cleanframe-data 🪄
Automated Data Cleaning for Faster Analytics
cleanframe-data is a lightweight, fast, and intuitive Python library designed to automate dataset diagnostics and cleaning. It helps data analysts, scientists, and beginners clean messy datasets, handle missing values, drop low-quality columns, and cap outliers in just one line of code.
🚀 Features
- One-Line Auto-Clean: Drop duplicates, remove low-quality columns, impute missing values, and handle outliers instantly using
cf.auto_clean(df). - Advanced Outlier Handling: Automatically detects and caps extreme numerical outliers using the Interquartile Range (IQR) method.
- Smart Column Dropping: Drops columns automatically if their missing data percentage crosses your defined threshold.
- Dataset Diagnostics: Get a quick, comprehensive report of data types, missing values, and percentages.
- Modern Pandas Ready: Built from the ground up to support modern Pandas (2.0+) Copy-on-Write behaviors without annoying warnings.
🛠️ Installation
You can install the official stable release directly from PyPI:
pip install cleanframe-data
Metadata
Release files for cleanframe-data 0.0.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| cleanframe_data-0.0.6.tar.gz | 4.4 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| cleanframe_data-0.0.6-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.1 kB
Release files / cleanframe_data-0.0.6.tar.gz
| Download URL | cleanframe_data-0.0.6.tar.gz |
|---|---|
| Size | 4.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
fb6dae59c6d82fb704b3c7ceddf646dcc07fe20325bdf5f390d4fca0c78bd1b7
|
|
BLAKE2b-256 checksum How to use checksums |
2bcaafa24dc6d79b9e6637e546b6c0badc1a7b8fc69157dda9fe1baf3422ff01
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.14.3
|
Release files / cleanframe_data-0.0.6-py3-none-any.whl
| Download URL | cleanframe_data-0.0.6-py3-none-any.whl |
|---|---|
| Size | 5.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
643f138c5915afab418dd01f279db0bf17a1e82940739dee98ef4b0dfc3ab5e4
|
|
BLAKE2b-256 checksum How to use checksums |
0e87b647898d6d45409156321e7bc7fe2dd6d475539e2f3eee6dfe506ac2e594
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.14.3
|
Security for cleanframe-data 0.0.6
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.