https://github.com/cmudig/guidedstats
Science Score: 23.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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○DOI references
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✓Academic publication links
Links to: arxiv.org -
○Committers with academic emails
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (11.2%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: cmudig
- License: bsd-3-clause
- Language: Python
- Default Branch: main
- Size: 181 MB
Statistics
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
GuidedStats
GuidedStats assists users with statistical analyses through guided workflows. It automatically verifies assumptions and provides actionable suggestions. It is integrated into notebook coding environment, and exchanges dataset, model and results with the coding environment.
Paper link: Guided Statistical Workflows with Interactive Explanations and Assumption Checking
Install (For Developers)
Tips: you can create a new conda environment to avoid any package conflicts.(Currently fixing errors in jupyter notebooks and jupyter lab>=4.0).
conda create -n test_env jupyter-packaging python=3.11 "jupyterlab<4.0"
First, install the package in editable mode
python -m pip install -e .
And enable widet frontend
```
link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite ```
To build the project
npm install
npm run build
To automatically rebuild the project after editing frontend code
npm run watch
To rebuild after editing python package, you need to restart the kernel.
Install (For Users)
Testing...
Usage (under construction...)
To start with
To initialize the UI, first we need to import GuidedStats and load the dataset into a Pandas DataFrame. Then we pass the DataFrame to GuidedStats.
``` from guidedstats import GuidedStats import pandas as pd
df = pd.readcsv("californiahousing.csv") gs = GuidedStats(df) gs ```
Notice
- Many thanks to Will Epperson and Adam Perer for their kind assistance in my first HCI paper and my early exploration of research interests.
- I am currently focused on incorporating more statistical workflows to empirically demonstrate the scalability of our approach, and simplify the code structure as well.
- As software development is not my primary field of study, I recognize that the code implementation has room for improvement 🙏. I greatly welcome and appreciate any advice or suggestions.
Owner
- Name: CMU Data Interaction Group
- Login: cmudig
- Kind: organization
- Location: Pittsburgh, PA
- Website: https://dig.cmu.edu/
- Repositories: 32
- Profile: https://github.com/cmudig
People, Visualization, Analysis, Machine Learning
GitHub Events
Total
- Issues event: 11
- Watch event: 3
- Push event: 2
Last Year
- Issues event: 11
- Watch event: 3
- Push event: 2
Committers
Last synced: about 1 year ago
Top Committers
| Name | Commits | |
|---|---|---|
| admation | a****0@g****m | 56 |
| Will Epperson | w****p@l****m | 11 |
Issues and Pull Requests
Last synced: about 1 year ago
All Time
- Total issues: 22
- Total pull requests: 4
- Average time to close issues: 5 months
- Average time to close pull requests: 5 days
- Total issue authors: 1
- Total pull request authors: 2
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 2
- 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
- yuqizhang99 (21)
Pull Request Authors
- yuqizhang99 (3)
- willeppy (2)