Kazakhstan corporate credit risk factors
Project description
ares-kz
This Python package contains Kazakhstan-specific corporate credit risk factors used for bank-level default prediction models.
Features
- Access to structured dataset of qualitative and quantitative risk factors.
- Optimized for educational and demonstration use.
Usage
from ARES_KZ import load_kz_data
df = load_kz_data()
print(df.head())
License
MIT
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
ares_kz-3.0.0.tar.gz
(22.1 kB
view details)
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
ares_kz-3.0.0-py3-none-any.whl
(22.0 kB
view details)
File details
Details for the file ares_kz-3.0.0.tar.gz.
File metadata
- Download URL: ares_kz-3.0.0.tar.gz
- Upload date:
- Size: 22.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.14.0a2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
480e8c874dbb26cd42380848f66628191ea0975c6642f434f66e9f954e4c3668
|
|
| MD5 |
289239bca4129fc214fa47b460c7e402
|
|
| BLAKE2b-256 |
83f9198e1b0e751cc216076f8321bd01312e6f9435b907de7e0484453a788f51
|
File details
Details for the file ares_kz-3.0.0-py3-none-any.whl.
File metadata
- Download URL: ares_kz-3.0.0-py3-none-any.whl
- Upload date:
- Size: 22.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.14.0a2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
77cf371f77b5c9e991e550ac3ee840edf351c16aedc5a1b3c2470ea238e428c3
|
|
| MD5 |
893e2f9021836814c71755b3906e2ff5
|
|
| BLAKE2b-256 |
884ee3c92b466c49a1938592b9894dc6ec726215a7324846c7d7b423b5d771d8
|
