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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 params_mpl(df):
 """Returns dict of matplotlib parameters, dependent on dataframe."""

    return {'ANIb_alignment_lengths': ('afmhot', df.values.min(),
                                       df.values.max()),
            'ANIb_percentage_identity': ('spbnd_BuRd', 0, 1),
            'ANIb_alignment_coverage': ('BuRd', 0, 1),
            'ANIb_hadamard': ('hadamard_BuRd', 0, 1),
            'ANIb_similarity_errors': ('afmhot', df.values.min(),
                                       df.values.max()),
            'ANIm_alignment_lengths': ('afmhot', df.values.min(),
                                       df.values.max()),
            'ANIm_percentage_identity': ('spbnd_BuRd', 0, 1),
            'ANIm_alignment_coverage': ('BuRd', 0, 1),
            'ANIm_hadamard': ('hadamard_BuRd', 0, 1),
            'ANIm_similarity_errors': ('afmhot', df.values.min(),
                                       df.values.max()),
            'TETRA_correlations': ('spbnd_BuRd', 0, 1),
            'ANIblastall_alignment_lengths': ('afmhot', df.values.min(),
                                              df.values.max()),
            'ANIblastall_percentage_identity': ('spbnd_BuRd', 0, 1),
            'ANIblastall_alignment_coverage': ('BuRd', 0, 1),
            'ANIblastall_hadamard': ('hadamard_BuRd', 0, 1),
            'ANIblastall_similarity_errors': ('afmhot', df.values.min(),
                                              df.values.max())}