Inform voters about the 2018 General Election San José, California and Santa Clara County local candidates' and measures' campaign finance data.
We want to highlight the following with data visualizations or a dashboard:
- Who is donating the money -- individuals? PACs?
- Are the donors from the same jurisdiction, outside of jurisdiction but in California, or live outside of California?
This information might help voters make more informed decisions.
Before you run the development server, you will want to have the following installed:
- Git clone the repository and cd the repository
cd nov_2018_code
cd react-frontend
yarn install
ornpm install
- Open a terminal and run
yarn run server:dev
ornpm run server:dev
- Open another terminal and run
yarn run build:dev
ornpm run server:dev
- Open
localhost:8080
in a browser
Before you run the scripts:
- Install Python
- Install Anaconda or Miniconda
- If you use Anaconda,
conda install -c anaconda pandas
- If you use Miniconda, view instructions here must have Python installed, and either Anaconda or Miniconda.
After you install the necessary libraries:
cd data/scripts
python
one of the files in that folder- If running the convert script, ```cd ../json-11-6-2018-General-Election-SJC-candidates/" to find the output file
- If running the combine script, ```cd ../combined-data-11-6-2018-General-Election-SJC-candidates/" to find the output file
Go to cd data/resources
Use the key for questions about the data headers. The source of this key is the Santa Clara County Public Portal for Campaign Finance Disclosure. Some of the header information in the key should apply to both SJC and SCC data for Form 460 files (the files that detail contributions, loans and expenses).
Please assign yourself one of "Find data" GitHub issues here: https://github.com/codeforsanjose/OpenDSJ-2018/issues
Communicate with us on Slack (channel: #open-disclosure). Join our Slack or Log onto our Slack
If you find a great source to get campaign finance data on candidates:
- Please message the team group chat about the source you found.
- Download the XSL/CSV files, add them to the git repository on a new branch and then create a pull request (let me know if you need help with this)
- Extract the important information from the XSL/CSV files you found by extracting the important information to another XSL/CSV