72ac0daa7bd60936eeb563b2c352c9a6631f50fc,featuretools/computational_backends/calculate_feature_matrix.py,,calculate_feature_matrix,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,38

Before Change

            cutoff_time.rename(columns={not_instance_id[0]: "time"}, inplace=True)
        if cutoff_time["time"].dtype == object:
            if (entityset.time_type == NumericTimeIndex and
                    cutoff_time["time"].dtype.name.find("int") == -1 and
                    cutoff_time["time"].dtype.name.find("float") == -1):
                raise TypeError("cutoff_time times must be numeric: try casting via pd.to_numeric(cutoff_time["time"])")
            elif (entityset.time_type == DatetimeTimeIndex and
                  cutoff_time["time"].dtype.name.find("time") == -1):

After Change

            raise TypeError("cutoff_time times must be numeric: try casting "
                            "via pd.to_numeric(cutoff_time["time"])")
    elif entityset.time_type == DatetimeTimeIndex:
        if cutoff_time["time"].dtype.name not in PandasTypes._pandas_datetimes:
            raise TypeError("cutoff_time times must be datetime type: try casting via pd.to_datetime(cutoff_time["time"])")
    assert (cutoff_time[["instance_id", "time"]].duplicated().sum() == 0), \
        "Duplicated rows in cutoff time dataframe."

Instances