AutoEDA
One-line automated exploratory data analysis for any dataset.
🚀 Features
- Dataset overview (info, statistics)
- Missing value detection
- Duplicate detection
- Correlation analysis
- Skewness detection
- Clean visualizations
- Target column analysis
📦 Installation
pip install autoeda-prayag
Usage
from autoeda.analyzer import analyze
import pandas as pd
df = pd.read_csv("data.csv")
analyze(df, target="survived")
CLI Usage
autoeda data.csv --target survived
Built With
• Python
• Pandas
• Matplotlib
• Seaborn
1 maintainer
Metadata
1 maintainer
Release files for autoeda-prayag 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 | |
|---|---|---|---|---|
| autoeda_prayag-0.0.6.tar.gz | 3.8 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| autoeda_prayag-0.0.6-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 9.2 kB
Release files / autoeda_prayag-0.0.6.tar.gz
| Download URL | autoeda_prayag-0.0.6.tar.gz |
|---|---|
| Size | 3.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/6.2.0 CPython/3.13.9
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Release files / autoeda_prayag-0.0.6-py3-none-any.whl
| Download URL | autoeda_prayag-0.0.6-py3-none-any.whl |
|---|---|
| Size | 5.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.13.9
|
Security for autoeda-prayag 0.0.6
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