Install quarto to generate the final document.
Install an Anaconda distribution, either:
- Miniforge3 (recommended),
- Miniconda, or
- Anaconda if you wish.
Once installed, you can create a virtual environment to avoid breaking your applications:
conda create -n acc python=3.11
conda activate acc
conda install pip jupyterlab pandas matplotlib plotly scipy scikit-learn
Connect to the 2024 directory and use quarto to generate the report.
The file "Analysis 2024.ipynb" is a JupyterLab notebook. To edit it, run:
jupyter lab Analysis\ 2024.ipynb
The notebook file should be displayed on your browser, but it has no attached image or computed cells. You need to run the whole notebook using the menu item "Kernel->Restart Kernel and Run All Cells..." to update the visualizations and computed results. It takes a few minutes to finish running.
Then, save the file using the "File -> Save Notebook" menu item. You can then generate the report in htnm format using the following command:
quarto preview Analysis\ 2024.ipynb
Quarto will generate the Analysis\ 2024.html file and show it in a browser.
Don't try to commit and push the notebook to github.com, it is too large. You need to strip it from all the generated cells first using the "Kernel -> Restart Kernel and Clear Outputs of All Cells..." menu item. Then, save the file again (Ctrl-S), and you can commit and push the file.
If you try to commit the big file, you are in trouble since github.com will not let you do anything since the file is too big. The simplest way out is to rename the local repo, clone the original repo, copy the modified stripped files to the clean repo, and commit/push.
There is a database containing information from the PCS conference management web site. It is managed by SQLite and is located in the data/vis-area-chair.db
file. This database is used internally by the notebooks generating the reports.
You can look at its contents using the sqlite3
program that you can install with:
conda install sqlite
To see the contents in detail, use regular SQL SELECT commands. To see the structure of the available tables, you can do as follows:
sqlite3 vis-area-chair.db
sqlite> .schema
CREATE TABLE keywords (kid integer, keyword text);
CREATE TABLE areas (aid integer, area text, legacy integer);
CREATE TABLE submissions (sid integer, confsubid integer, aid integer, decision text, year integer);
CREATE TABLE submissionkeywords (sid integer, kid integer);
CREATE TABLE reviewers (rid integer, year integer);
CREATE TABLE reviewerbids (rid integer, sid integer, match real, bid integer, stat integer);
CREATE TABLE legacyareasurvey (sid integer, aid integer, laid integer);
CREATE TABLE metadata (key text, value text);
sqlite> .exit
To import a new year of submission data received in csv format, assuming it follows the right schema, use the following commands:
sqlite>.mode csv
sqlite>.import submissions-2024.csv submissions
pip install bertopic
- Steven Drucker
- ieee-vgtc/ieeevis-area-chair-committee-data