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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 _background_gradient(s, cmap='PuBu', low=0, high=0, text_color_threshold=0.408):
 """ Color background in a range according to the data. """

        if (not isinstance(text_color_threshold, (float, int)) or
                not 0 <= text_color_threshold <= 1):
            msg = "`text_color_threshold` must be a value from 0 to 1."
            raise ValueError(msg)

        with _mpl(Styler.background_gradient) as (plt, colors):
            smin = s.values.min()
            smax = s.values.max()
            rng = smax - smin
            # extend lower / upper bounds, compresses color range
            norm = colors.Normalize(smin - (rng * low), smax + (rng * high))
            # matplotlib colors.Normalize modifies inplace?
            # https://github.com/matplotlib/matplotlib/issues/5427
            rgbas = plt.cm.get_cmap(cmap)(norm(s.values))

            def relative_luminance(rgba):
                """
                Calculate relative luminance of a color.

                The calculation adheres to the W3C standards
                (https://www.w3.org/WAI/GL/wiki/Relative_luminance)

                Parameters
                ----------
                color : rgb or rgba tuple

                Returns
                -------
                float
                    The relative luminance as a value from 0 to 1
                """
                r, g, b = (
                    x / 12.92 if x <= 0.03928 else ((x + 0.055) / 1.055 ** 2.4)
                    for x in rgba[:3]
                )
                return 0.2126 * r + 0.7152 * g + 0.0722 * b

            def css(rgba):
                dark = relative_luminance(rgba) < text_color_threshold
                text_color = '#f1f1f1' if dark else '#000000'
                return 'background-color: {b};color: {c};'.format(
                    b=colors.rgb2hex(rgba), c=text_color
                )

            if s.ndim == 1:
                return [css(rgba) for rgba in rgbas]
            else:
                return pd.DataFrame(
                    [[css(rgba) for rgba in row] for row in rgbas],
                    index=s.index, columns=s.columns
                )