The most complete open-source database of UC Berkeley faculty salary data.

What is this?

• data: A collection of CSVs with pay data for the University of California from 2006 to 2015. For 2010 to 2015, these are sourced from public records requests with the University of California. For 2006 to 2009, these are from Microsoft Access databases stored on CDs in the UC Berkeley library.
• salary: A Django app to load UC Berkeley faculty pay data and departmental information.
• browser: A Django app to browse UC Berkeley faculty salary information.

How can I use this?

Are you a journalist or a researcher who wants to download this data?

Head to the /data directory. You can find the processed file of Berkeley professors associated with departments at processed_berkeley_professors.csv. The merged file of every UC employee (excluding those whose names were redacted) for the 2006 to 2015 data is available at merged.csv (this is a big file). The raw, unstandardized CSVs are in the /data/salary directory. If you have any questions, contact us at [email protected], and if you end up using the data, we'd love if you dropped us a line!

Are you a programmer who wants to adapt our database to fit your own needs?

First, get a Django project started.

Create a new virtualenv and clone the repository.

virtualenv ucb-faculty-salary
git clone https://github.com/dailycal-projects/ucb-faculty-salary.git

Install the requirements.

pip install -r requirements.txt

Create a Postgres database. For example, if you wanted to call it salary:

createdb salary

Set the following environment variables using EXPORT VARIABLE = 'VALUE':

• DB_NAME: name of the Postgres database
• DB_HOST: name of the database host

Migrate the database.

python manage.py migrate

The data is processed with a series of Django management commands, which you can run with python manage.py [command]. They are, in the order they should be run:

• mergerawfiles Process and join the raw CSVs in data/salary, creating a merged, cleaned CSV at data/merged.csv. This file includes information for every UC campus. It's big — about 180 MB.
• filterberkeleyfaculty: Filters for UC Berkeley faculty. Here's where you could, for example, include other campuses or administrative positions. Creates data/berkeley_faculty.csv.
• importsalaryrecords: Uses django-postgres-copy to import the clean Berkeley faculty CSV into a Postgres database.
• collapsepeople: Looks for common names in the ten years of data and creates Person objects for each unique faculty member.
• importdirectoryrecords: Imports information from the UC Berkeley directory that associates people with department codes, and associates Person objects with DirectoryRecord objects.
• processdepartments: Imports information associating department codes to canonical departments, and creates Department objects.
• overrides: Manually corrects for some errors, like professors who have left UC Berkeley or whose departments are incorrect.
• exportprocesseddata: Exports CSV of each year of salary information we have for Berkeley professors who we've associated with a department.

Alternatively, run python manage.py initialize to bootstrap the project, which will call the above commands in succession.