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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 heatmap(self, df, imagefile):
 """ Create the heat map. """

        import seaborn as sns
        import matplotlib.ticker as tkr
        import matplotlib.pyplot as plt
        from  matplotlib.colors import LinearSegmentedColormap

        sns.set()
        with sns.axes_style('whitegrid'):
            fig, ax = plt.subplots(figsize=(5, 11))  # inches

            cmax = max(df[self.args[2]].max(), self.CMAP_MIN_MAX)
            csteps = {
                0.0: 'darkred', 0.3/cmax: 'red', 0.6/cmax: 'orangered', 0.9/cmax: 'coral',
                1.0/cmax: 'skyblue', 1.5/cmax: 'blue', 1.9/cmax: 'darkblue',
                2.0/cmax: 'darkgreen', 3.0/cmax: 'green',
                (self.CMAP_MIN_MAX - .1)/cmax: 'palegreen', 1.0: 'yellow'}
            cmap = LinearSegmentedColormap.from_list('RdGrYl', sorted(csteps.items()), N=256)

            dataset = df.pivot(*self.args)

            sns.heatmap(dataset, mask=dataset.isnull(), annot=False, linewidths=.5, square=True, ax=ax, cmap=cmap,
                        annot_kws=dict(stretch='condensed'))
            ax.tick_params(axis='y', labelrotation=30, labelsize=8)
            # ax.get_yaxis().set_major_formatter(tkr.FuncFormatter(lambda x, p: x))
            plt.savefig(imagefile)