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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 apply(self, func, axis=0, subset=None, **kwargs):
 """ Apply a function column-wise, row-wise, or table-wise, updating the HTML representation with the result. Parameters func : function ``func`` should take a Series or DataFrame (depending on ``axis``), and return an object with the same shape. Must return a DataFrame with identical index and column labels when ``axis=None`` axis : {0 or 'index', 1 or 'columns', None}, default 0 apply to each column (``axis=0`` or ``'index'``), to each row (``axis=1`` or ``'columns'``), or to the entire DataFrame at once with ``axis=None``. subset : IndexSlice a valid indexer to limit ``data`` to *before* applying the function. Consider using a pandas.IndexSlice kwargs : dict pass along to ``func`` Returns ------- self : Styler Notes ----- The output shape of ``func`` should match the input, i.e. if ``x`` is the input row, column, or table (depending on ``axis``), then ``func(x).shape == x.shape`` should be true. This is similar to ``DataFrame.apply``, except that ``axis=None`` applies the function to the entire DataFrame at once, rather than column-wise or row-wise. Examples -------- for v in x] """

        self._todo.append((lambda instance: getattr(instance, '_apply'),
                           (func, axis, subset), kwargs))
        return self