cnparser is a parser library of Corporate Number Publication Site data.


Keywords
python
License
Apache-2.0
Install
pip install cnparser==1.6.4

Documentation

cnparser

Test PyPI - Version

cnparser is a python library for loading and enrichment Corporate Number Publication Site data that is provided from National Tax Agency Japan. cnparser only support to parse latest data now.

Installation


cnparser is available on pip installation.

$ python -m pip install cnparser

GitHub Install

Installing the latest version from GitHub:

$ git clone https://github.com/new-village/cnparser
$ cd cnparser
$ python setup.py install

Usage

This section demonstrates how to use this library to load and process data from the National Tax Agency's Corporate Number Publication Site.

Direct Data Loading

To download data for a specific prefecture, use the load function. By passing the prefecture name as an argument, you can obtain a DataFrame containing data for that prefecture.If you wish to download data for a specific prefecture, you must specify the prefecture name in Roman characters (list of the supported prefectures).
To execute the load function without specifying any arguments, data for all prefectures across Japan will be downloaded.

>>> import cnparser
>>> df = cnparser.load("Shimane")

CSV Data Loading

If you already have a downloaded CSV file, use the read_csv function. By passing the file path as an argument, you can obtain a DataFrame with headers from the CSV data.

>>> import cnparser
>>> df = cnparser.read_csv("path/to/data.csv")

Data Enrichment Functionality

The enrich function standardises and transforms the values of specific fields in the loaded DataFrame.

>>> import cnparser
>>> df = cnparser.enrich(df)

The functions perform all processing, but it is possible to apply only specific processing by defining specific processing as an argument.

>>> import cnparser
>>> df = cnparser.enrich(df, "enrich_kana" ...)

The processes supported by the enrich function are as follows:

  • enrich_kana: Function that adds a standardized furigana column furigana to the DataFrame. It handles data entry by converting name to kana, if furigana is NaN. Note that currently only kanji and katakana conversions are supported. Alphabet conversions are not supported.
  • enrich_kind: Function that adds the kind label to the legal_entity.
  • enrich_post_code: Function that adds the formatted postcode as XXX-XXX to post_code.