Data from 2016–Present

These files will be of most interest to users exploring audits of Federal grants made in the past several years. This is the same as the data currently available in our search.

We've split the data in three different ways for different use cases.

Full data files

The full data files are complete exports of data from the FAC. These files are too large to load into Excel and will require programs like Python notebooks, SAS, SPSS, and other code-oriented tools to manage.

Data by audit year

These files are the same data divided by the submission audit year. For example, the file general-ay-2016.csv contains all the general information from audit submissions for the audit year 2016.

If you are using Excel or similar tools to explore this data, we recommend the files split by year.

Data by federal fiscal year

These files are split based on the federal fiscal year in which the auditee submitted their audit.

This means that the file named general-ffy-2106.csv is the record of audits collected from October 1st, 2015, through September 30, 2016.

How to work with this data

We describe both the data itself, and how to get you started exploring and doing work with this data.

Data dictionary

This data is provided as CSV (comma-separated value) files. CSV files are, in many ways, like spreadsheets; you can use Excel, Google Docs, or an open source alternative (like LibreOffice) to open these files.

Each file has a header row, and then the rest of the file is data.

• Data dictionary for current data

Using the data in a spreadsheet

The files are organized according to the data tables exported by the FAC. Our data export files have the same “shape” as our API. Our data dictionary describes the columns, data types, and values contained within each of these files.

This means that the file general-ay-2016.csv is data from audit year 2016, it contains the same data that could be found via the API for the general table, and it therefore contains all of the columns described online and in our dictionary.

By the same logic, the file federal_awards-fy-2018.csv contains data from the federal fiscal year 2018 (Oct 1, 2017 through Sept 30, 2018). The columns in the file are the same as the fields presented in the federal_awards table in the API.

For example, you could:

1. download the file general-ay-2016.csv,
2. open the file in a spreadsheet, and
3. sum the column total_amount_expended.

This will tell you what the total (audited) federal expenditures were in 2016.

Using the data files in code

The CSV files should import cleanly using tooling like SAS, SPSS, or any number of other programming languages (PowerBI, Python, etc.).

If you work with code, you might write something like the following to get the same total expenditures as above.

import pandas as pd
file_path = "general-ay-2016.csv"
chunk_size = 10_000
total_expenditures = 0
for chunk in pd.read_csv(file_path, chunksize=chunk_size):
    total_expend_series = chunk.loc[:, "total_amount_expended"]
    total_expend_numeric = pd.to_numeric(total_expend_series, errors="coerce")
    total_expenditures += total_expend_numeric.sum()
print(f"There were ${total_expenditures} audited")