Advanced Automated EDA Library for comprehensive data analysis
Project description
auto_lm - Advanced Automated EDA Library
auto_lm is a powerful Python library for automated Exploratory Data Analysis (EDA) that provides comprehensive statistical analysis with just a few lines of code.
🚀 Features
- Comprehensive Analysis: Univariate, Multivariate, Correlation, and Causation analysis
- Statistical Tests: Normality tests, ANOVA, Chi-square, and more
- Automated Insights: Detect outliers, multicollinearity, and data quality issues
- Beautiful Output: Results displayed in customized, easy-to-read tables
- Google Colab Ready: Works seamlessly in Google Colab environments
- Target Analysis: Special analysis for supervised learning scenarios
📦 Installation
pip install auto_lm
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
auto_lm-0.1.0.tar.gz
(8.7 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 auto_lm-0.1.0.tar.gz.
File metadata
- Download URL: auto_lm-0.1.0.tar.gz
- Upload date:
- Size: 8.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.9.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
0aee931113ff04a8805ffbebaf06b40439d353e14fb7672c0919659fcbaccdfa
|
|
| MD5 |
c39d03e886460a510db821b540112dea
|
|
| BLAKE2b-256 |
af6309e73e801b63625d1e1bc40abc91c0d1765ee36a27604fea7d85fd6594bd
|
File details
Details for the file auto_lm-0.1.0-py3-none-any.whl.
File metadata
- Download URL: auto_lm-0.1.0-py3-none-any.whl
- Upload date:
- Size: 8.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.9.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
5b052fac26c9e57fc7b0bdcc6f4d31f48aa673676ab3457c007a42b8dae35ab8
|
|
| MD5 |
636c11626cbeacc53e2c88d503814579
|
|
| BLAKE2b-256 |
13546d5e6c2c8bf8c62729a483ed00f713d3112c8338b5f1d4ede2c1e531f0b7
|
