def cut_to_specific_word(dataframe, specific_word, part_in_bid):
    """
    Takes in a dataframe and a column, and then creates a new dataframe containing only
    the rows from the original dataframe that had the search word in that column
    :params: a dataframe, a specific_word to look for, and a column name relating to
             a part in a case study in which the specific_word should be searched for
    :return: a dataframe containing only the case studies which had specific word in
             the column of interest
    """
    # Cut dataframe down to only those rows with a word in the right column
    current_df = dataframe[dataframe[part_in_bid].str.contains(r'\b' + specific_word + r'\b', regex=True, na=False)]
    # Suppress the annoyingly pedantic SettingWithCopyWarning,
    # since we know explicitly we're dealing with a copy
    current_df.is_copy = False
    # Add a new col to indicate where the specific word was found
    new_col_name = specific_word + '_found_in_' + part_in_bid
    current_df[new_col_name] = part_in_bid
    # Drop all columns except the case study and the col showing where the word was found
    current_df = current_df[['Case Study Id', new_col_name]]

    return current_df