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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 get_seaborn_colorbar(dfr, classes):
 """Return a colorbar representing classes, for a Seaborn plot. The aim is to get a pd.Series for the passed dataframe columns, in the form: 0 colour for class in col 0 1 colour for class in col 1 n colour for class in col n """

    levels = sorted(list(set(classes.values())))
    paldict = {
        lvl: pal
        for (lvl, pal) in zip(
            levels,
            sns.cubehelix_palette(
                len(levels), light=0.9, dark=0.1, reverse=True, start=1, rot=-2
            ),
        )
    }
    lvl_pal = {cls: paldict[lvl] for (cls, lvl) in list(classes.items())}
    col_cb = pd.Series(dfr.index).map(lvl_pal)
    # The col_cb Series index now has to match the dfr.index, but
    # we don't create the Series with this (and if we try, it
    # fails) - so change it with this line
    col_cb.index = dfr.index
    return col_cb