shxco-missingdata-specreading
replication code and data for missing data, speculative reading article
Science Score: 26.0%
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Low similarity (11.0%) to scientific vocabulary
Keywords
Repository
replication code and data for missing data, speculative reading article
Basic Info
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- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
- Releases: 1
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Metadata Files
README.md
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; read article on Journal of Cultural Analytics.
Contents
- data - data specific to this article and source data from the Shakepeare and Company Project
- missing_data - code notebooks for the missing data portion of the article
- speculative_reading - code notebooks for the speculative reading portion of the article
- appendix - additional notebooks with validation, alternate approaches, etc; work that did not make it into the article
- figures - exported versions of figures for the article generated by code in multiple formats where supported
- 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 (pip install treon) to
confirm that Jupyter notebooks execute without errors.
Owner
- Name: Rebecca Sutton Koeser
- Login: rlskoeser
- Kind: user
- Company: @Princeton-CDH
- Website: http://rlskoeser.github.io
- Twitter: suttonkoeser
- Repositories: 34
- Profile: https://github.com/rlskoeser
Lead Research Software Engineer @Princeton-CDH. Previously software engineer at @emory-libraries and contributor to @ecds, @emory-lits-labs
GitHub Events
Total
- Issues event: 1
- Issue comment event: 1
Last Year
- Issues event: 1
- Issue comment event: 1
Issues and Pull Requests
Last synced: 9 months ago
All Time
- Total issues: 5
- Total pull requests: 15
- Average time to close issues: 3 months
- Average time to close pull requests: 1 day
- Total issue authors: 2
- Total pull request authors: 2
- Average comments per issue: 1.2
- Average comments per pull request: 1.0
- Merged pull requests: 14
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- ZoeLeBlanc (3)
- rlskoeser (2)
Pull Request Authors
- rlskoeser (18)
- ZoeLeBlanc (12)
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Dependencies
- numpy *
- pandas *
- actions/cache v3 composite
- actions/checkout v3 composite
- actions/setup-python v4 composite