Enhance ChnPiiGenerator with Support for Additional Chinese PII Data Types

[MooooCat]

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🚅Description

We would like to enhance the existing ChnPiiGenerator by adding support for more data types. Currently, this generator primarily handles Chinese personal identifiable information (PII) data. Expanding its capabilities to support additional data types will improve its applicability and functionality.

The PR link is #191, which introduces the ChnPiiGenerator class for handling Chinese PII data, including fitting, converting, and reverse converting processes.

🏕Solution(optional)

It is suggested to add support for the following data types in the ChnPiiGenerator:

1. Chinese addresses
2. Unified Social Credit Codes
3. Other common Chinese PII data types

🍰Detail(optional)

In the ChnPiiGenerator class, the fit method can be extended to identify and process new data types. Below is a relevant code snippet from the fit method, you can refer to the following code snippet to understand how existing data types are handled in the ChnPiiGenerator:

    def fit(self, metadata: Metadata | None = None, **kwargs: dict[str, Any]):

        for each_col in metadata.column_list:
            data_type = metadata.get_column_data_type(each_col)
            if data_type == "chinese_name":
                self.chn_name_columns_list.append(each_col)
                continue
            if data_type == "china_mainland_mobile_phone":
                self.chn_phone_columns_list.append(each_col)
                continue
            if data_type == "china_mainland_id":
                self.chn_id_columns_list.append(each_col)
                continue
            if data_type == "chinese_company_name":
                self.chn_company_name_list.append(each_col)

        self.fitted = True