Get started with ‘Lewis Grassic Gibbon First Editions’ with this Jupyter Notebook.

Whether or not you have experience programming or working with data, this Notebook will give you a starting point for analysing digitised text. Using Python and several of its libraries, including Pandas and Natural Language Toolkit (NLTK), the Notebook demonstrates how to:

– Load a folder of text (.TXT) files as a corpus

– Ask questions about the words and sentence structure of all of Gibbon’s works in the collection

– Group Gibbon’s works into subsets, such as the three books in the trilogy, A Scot’s Quair 

Questions this Notebook can help you begin investigating include:

– What are the most common words in Gibbon’s works?

– What are the most common pairs of words (bigrams) in Gibbon’s works?

– How does Gibbon’s vocabulary change from one of his works to another?

– How can one visualise the diversity of Gibbon’s word choice for each year he published a work? 

Sunset Song - Kinraddie map

If you have never used a Jupyter Notebook before, we recommend visiting Tim Sherratt’s introduction to Jupyter Notebooks.

A note on the data

The text used in Exploring Lewis Grassic Gibbon First Editions was digitised with Optical Character Recognition (OCR) and has not been manually corrected. As a result, certain words and numbers may not be accurately represented. For example, incorrect characters may appear such as “ ¬”. Analysis conducted in the Notebook should thus be viewed as estimates and a guide for further research. 

Additionally, due to the historical nature of the dataset (the first editions included were published as early as 1928), its language may include terms or sentiments that are considered inappropriate today. The language of the publications does not reflect the values of the National Library of Scotland. Rather, the language of the publications reflects historical values that offer insight on historical perceptions of places and people.

Access the Notebook

Explore Lewis Grassic Gibbon First Editions in one of three ways:

View in your browser

Open a static version of the Notebook in your browser.

Run an interactive version

Run an interactive version of the Notebook in Binder.

Please note that the interactive version may take several minutes to load.

Some code may not work fully when opened in Binder.

Download from GitHub

Download from GitHub to run locally on your machine with Jupyter Lab, Anaconda, or Miniconda.

Cite this Notebook


Dataset creator: National Library of Scotland

Dataset publisher: National Library of Scotland

Publication year: 2020

Suggested citation: National Library of Scotland. Exploring Lewis Grassic Gibbon First Editions. National Library of Scotland, 2020.

Which dataset did this project use?

This project used Lewis Grassic Gibbon First Editions: Lewis Grassic Gibbon First Editions on the Data Foundry website