Metadata-Version: 2.1
Name: chafic
Version: 0.1.6
Summary: chakki Financial Report Corpus
Home-page: https://github.com/chakki-works/chaFiC
Author: icoxfog417
Author-email: icoxfog417@yahoo.co.jp
License: MIT
Description: # chaFiC: chakki Financial Report Corpus
        
        [![PyPI version](https://badge.fury.io/py/chafic.svg)](https://badge.fury.io/py/chaFiC)
        [![Build Status](https://travis-ci.org/chakki-works/chaFiC.svg?branch=master)](https://travis-ci.org/chakki-works/chaFiC)
        [![codecov](https://codecov.io/gh/chakki-works/chaFiC/branch/master/graph/badge.svg)](https://codecov.io/gh/chakki-works/chaFiC)
        
        We organized Japanese financial reports to encourage applying NLP techniques to financial analytics.
        
        ## Dataset
        
        You can download dataset by command line tool.
        
        ```
        pip install chafic
        ```
        
        ```
        chafic download --kind F --year 2014
        
        ```
        
        Please refer the usage by `--`.
        
        ```
        chafic --
        ```
        
        ### Raw dataset file
        
        The corpora are separated to each financial years.
        
        | fiscal_year | Raw file version (F) | Text extracted version (E) | 
        |-------------|-------------------|-----------------|
        | 2014        | [.zip (9.3GB)](https://s3-ap-northeast-1.amazonaws.com/chakki.esg.financial.jp/dataset/release/chakki_esg_financial_2014.zip)          | [.zip (270.8MB)](https://s3-ap-northeast-1.amazonaws.com/chakki.esg.financial.jp/dataset/release/chakki_esg_financial_extracted_2014.zip)              | 
        | 2015        | [.zip (9.8GB)](https://s3-ap-northeast-1.amazonaws.com/chakki.esg.financial.jp/dataset/release/chakki_esg_financial_2015.zip)          | [.zip (291.1MB)](https://s3-ap-northeast-1.amazonaws.com/chakki.esg.financial.jp/dataset/release/chakki_esg_financial_extracted_2015.zip)        | 
        | 2016        | [.zip (10.2GB)](https://s3-ap-northeast-1.amazonaws.com/chakki.esg.financial.jp/dataset/release/chakki_esg_financial_2016.zip)          | [.zip (334.7MB)](https://s3-ap-northeast-1.amazonaws.com/chakki.esg.financial.jp/dataset/release/chakki_esg_financial_extracted_2016.zip)              | 
        | 2017        | [.zip (9.1GB)](https://s3-ap-northeast-1.amazonaws.com/chakki.esg.financial.jp/dataset/release/chakki_esg_financial_2017.zip)          | [.zip (310.2MB)](https://s3-ap-northeast-1.amazonaws.com/chakki.esg.financial.jp/dataset/release/chakki_esg_financial_extracted_2017.zip)        | 
        | 2018        | [.zip (10.5GB)](https://s3-ap-northeast-1.amazonaws.com/chakki.esg.financial.jp/dataset/release/chakki_esg_financial_2018.zip)          | [.zip (260.9MB)](https://s3-ap-northeast-1.amazonaws.com/chakki.esg.financial.jp/dataset/release/chakki_esg_financial_extracted_2018.zip)        | 
        
        
        ## Statistics
        
        | fiscal_year | number_of_reports | has_csr_reports | has_financial_data | has_stock_data | 
        |-------------|-------------------|-----------------|--------------------|----------------| 
        | 2014        | 3,724             | 92              | 3,583              | 3,595           | 
        | 2015        | 3,870             | 96              | 3,725              | 3,751           | 
        | 2016        | 4,066             | 97              | 3,924              | 3,941           | 
        | 2017        | 3,578             | 89              | 3,441              | 3,472           | 
        | 2018        | 3,513             | 70              | 2,893              | 3,413           | 
        
        * financial data is from [決算短信情報](http://db-ec.jpx.co.jp/category/C027/).
          * We use non-cosolidated data if it exist.
        * stock data is from [月間相場表（内国株式）](http://db-ec.jpx.co.jp/category/C021/STAT1002.html).
          * `close` is fiscal period end and `open` is 1 year before of it.
        
        ### Content
        
        **Raw file version**
        
        The structure of dataset is following.
        
        ```
        chakki_esg_financial_{year}.zip
        └──{year}
             ├── documents.csv
             └── docs/
        ```
        
        `docs` includes XBRL and PDF file.
        
        * XBRL file of annual reports (files are retrieved from [EDINET]).
        * PDF file of CSR reports (additional content).
        
        `documents.csv` has metadata like following.
        
        * edinet_code: `E0000X`
        * filer_name: `XXX株式会社`
        * fiscal_year: `201X`
        * fiscal_period: `FY`
        * doc_path: `docs/S000000X.xbrl`
        * csr_path: `docs/E0000X_201X_JP_36.pdf`
        
        **Text extracted version**
        
        Text extracted version includes `txt` files that match each part of an annual report.  
        The extracted parts are defined at [`edinet-python`](https://github.com/chakki-works/edinet-python#2-extract-contents-from-xbrl).
        
        ```
        chakki_esg_financial_{year}_extracted.zip
        └──{year}
             ├── documents.csv
             └── docs/
        ```
        
        ## Utilize Data for NLP
        
        We offer the parser for the financial documents based on [GiNZA](https://github.com/megagonlabs/ginza). Please refer the [ficser](https://github.com/chakki-works/ficser) to use this feature.
        
        Example: Parse
        
        ```py
        ```
        
        Example: NER
        
        ```py
        ```
        
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