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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 view_portfolio_loss(token, dstore):
 """ The mean and stddev loss for the full portfolio for each loss type, extracted from the event loss table, averaged over the realizations """

    data = portfolio_loss(dstore)  # shape (R, L)
    loss_types = list(dstore['oqparam'].loss_dt().names)
    header = ['portfolio_loss'] + loss_types
    mean = ['mean'] + [row.mean() for row in data.T]
    stddev = ['stddev'] + [row.std(ddof=1) for row in data.T]
    return rst_table([mean, stddev], header)