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:

python -m pip install .

In Jupyter, install into the active kernel with:

%pip install .

Use in Jupyter

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):

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

Terminal menu

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.