def none_missing(df, columns=None):
    if columns is None:
        columns = df.columns
    try:
        assert not df[columns].isnull().any().any()
    except AssertionError as e:
        missing = df[columns].isnull()
        msg = generic.bad_locations(missing)
        e.args = msg
        raise
    return df
Asserts that there are no missing values (NaNs) in the DataFrame.
dataset/ETHPy150Open TomAugspurger/engarde/engarde/checks.py/none_missing