A project for Stanford's COMM 277T course.
Currently, data for the project is not pushed to this repo to avoid unnecessary steps when trivial changes are made. To populate the data locally, clone this repo and run the following command from the project root:
Rscript scripts/run_data_pipeline.R This should populate all relevant data and HTML files for the website. Current runtime is fairly quick (~45 seconds), but we'll monitor as the data grows.
To run the website for development fire up a python web server:
python -m http.serverThen go to http://localhost:8000 and navigate to appropriate page(s).
It's important to use the web server because using any external JS requires serving the data in the same way as you would in a production setting on the web. If you try to access the HTML file using your browser with the
file://scheme (i.e. without the web server), you will get Cross-Origin (aka CORS) errors when trying to access "local" JSON files.
Scrum meetings are held daily from 4PM-4:15PM PST.
By the last week of the quarter, I will produce a user-friendly website that has a landing page with a search bar, and a detail page with a nav bar/tabs and interactive data visualizations. This dashboard/web application will serve as a tool for local reporters to understand their area’s economic health. I hope to gain some skills in data gathering/wrangling, but I hope to mostly focus on creating interactive data visualization and designing/developing a UX-friendly website (even if it’s simple).
By the last week of the quarter, I will support development of a user-friendly website and produce at least two static charts and two interactive data visualizations within this website by sourcing and analyzing relevant local-economic data. The backend analysis, data-sourcing and data visualizations will help feed into my team's interactive website/dashboard, which is meant to support local journalists in understanding their area's economic health. In achieving this goal, I hope to learn and develop basic front-end and back-end data-storytelling skills, which will ultimately help me better communicate data to a wider audience.
Key skills I hope to develop include:
Below is an overview of the project structure. It is subject to change as the project develops, but will be updated regularly:
├── Pipfile
├── Pipfile.lock
├── .Rhistory
├── bna-econ-n-metrics.Rproj
├── README.md
├── data
| ├── processed (Raw data that has been transformed)
| └── raw (Copy of original source data when neccessary)
├── lib (Re-usable Python or R code in .py or .R files)
| ├── __init__.py
| ├── load_r_libraries.py
| └── utils.py
├── notebooks (Jupyter notebooks or Rmarkdown files if neccessary to share)
├── scripts
| ├── analysis (Analyze data for templating)
| ├── data_wrangling (Source and clean data for analysis)
| └── templates (HTML template/script to be used in Whisker rendering)
├── county-pages (HTML files for each county)
├── county-data (data files for each county)
| └── JSON
├── static
| ├── CSS
| └── JS
└── tasks (Invoke task definitions)
├── __init__.py
└── code.py