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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 sapm_spectral_loss(airmass_absolute, module):
 """ Calculates the SAPM spectral loss coefficient, F1. Parameters airmass_absolute : numeric Absolute airmass module : dict-like A dict, Series, or DataFrame defining the SAPM performance parameters. See the :py:func:`sapm` notes section for more details. Returns ------- F1 : numeric The SAPM spectral loss coefficient. Notes ----- nan airmass values will result in 0 output. """


    am_coeff = [module['A4'], module['A3'], module['A2'], module['A1'],
                module['A0']]

    spectral_loss = np.polyval(am_coeff, airmass_absolute)

    spectral_loss = np.where(np.isnan(spectral_loss), 0, spectral_loss)

    spectral_loss = np.maximum(0, spectral_loss)

    if isinstance(airmass_absolute, pd.Series):
        spectral_loss = pd.Series(spectral_loss, airmass_absolute.index)

    return spectral_loss