Metadata-Version: 2.4
Name: pandass-library
Version: 0.1.0
Summary: A small importable library of course Jupyter code notebooks
Author: Pandass contributors
License: MIT
Keywords: jupyter,notebooks,machine-learning,study-library
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Dynamic: license-file

# Pandass

Pandass is a small Python package that bundles six course Jupyter notebooks and makes their code searchable from Python/Jupyter or from a terminal menu.

> The package name is intentionally `pandass`; it is an independent study library, not the official `pandas` project. Check PyPI name availability and naming/trademark considerations before publishing.

## Install locally

Unzip the project, open a terminal in the `pandass-library` folder, then run:

```bash
python -m pip install .
```

In Jupyter, install into the active kernel with:

```python
%pip install .
```

## Use in Jupyter

```python
import pandass

pandass.list_files()                 # list the six bundled notebooks
code = pandass.get_code("knn")       # get all code cells from KNN notebook
print(code)

notebook = pandass.get_notebook("pca-faces")
search_results = pandass.search_code("PCA")
```

Notebook IDs: `lda`, `tensorflow-diabetes`, `pca-faces`, `pca-tensorflow`, `knn`, `k-means`.

To get one code cell (zero-based code-cell index):

```python
print(pandass.get_code("knn", cell=0))
```

## Terminal menu

```bash
python -m pandass
```

## Important notes about the original notebooks

The package preserves the uploaded notebooks; it does not execute them automatically. Some notebooks reference external files that were not included in the six uploads, including `lda.csv`, `diabetes.csv`, `KNN.csv`, and `Kmeans_data.xlsx`. To run those notebook cells, place the relevant data files in your working directory or update the paths. Some notebooks also require third-party libraries such as NumPy, pandas, scikit-learn, Matplotlib, TensorFlow, and openpyxl. Install only the dependencies required for the notebook you want to run.

## Package details

- Distribution name: `pandass`
- Import name: `pandass`
- Version: `0.1.0`
- Python: 3.9+
- The package's own browsing/search functions use the Python standard library and do not require notebook execution dependencies.
