (str): column name for user
col_item (str): column name for item
col_rating (str): column name for rating
col_prediction (str): column name for prediction
"""
if not has_columns(rating_true, [col_user, col_item, col_rating]):
raise ValueError("Missing columns in true rating DataFrame")
if not has_columns(rating_pred, [col_user, col_item, col_prediction]):
raise ValueError("Missing columns in predicted rating DataFrame")
if not has_same_base_dtype(
rating_true, rating_pred, columns=[col_user, col_item]
):
raise ValueError("Columns in provided DataFrames are not the same datatype")
return func(
rating_true=rating_true,
rating_pred=rating_pred,
col_user=col_user,
col_item=col_item,
col_rating=col_rating,
col_prediction=col_prediction,
*args,
**kwargs
)