Automated Data Cleaning Library
Project description
AutomatedCleaning
AutomatedCleaning is a Python library for automated data cleaning.It helps preprocess and analyze datasets by handling missing values, outliers, spelling corrections, and more.
Features
- Supports both large (100+ GB) and small datasets
- Detects and handles missing values and duplicate records
- Identifies and corrects spelling errors in categorical values
- Detect outliers
- Detects and fixes data imbalance
- Identifies and corrects skewness in numerical data
- Checks for correlation and detects multicollinearity
- Analyzes cardinality in categorical columns
- Identifies and cleans text columns
- Detect JSON-type columns
- Performs univariate, bivariate, and multivariate analysis
Installation
pip install AutomatedCleaning
Usage
import AutomatedCleaning as ac
df = ac.load_data("dataset.csv")
df_cleaned = ac.clean_data(df)
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
AutomatedCleaning-0.1.8.tar.gz
(14.4 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
File details
Details for the file AutomatedCleaning-0.1.8.tar.gz.
File metadata
- Download URL: AutomatedCleaning-0.1.8.tar.gz
- Upload date:
- Size: 14.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.11.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f37c355ab227a5233b68557ea11eb97ffc6cbd386f090a9ed9510630ea7ff4c6
|
|
| MD5 |
d856c7f5f9667a08be7eb25b11688ff1
|
|
| BLAKE2b-256 |
1540ce4c27f4e08edcf4d482413c3d131379bc73956e8f8927fb1e2c2d8c4504
|
File details
Details for the file AutomatedCleaning-0.1.8-py3-none-any.whl.
File metadata
- Download URL: AutomatedCleaning-0.1.8-py3-none-any.whl
- Upload date:
- Size: 13.4 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 |
391a6b5b562da9d67edbe3cbe386aef5d4134282127a931888cf960955503645
|
|
| MD5 |
f0b153c9413140f8d4f73daab11f8be8
|
|
| BLAKE2b-256 |
68f419b2a622e03cb74fd3a7ab989c6b6f2d76ea19fab08f5015e0a2bd90cc41
|