semvec/pypi-packages huggingface dataset:
justnlp 0.2.2
A low-code library to automate baseline exploratory data analysis (EDA) and modelling for natural language processing (NLP).
License: Apache-2.0
Requires Python: >=3.7.1,<4.0

# JustNLP


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A low-code library to automate baseline exploratory data analysis (EDA) and modelling for natural language processing (NLP).


* Documentation: <https://cheeyeelim.github.io/justnlp>
* GitHub: <https://github.com/cheeyeelim/justnlp>
* PyPI: <https://pypi.org/project/justnlp/>
* Free software: Apache-2.0

- [JustNLP](#justnlp)
  - [Features](#features)
  - [How to Install](#how-to-install)
  - [How to Use](#how-to-use)
  - [Supported Languages](#supported-languages)
  - [Credits](#credits)

## Features

* `run_eda` - Generate an EDA report that includes the following checks :
    * Missing data
    * Abnormal document / word lengths
    * Multiple character encodings
    * Multiple languages
    * Word & stopword distributions
    * Sentiment distribution

## How to Install

```bash
pip install justnlp
```

## How to Use

```python
from justnlp.core import JustNLPEDA

# Get data
from sklearn.datasets import fetch_20newsgroups

newsgroups_all = fetch_20newsgroups(subset="all", categories=["alt.atheism"])
all_df = pd.DataFrame(newsgroups_all.data, columns=["text"])

# Create EDA object
eda_obj = JustNLPEDA(data_df=all_df, text_col="text", method="noun")

# Run EDA
eda_obj.run_eda()

# Save outputs
eda_obj.save_data("./output/processed_data.csv")
eda_obj.to_html("./output/report.html")
eda_obj.to_jupyter()
```

## Supported Languages

Currently this library only supports English.

## Credits

This package was created with [Cookiecutter](https://github.com/audreyr/cookiecutter) and the [cheeyeelim/cookiecutter-pypackage](https://github.com/cheeyeelim/cookiecutter-pypackage) project template.