Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/wakame1367/japanese-addresses
Parsing Japan addresses to prefectures and cities
https://github.com/wakame1367/japanese-addresses
python
Last synced: about 2 months ago
JSON representation
Parsing Japan addresses to prefectures and cities
- Host: GitHub
- URL: https://github.com/wakame1367/japanese-addresses
- Owner: wakame1367
- License: mit
- Created: 2020-08-11T02:20:54.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2022-04-17T11:16:47.000Z (over 2 years ago)
- Last Synced: 2024-11-16T10:46:20.805Z (about 2 months ago)
- Topics: python
- Language: Python
- Homepage:
- Size: 3.11 MB
- Stars: 21
- Watchers: 1
- Forks: 2
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# japanese-addresses
[](https://badge.fury.io/py/japanese-addresses)
[](https://github.com/wakamezake/japanese-addresses/actions?query=workflow%3A%22Python+package%22)
[](https://codecov.io/gh/wakamezake/japanese-addresses)
[](https://mybinder.org/v2/gh/wakamezake/japanese-addresses/master)
Parsing Japan addresses to prefectures and cities.
## Installation
```
pip install japanese-addresses
```
## Examples
```python
from japanese_addresses import separate_address
parsed_address = separate_address('宮城県仙台市泉区市名坂字東裏97-1')
print(parsed_address)
"""
ParsedAddress(prefecture='宮城県', city='仙台市泉区', street='市名坂')
"""
parsed_address = separate_address('鹿児島県志布志市志布志町志布志')
print(parsed_address)
"""
ParsedAddress(prefecture='鹿児島県', city='志布志市', street='志布志町志布志')
"""
```
How to use it in combination with pandas.
```python
import pandas as pd
from japanese_addresses import separate_address
df = pd.read_csv('sample.csv')
df.head()
"""
address
0 宮城県仙台市泉区市名坂字東裏97-1
1 鹿児島県志布志市志布志町志布志
2 東京都 神津島村２８４番
"""
target_col = 'address'
# https://stackoverflow.com/questions/16236684/apply-pandas-function-to-column-to-create-multiple-new-columns
def get_separate_address(address):
parsed_address = separate_address(address)
return parsed_address.prefecture, parsed_address.city, parsed_address.street
df['prefecture'], df['city'], df['street']= zip(*df[target_col].map(get_separate_address))
df.head()
"""
address prefecture city street
0 宮城県仙台市泉区市名坂字東裏97-1 宮城県 仙台市泉区 市名坂
1 鹿児島県志布志市志布志町志布志 鹿児島県 志布志市 志布志町志布志
2 東京都 神津島村２８４番 東京都 神津島村
"""
```
## Testing
```
pip install poetry
poetry install
poetry run pytest
```
## License
Japanese_addresses are licensed under [MIT](https://github.com/wakamezake/japanese-addresses/blob/master/LICENSE)
### [prefecture2city2street.pkl](https://github.com/wakamezake/japanese-addresses/blob/master/japanese_addresses/prefecture2city2street.pkl)
[prefecture2city2street.pkl](https://github.com/wakamezake/japanese-addresses/blob/master/japanese_addresses/prefecture2city2street.pkl) is a derivative work with a modification of [geolonia
/
japanese-addresses](https://github.com/geolonia/japanese-addresses)
Also, [prefecture2city2street.pkl](https://github.com/wakamezake/japanese-addresses/blob/master/japanese_addresses/prefecture2city2street.pkl) was created using [csv_to_dict.py](https://github.com/wakamezake/japanese-addresses/blob/master/scripts/csv_to_dict.py).
### Information on the original work
Here's the link to the original work.
https://geolonia.github.io/japanese-addresses/
[](https://github.com/geolonia/japanese-addresses)
The following is written in Japanese according to the description of the original work.
#### タイトル
Geolonia 住所データ
#### 出典
本データは、以下のデータを元に、毎月 Geolonia にて更新作業を行っています。
- [国土交通省位置参照情報ダウンロードサイト](https://nlftp.mlit.go.jp/cgi-bin/isj/dls/_choose_method.cgi)
- [郵便番号データダウンロード - 日本郵便](https://www.post.japanpost.jp/zipcode/download.html)
#### スポンサー
[一般社団法人 不動産テック協会](https://retechjapan.org/)
#### ライセンス
[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/deed.ja)