Package: edfinr 0.2.0

Alex Spurrier

edfinr: Access Tidy Education Finance Data

Provides easy access to tidy education finance data using Bellwether's methodology to combine NCES F-33 Survey, Census Bureau Small Area Income Poverty Estimates (SAIPE), community data from the ACS 5-Year Estimates, the Comparable Wage Index for Teachers (CWIFT) from NCES EDGE, and school district land area from U.S. Census Bureau Gazetteer Files. The package simplifies downloading, caching, and filtering education finance data by year and state, enabling researchers and analysts to explore K-12 education funding patterns, revenue sources, expenditure categories, and demographic factors across U.S. school districts.

Authors:Alex Spurrier [aut, cre], Krista Kaput [aut], Michael Chrzan [ctb], Bellwether [cph]

edfinr_0.2.0.tar.gz
edfinr_0.2.0.zip(r-4.7-any)edfinr_0.2.0.zip(r-4.6-any)edfinr_0.2.0.zip(r-4.5-any)
edfinr_0.2.0.tgz(r-4.6-any)edfinr_0.2.0.tgz(r-4.5-any)
edfinr_0.2.0.tar.gz(r-4.7-any)edfinr_0.2.0.tar.gz(r-4.6-any)
edfinr_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
edfinr/json (API)

# Install 'edfinr' in R:
install.packages('edfinr', repos = c('https://bellwetherorg.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bellwetherorg/edfinr/issues

Pkgdown/docs site:https://bellwetherorg.github.io

On CRAN:

Conda:

5.13 score 5 stars 18 scripts 296 downloads 3 exports 16 dependencies

Last updated from:7c7b8340ef. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK119
source / vignettesOK195
linux-releaseOK145
macos-releaseOK185
macos-oldrelOK213
windows-develOK92
windows-releaseOK86
windows-oldrelOK82
wasm-releaseOK96

Exports:get_finance_dataget_stateslist_variables

Dependencies:clidplyrgenericsgluelifecyclemagrittrnanoparquetpillarpkgconfigR6rlangtibbletidyselectutf8vctrswithr

Basic usage of edfinr
Introduction | Core function: get_finance_data() | Basic usage | Dataset types: skinny vs. full | Finding variables | Multiple years and states | Downloads and caching | Working with the data | Do high local revenue share districts end up with more total revenue? | How do revenue sources differ by urbanicity? | See also
Rendered fromedfinr.Rmdusingknitr::rmarkdown

Last update: 2026-08-21
Started: 2026-08-17

Data Sources and Methodology
Overview | Data Sources | Data Processing Methods | Data Processing Detail | NCES F-33 Survey Data | CCD Directory Data | SAIPE Poverty Estimates | ACS 5-Year Estimates | CPI | CWIFT (Comparable Wage Index for Teachers) | Census Gazetteer Files (District Land Area) | Joining Data | Revenue Adjustments | Exclusions | Data Notes and Cautions
Rendered fromdata-sources-methods.Rmdusingknitr::rmarkdown

Last update: 2026-08-19
Started: 2025-07-19

CPI Adjustments
Introduction | Understanding nominal vs. real dollars | How CPI adjustment works | Using the cpi_adj parameter | What gets adjusted | Working with the CPI index | Practical example: tracking real spending over time | Choosing a base year | Best practices | Technical notes | See also
Rendered fromcpi-adjustments.Rmdusingknitr::rmarkdown

Last update: 2026-08-17
Started: 2025-07-19