https://github.com/rlskoeser/shxco-missingdata-specreading
replication code and data for missing data, speculative reading article
https://github.com/rlskoeser/shxco-missingdata-specreading
digital-humanities forecasting-time-series humanities-data recommendation-system
Last synced: about 1 year ago
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replication code and data for missing data, speculative reading article
- Host: GitHub
- URL: https://github.com/rlskoeser/shxco-missingdata-specreading
- Owner: rlskoeser
- Created: 2022-03-25T16:07:28.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2024-06-03T16:06:52.000Z (about 2 years ago)
- Last Synced: 2025-04-11T20:33:46.190Z (about 1 year ago)
- Topics: digital-humanities, forecasting-time-series, humanities-data, recommendation-system
- Language: Jupyter Notebook
- Homepage:
- Size: 83.2 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Citation: CITATION.cff
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README
# Replication code and data for “Missing data, Speculative Reading”
This repository provides replication code and data for **Missing Data, Speculative Reading**, by Rebecca Sutton Koeser and Zoe LeBlanc, co-published by *Modernism/modernity PrintPlus* and *Journal of Cultural Analytics* as part of a special issue on “The World of Shakespeare and Company” edited by Joshua Kotin and Rebecca Sutton Koeser.
Read the [article on *Modernism/modernity PrintPlus*](https://modernismmodernity.org/forums/posts/koeser-leblanc-missing-data-speculative-reading); read [article on *Journal of Cultural Analytics*](https://culturalanalytics.org/article/116926-missing-data-speculative-reading).
## Contents
- [data](data) - data specific to this article and source data from the [Shakepeare and Company Project](https://shakespeareandco.princeton.edu/)
- [missing_data](missing_data) - code notebooks for the missing data portion of the article
- [speculative_reading](speculative_reading) - code notebooks for the speculative reading portion of the article
- [appendix](appendix) - additional notebooks with validation, alternate approaches, etc; work that did not make it into the article
- [figures](figures) - exported versions of figures for the article generated by code in multiple formats where supported
- [utils](utils) - utility python code used by multiple notebooks
## Installing dependencies and running code
This code has been tested against **python 3.9**.
To run the code, first clone or download the repository.
Python dependencies are documented in `requirements.txt`. We recommend using
a python virtual environment. Dependencies can be installed with pip:
```sh
pip install -r requirements.lock
```
### Testing
There are unit tests for some utility code, which include checks that data files
are available at the expected locations. To run them, install and run pytest:
```sh
pip install pytest
pytest
```
Code notebooks can be run using jupyter-lab or a jupyter-aware IDE such as VS Code.
They are intended to be run locally, with dependencies installed.
We use [treon](https://github.com/ReviewNB/treon) (`pip install treon`) to
confirm that Jupyter notebooks execute without errors.