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-0.1.4.tar.gz
(15.1 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
File details
Details for the file automatedcleaning-0.1.4.tar.gz.
File metadata
- Download URL: automatedcleaning-0.1.4.tar.gz
- Upload date:
- Size: 15.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.11.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
bbe9064aac1279e4011441ff05392258e2d6d6f0671947ecf88a6ba50ab89117
|
|
| MD5 |
cabf0d78d404fce8a0b3dbd00e74d665
|
|
| BLAKE2b-256 |
43dd19d7f3cab91930ff7271cdf41d3463158aec231abfd82b82b446e7c453fe
|
File details
Details for the file automatedcleaning-0.1.4-py3-none-any.whl.
File metadata
- Download URL: automatedcleaning-0.1.4-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 |
42f77e3901006cde234dca5a2bd63e4f95e844656a9b92ffa0db96635f453362
|
|
| MD5 |
2d153da6262ba5cf48ec4010ef0d630f
|
|
| BLAKE2b-256 |
03ce6e2ce68b0a89848ee78d172c8edcf6f6478e79010c36f683e39ca5a2acc5
|