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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 from_frame(cls, df, sortorder=None, names=None):
 """ Make a MultiIndex from a DataFrame. .. versionadded:: 0.24.0 Parameters df : DataFrame DataFrame to be converted to MultiIndex. sortorder : int, optional Level of sortedness (must be lexicographically sorted by that level). names : list-like, optional If no names are provided, use the column names, or tuple of column names if the columns is a MultiIndex. If a sequence, overwrite names with the given sequence. Returns ------- MultiIndex The MultiIndex representation of the given DataFrame. See Also -------- MultiIndex.from_arrays : Convert list of arrays to MultiIndex. MultiIndex.from_tuples : Convert list of tuples to MultiIndex. MultiIndex.from_product : Make a MultiIndex from cartesian product of iterables. Examples -------- a b 0 HI Temp 1 HI Precip 2 NJ Temp 3 NJ Precip MultiIndex(levels=[['HI', 'NJ'], ['Precip', 'Temp']], codes=[[0, 0, 1, 1], [1, 0, 1, 0]], names=['a', 'b']) Using explicit names, instead of the column names MultiIndex(levels=[['HI', 'NJ'], ['Precip', 'Temp']], codes=[[0, 0, 1, 1], [1, 0, 1, 0]], names=['state', 'observation']) """

        if not isinstance(df, ABCDataFrame):
            raise TypeError("Input must be a DataFrame")

        column_names, columns = lzip(*df.iteritems())
        names = column_names if names is None else names
        return cls.from_arrays(columns, sortorder=sortorder, names=names)