def filter_by_dictionary(dictionary_df, column_criteria, equivelancy_criteria, ls_of_dfs):
    """
    Uses the categorical/meta information from one dataframe (in this case, the dictionary dataframe), and uses some criteria
    within it to filter another dataframe.

    Parameters
    ----------
        dictionary_df : a pandas DataFrame with information relating to how you might want to filter the df

        column_criteria : a string that is the column name of what you want to filter by in in dictionary_df

        equivelancy_criteria : what the cells in dictionary_df[column_criteria] are equal to (e.g. 1, False, "<a>", etc.)

        ls_of_dfs : a list of pandas DataFrames that you want to filter by some criteria

    Returns
    --------
        returns : a list of filtered dataframes

        rtype : list of pd DataFrames

    """

    word_selects = dictionary_df[dictionary_df[column_criteria] == equivelancy_criteria]

    new_ls_of_dfs = []

    for i in range(len(ls_of_dfs)):
        temp_df = ls_of_dfs[i]
        temp_df = temp_df[temp_df['word_number'].isin(word_selects['list_number'])]
        new_ls_of_dfs.append(temp_df)

    return(new_ls_of_dfs)