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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 make_axis_dummies(frame, axis='minor', transform=None):
 """ Construct 1-0 dummy variables corresponding to designated axis labels Parameters frame : DataFrame axis : {'major', 'minor'}, default 'minor' transform : function, default None Function to apply to axis labels first. For example, to get "day of week" dummies in a time series regression you might call:: make_axis_dummies(panel, axis='major', transform=lambda d: d.weekday()) Returns ------- dummies : DataFrame Column names taken from chosen axis """

    numbers = {'major': 0, 'minor': 1}
    num = numbers.get(axis, axis)

    items = frame.index.levels[num]
    codes = frame.index.codes[num]
    if transform is not None:
        mapped_items = items.map(transform)
        codes, items = _factorize_from_iterable(mapped_items.take(codes))

    values = np.eye(len(items), dtype=float)
    values = values.take(codes, axis=0)

    return DataFrame(values, columns=items, index=frame.index)