def sample_perturb(counts_frame, crime_type, pct_change):
    """
    Utility function to increase the counts of specific crime types
    after sampling by a given percentage.
    Inputs : counts_frame, the counts of crime dataframe produced by sampler
             crime_type, string of crime type that we want to increase
                         counts for
             pct_change, the percentage change (negative or positive) of crime
                         counts desired.
    Outputs: new_counts_frame, identical dataframe passed but with increased
                               crime counts for specific crime type
    """

    new_counts_frame = counts_frame.copy()

    mask = (new_counts_frame.Crime_type == crime_type)

    mask_frame = new_counts_frame[mask]

    new_counts_frame.loc[mask,'Counts'] = round(mask_frame.Counts * pct_change, 0)

    # need to set new masked data to int
    new_counts_frame['Counts'] = new_counts_frame['Counts'].astype(int)

    return new_counts_frame