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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def add_margins(df, vars, margins=True):
 """ Add margins to a data frame. All margining variables will be converted to factors. Parameters df : dataframe input data frame vars : list a list of 2 lists | tuples vectors giving the variables in each dimension margins : bool | list variable names to compute margins for. True will compute all possible margins. """

    margin_vars = _margins(vars, margins)
    if not margin_vars:
        return df

    # create margin dataframes
    margin_dfs = [df]
    for vlst in margin_vars[1:]:
        dfx = df.copy()
        for v in vlst:
            dfx.loc[0:, v] = '(all)'
        margin_dfs.append(dfx)

    merged = pd.concat(margin_dfs, axis=0)
    merged.reset_index(drop=True, inplace=True)

    # All margin columns become categoricals. The margin indicator
    # (all) needs to be added as the last level of the categories.
    categories = {}
    for v in itertools.chain(*vars):
        col = df[v]
        if not pdtypes.is_categorical_dtype(df[v].dtype):
            col = pd.Categorical(df[v])
        categories[v] = col.categories
        if '(all)' not in categories[v]:
            categories[v] = categories[v].insert(
                len(categories[v]), '(all)')

    for v in merged.columns.intersection(set(categories)):
        merged[v] = merged[v].astype(
           pdtypes.CategoricalDtype(categories[v]))

    return merged