A package for preprocessing financial datasets
Project description
Financial Dataset Preprocessor
A Python package for preprocessing financial datasets from various sources. This package provides tools and utilities for cleaning, transforming, and preparing financial data for analysis.
Features
- Menu 2205 Preprocessor
- Corporation Name Finder
- Domestic Beneficiary Certificates Processing
- Domestic Bonds Analysis
- Repo Agreement Processing
- Borrowings Management
- Additional preprocessors for other financial datasets (coming soon)
Installation
You can install the package using pip:
pip install financial_dataset_preprocessor
Requirements
- Python >= 3.11
- Dependencies are listed in requirements.txt
Usage Examples
1. Search for Funds with Bonds
from financial_dataset_preprocessor.menu2205_preprocessor.menu2205_applications.domestic_bonds import (
search_funds_having_domestic_bonds,
get_domestic_bonds_by_fund
)
# Get all funds that have domestic bonds
fund_bonds = search_funds_having_domestic_bonds(date_ref='2025-02-21')
# Get bond details for a specific fund
fund_code = '100075'
bond_details = get_domestic_bonds_by_fund(fund_code=fund_code, date_ref='2025-02-21')
2. Analyze Fund Borrowings
from financial_dataset_preprocessor.menu2205_preprocessor.menu2205_applications.borrowings import (
search_funds_having_borrowings,
get_borriwings_by_fund
)
# Find funds with borrowings
funds_with_borrowings = search_funds_having_borrowings(date_ref='2025-02-21')
# Get borrowing details
fund_code = '100075'
borrowing_details = get_borriwings_by_fund(fund_code=fund_code, date_ref='2025-02-21')
3. Check Repo Agreements
from financial_dataset_preprocessor.menu2205_preprocessor.menu2205_applications.repos import (
search_funds_having_repos,
get_repos_by_fund
)
# Find funds with repos
funds_with_repos = search_funds_having_repos(date_ref='2025-02-21')
# Get repo details for a specific fund
fund_code = '100075'
repo_details = get_repos_by_fund(fund_code=fund_code, date_ref='2025-02-21')
Development
To set up the development environment:
- Clone the repository
- Create a virtual environment
- Install dependencies:
pip install -r requirements.txt
License
This project is licensed under a proprietary license. All rights reserved.
Terms of Use
- Source code viewing and forking is allowed
- Commercial use is prohibited without explicit permission
- Redistribution or modification of the code is prohibited
- Academic and research use is allowed with proper attribution
Author
June Young Park
AI Management Development Team Lead & Quant Strategist at LIFE Asset Management
LIFE Asset Management is a hedge fund management firm that integrates value investing and engagement strategies with quantitative approaches and financial technology, headquartered in Seoul, South Korea.
Contact
- Email: juneyoungpaak@gmail.com
- Location: TWO IFC, Yeouido, Seoul
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file financial_dataset_preprocessor-0.1.0.tar.gz.
File metadata
- Download URL: financial_dataset_preprocessor-0.1.0.tar.gz
- Upload date:
- Size: 24.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.11.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
2c5c3cc62d64b9804ea64b9711e3583491cd2538cb48b311a3757fc85737a1ff
|
|
| MD5 |
f10fa371270b333e7f8573e9083ce864
|
|
| BLAKE2b-256 |
ae9ebad877e54e4ed56c04b56f3d93c56abefc3997f98ff4ee03182d2232c30c
|
File details
Details for the file financial_dataset_preprocessor-0.1.0-py3-none-any.whl.
File metadata
- Download URL: financial_dataset_preprocessor-0.1.0-py3-none-any.whl
- Upload date:
- Size: 52.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.11.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
55796bae118f94bf4a8ff19b4ef6cdd71afc23c0c636ee5371fbf7397f8a75db
|
|
| MD5 |
f28ec379d09f64c25a945658ec36449a
|
|
| BLAKE2b-256 |
f582b1abc675e6fb8c5725b371ec3e1e2cc00cce77c43f339049c3948adcabfb
|