A list of interesting / useful notebooks and other things
Basic Skills
We are going to use Jupyter Notebooks in this class. For a global overview of how Jupyter notebooks work and are used in humanities research, see Quinn Dombrowski’s lesson in The Programming Historian. The links below go to either live notebooks that you can work through, or guide you through some of the same steps that Dombrowski discusses, but with more detail.
-
Working with the Command Line
- A walkthrough, by Chantal Brousseau
- For Windows
- For MacOS
-
Introduction to Jupyter Notebooks; if that link breaks, launch this and then select the notebook from the list.
- Courtesy Nathan Kelber and Ted Lawless for JSTOR Labs, CC-BY
- This notebook introduces Jupyter notebooks and Python for absolute beginners.
- Going further: Kelber and Lawless have a number of notebooks for working with JSTOR’s ‘Data for Research’ dataset creation service; find out more here
-
- A short walkthrough, by Chantal Brousseau
- How to use R on your own machine!
-
Running Jupyter Notebooks on Your Own Machine
- A walkthrough, by Chantal Brousseau
-
How to install R in Jupyter Notebooks
- Run these commands in the R console (you should be able to find it by searching “R” in your applications)
- In reference to step 2, you want to install this system-wide
-
Using Git on the Command Line to Keep your Notebook Under Version Control
- A walkthrough, by Dr. Graham and Chantal Brousseau
-
How to launch your Notebook in a computational binder online with mybinder.org
- A walkthrough, by Chantal Brousseau
Retrieve and Visualize Data
Retrieving data
If the data is already made available on the open web, and it’s in a reasonable format (json or csv) then it’s not too difficult a task.
-
Loading simple data that you’ve found online into a Notebook
-
Using OpenRefine to Obtain Data
- This tutorial adapts the Programming Historian lesson by Evan Peter Williamson “Fetching and Parsing Data from the Web with OpenRefine”, especially its example 2.
- Tutorial link here.
-
Extract Illustrated Pages from the Hathi Trust & Internet Archive
- This tutorial & associated notebooks are developed from Stephen Krewson’s piece for the Programming Historian, “Extracting Illustrated Pages from Digital Libraries with Python”
- Try searching for images related to “Ottawa”.
- Hathi Notebook;
- Internet Archive Notebook
- the json file for the notebooks is in the ‘data’ folder
-
Retrieve data from a ‘datasette’-created API launch binder here
- note that the ‘api_search_url’ variable might need to be changed to point to the survey markers datasette or the CARF excavation datasette re Fort Frontenac (see below for url)
-
Scraper. This notebook adapts this tutorial on beautiful soup to work with data from the Museum of History.
-
Working with web archives, a series of notebooks by Sherratt et al https://glam-workbench.github.io/web-archives/ (including the Internet Archive, so potentially you might find Ottawa things there.)
-
GLAM Notebooks from BVMC.Labs ‘Inspiring computationally-driven research with the British Library’s digital collections’ working with a wide variety of European datasets and archival sources.
-
National Library of Scotland, Data Foundry: A Medical History of British India
-
National Library of Scotland, Data Foundry: Edinburgh Ladies’ Debating Society
Visualize
-
Visualizing Data with Bokeh & Python
- This notebook is the one that accompanies the tutorial by Charlie Harper in The Programming Historian
- You can launch the notebook here; this will let you skip setting up the virtual environment (a way of keeping all of your lego pieces for each task separate so they don’t cause conflicts).
-
There might be useful things in Hands-On Data Visualization; not explicitly about jupyter notebooks, but give it a look.
Documentation
-
Building an API with Datasette
-
Building a documentation website with Mkdocs
- MKDocs is a python module that will turn a folder with markdown documents into a functioning website
Creativity
For when you’re ready/inclined to push things further.
-
- An overview of how and why you might sonify data
-
- An overview of why glitching an image might be one way of letting people play with collections
-
An introduction to ‘Processing’, a language for quick sketches, visualizations, and artwork
- A simple introduction to a language that enables creative expression (Brian Foo, the ‘Data Driven DJ’ uses processing to make visualizations to accompany his sonifications. See for instance his work, Lee and Jackson.)
Ottawa Datasets
Galleries
- National scale
Libraries & Archives
-
LAC
- Notebook that creates datasets from LAC Naturalization Records, 1915-1946 –> could likely be repurposed to extract later records as well
- Black Loyalist Refugees, 1782-1807- Port Roseway Associates
- Canadian Illustrated News, 1869-1883
- Canadian Patents, 1869-1919
- Carleton Papers – Book of Negroes, 1783
- Carleton Papers – Loyalists and British Soldiers, 1772-1784
- Immigrants Before 1865
- Immigrants from the Russian Empire, 1898-1922
- Ukrainian Immigrants, 1891-1930
- Marriage Bonds, 1779-1858 - Upper & Lower Canada
- Open Data
-
- Offers collections of artworks and items from Ottawa historical museums –> cannot find exportable data, would have to be scraped
Museums
-
Ingenium Museum Network
- Open data
- All artifacts in the collection of the Canada Agriculture and Food Museum, Canada Aviation and Space Museum and the Canada Science and Technology Museum
- Available in XML or CSV
- Open data
Misc
-
Student created datasettes:
-
Survey markers from the CSTM (compiled by Sherwin et al) https://cstm-demo2.herokuapp.com/cstm-markers/
-
This API makes available some 400 record cards from the CARF excavations of Fort Frontenac in Kingston. http://fort-frontenac-excavation.herokuapp.com/.
-