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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 filter_localization_probability(df, threshold=0.75):
 """ Remove rows with a localization probability below 0.75 Return a ``DataFrame`` where the rows with a value < `threshold` (default 0.75) in column 'Localization prob' are removed. Filters data to remove poorly localized peptides (non Class-I by default). :param df: Pandas ``DataFrame`` :param threshold: Cut-off below which rows are discarded (default 0.75) :return: Pandas ``DataFrame`` """

    df = df.copy()
    localization_probability_mask = df['Localization prob'].values >= threshold
    return df.iloc[localization_probability_mask, :]