from typing import List


def get_drop_columns_binary(categoricals: List[str], columns: List[str]) -> List[str]:
    """
    Selects the columns which can be dropped for one-hot-encoded dfs without drop_first.

    Is mainly needed to transform into drop_first encoding

    Parameters
    ----------
    categoricals: non encoded categorical feature names
    columns: one-hot-encoded features without drop_first

    Returns
    -------
    List of features to drop
    """
    list_drop = [
        c for c in columns if c.split("_")[0] in [c.split("_")[0] for c in categoricals]
    ]
    return list_drop[::2]