NLPsych 0.1.2

Tools for text analysis, embeddings, and lightweight modeling with a Streamlit app interface.

NLPsych

NLPsych (Natural Language Psychometrics) lets you upload a CSV file, pick your text columns, and get instant descriptive statistics, visualize semantic embeddings, and run predictive models all in one streamlined workflow.

⚙️ Features

• 📊 Descriptive statistics: word counts, sentence lengths, lexical diversity
• 🔎 Embeddings: Sentence-Transformers + dimensionality reduction (PCA, UMAP, t-SNE)
• 🤖 Modeling: Quick logistic regression / ridge regression with cross-validation + permutation tests
• 📑 Reports: Auto-generated HTML/Markdown reports with interpretations

💡 Tip: If you only need the functions, install via pip. If you want the interactive app, clone the repo and run it with Streamlit.

📦 Installation (library only)

To use NLPsych functions in your own Python code:

pip install NLPsych

🚀 Running the app locally

pip install "NLPsych[app]"
nlpsych-app

🛠 Example Usage (library)

import pandas as pd
from nlpsych.descriptive_stats import spacy_descriptive_stats
from nlpsych.embedding import embed_text_columns_simple_base, reduce_embeddings

df = pd.DataFrame({"text": [
    "Hello world. This is a tiny test.",
    "Patient denies chest pain. Vitals stable."
]})

stats_df, overall = spacy_descriptive_stats(df["text"])
print(overall["lexical_diversity"])

meta_df, emb, texts = embed_text_columns_simple_base([df["text"]])
Z = reduce_embeddings(emb, method="pca", n_components=2)

📂 Project structure

root/
├── .devcontainer/
├── .streamlit/   
│   └── config.toml
├── assets/    
│   └── NLPsych_logo.png          
├── src/
│   ├── nlpsych     
│   │   ├── __init__.py
│   │   ├── descriptive_stats.py
│   │   ├── embedding.py
│   │   ├── modeling.py
│   │   ├── report.py
│   │   └── utils.py
│   ├── nlpsych_app/              
│   │   ├── assets/    
│   │   │   └── NLPsych_logo.png          
│   │   ├── __init__.py
│   │   ├── app.py
│   │   └── launch.py
└── tests/              

🖋 License

MIT License © 2025 Shawn Manuel

👇 Contributing

PRs are welcome! If you have feature ideas or bug fixes, feel free to open an issue or submit a pull request.