Skip to content
Data and code supporting a BuzzFeed News article examining the number of donors per day among Democratic presidential candidates in the second quarter of the 2020 election cycle
Jupyter Notebook
Branch: master
Clone or download
Latest commit 5fe3b9b Aug 5, 2019
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
data initial commit Jul 17, 2019
notebooks initial commit Jul 17, 2019
output initial commit Jul 17, 2019
.gitignore initial commit Jul 17, 2019
Pipfile initial commit Jul 17, 2019
Pipfile.lock initial commit Jul 17, 2019
README.md Fix link Aug 5, 2019

README.md

Analysis of daily contributions to 2020 presidential candidates, as of 2019 Q2

This repository contains data and code supporting a BuzzFeed News article examining donor frequency. Published July 17, 2019. See below for details.

Data

All data in this repository comes from the campaigns' committee filings to the Federal Election Commission (FEC), with assistance from ProPublica's Campaign Finance API.

  • data/candidates.csv contains a list of high- and medium-profile Democratic presidential candidates (and primary campaign committees) for whom an "July Quarterly" filing was available on the FEC's website by 6:30am Eastern on July 16, 2019. (The filing deadline was July 15 at midnight.)

  • data/filings.csv contains a list of basic metadata for the aforementioned filings.

  • The data/filings/ directory contains the raw filing data for each of those filings, in the FEC's .fec format.

Methodology

Linking donors

The Federal Election Commission filings do not contain any truly-unique identifiers for campaign contributors. So, in order identify donors who have given to multiple campaigns, BuzzFeed News constructed a donor_id, created from the following fields:

  • First name
  • Last name
  • 5-digit ZIP code

There are some limitations to this approach:

  • If a donor changes their name, or misspells it occasionally, this approach will not cluster all of their contributions together
  • If a donor moves to a new ZIP code, this approach will not cluster all of their contributions together
  • If two or more donors in the same ZIP code share both a first and last name, this approach will assume (incorrectly) that they are the same person

For these reasons, the results of the analysis should be interpreted as approximations.

The $200 threshold

The Federal Election Commission does not require campaigns to itemize contributions from donors who have given $200 or less during a given campaign cycle. Some campaign committees have included such donors. Some democratic campaign committees seem to have done this because because they received overly large donations and then refunded a portion. For the sake of equal comparison, BuzzFeed News excluded contributions from donors whose aggregate was listed as $200 or less.

Contribution totals above legal limit

The FEC prohibits individual donors from giving more than $2,800 to any single committee. Even so, the data in the filings appear to indicate that some donors have given more than that amount. In some cases, this may be because the refunds have not yet been processed, or are declared elsewhere. Above-legal contributions have no effect on the analyses, which focus on the act of giving rather than how much money the campaigns have raised.

Analysis

The notebooks/daily_donors.ipynb notebook contains the main analysis, written in Python. Relevant outputs can be found there, as well as in the output/ directory.

Outputs

The output/ directory contains two files that may be of interest to other journalists and researchers:

output/donors_per_day.csv is a spreadsheet containing the number of distinct donors per day, per candidate.

output/donors_per_day.png is a chart of small ultiples showing the number of distinct donors per day, per candidate.

Reproducibility

The code running the analysis is written in Python 3, and requires the following Python libraries:

If you use Pipenv, you can install all required libraries with pipenv install.

Executing the notebook in the notebooks/ directory should reproduce the findings.

Licensing

All code in this repository is available under the MIT License. Files in the data/ directory are released into the public domain. Files in the output/ directory are available under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Questions / Feedback

Contact Scott Pham at scott.pham@buzzfeed.com.

Looking for more from BuzzFeed News? Click here for a list of our open-sourced projects, data, and code.

You can’t perform that action at this time.