The goal of dfeR is to help standardise R programming across the Department for Education (DfE), and facilitate sharing of business specific functions, making our code easier to read and write.
Credit to lauraselby for the logo featuring Frederick!
This package is open to all of DfE and anything we think could be useful to other programmers and analysts can be contributed.
Functionality for dfeR is expected to focus around the following:
- DfE specific formatting and helper functions
- Working with DfE databases
- Templates for analytical projects
- API wrappers commonly needed in DfE analysis (where they don’t have their own separate package)
- Geography lookup files and helper functions
Documentation for what has been included in the package so far is on our pkgdown site.
We also maintain the dfeshiny package, and expect any functions specific to R Shiny applications will live there.
For connecting to data in the explore education statistics, we are building the eesyapi package.
There is a giasr package, which has been developed for connecting to data in the get information about schools service.
While we have some DfE specific data in the dfeR package taken from the Open Geography Portal. If you’re looking at getting new data from the portal it is also worth looking at the boundr package, as this gives more functions for directly extracting data from there.
dfeR is not currently available on CRAN. For the time being you can install the development version from GitHub.
If you are using renv in your project (recommended):
renv::install("dfe-analytical-services/dfeR")Otherwise:
# install.packages("devtools")
devtools::install_github("dfe-analytical-services/dfeR")The need for setting proxy settings in order to be able to work with R and Git within the DfE estate has now ended. If you previously run the proxy script in previous versions of the dfeR package, then contact the Statistics Development Team to assist in cleaning out your system settings.
Ideas for dfeR should first be raised as a GitHub issue after which anyone is free to write the code and create a pull request for review.
For more details on contributing to dfeR, see our contributing guidelines.
Please note that the dfeR project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
Here are some example functions from within the package:
library(dfeR)
# Prettify large numbers
pretty_num(111111111, gbp = TRUE)
#> [1] "£111.11 million"
pretty_num(-11^8, dp = -1)
#> [1] "-210 million"
# Convert bytes to readable size
pretty_filesize(77777777)
#> [1] "77.78 MB"
# Calculate elapsed time and present prettily
start <- Sys.time()
end <- Sys.time() + 789890
pretty_time_taken(start, end)
#> [1] "219 hours 24 minutes 50 seconds"
# Round 5's up instead of bankers round used by round() in base R
round_five_up(2.5)
#> [1] 3
round(2.5) # base R
#> [1] 2
# Custom formatting for academic and financial years
format_ay(202425)
#> [1] "2024/25"
format_fy(202425)
#> [1] "2024-25"
format_ay_reverse("2024/25")
#> [1] "202425"
format_fy_reverse("2024-25")
#> [1] "202425"
# Get Ward to PCon to LAD to LA to Rgn to Ctry lookup file
my_data <- dfeR::wd_pcon_lad_la_rgn_ctry
head(my_data) # show first 5 rows in console
#> first_available_year_included most_recent_year_included
#> 1 2017 2017
#> 2 2017 2017
#> 3 2017 2020
#> 4 2017 2017
#> 5 2017 2020
#> 6 2017 2017
#> ward_name pcon_name lad_name la_name
#> 1 Bastwell Blackburn Blackburn with Darwen Blackburn with Darwen
#> 2 Ormesby Redcar Redcar and Cleveland Redcar and Cleveland
#> 3 Burn Valley Hartlepool Hartlepool Hartlepool
#> 4 Beardwood with Lammack Blackburn Blackburn with Darwen Blackburn with Darwen
#> 5 De Bruce Hartlepool Hartlepool Hartlepool
#> 6 St Germain's Redcar Redcar and Cleveland Redcar and Cleveland
#> region_name country_name ward_code pcon_code lad_code new_la_code
#> 1 North West England E05001621 E14000570 E06000008 E06000008
#> 2 North East England E05001518 E14000891 E06000003 E06000003
#> 3 North East England E05008942 E14000733 E06000001 E06000001
#> 4 North West England E05001622 E14000570 E06000008 E06000008
#> 5 North East England E05008943 E14000733 E06000001 E06000001
#> 6 North East England E05001519 E14000891 E06000003 E06000003
#> region_code country_code
#> 1 E12000002 E92000001
#> 2 E12000001 E92000001
#> 3 E12000001 E92000001
#> 4 E12000002 E92000001
#> 5 E12000001 E92000001
#> 6 E12000001 E92000001
# Get all countries
dfeR::countries
#> country_code country_name
#> 1 E92000001 England
#> 2 K02000001 United Kingdom
#> 3 K03000001 Great Britain
#> 4 K04000001 England and Wales
#> 5 N92000002 Northern Ireland
#> 6 S92000003 Scotland
#> 7 W92000004 Wales
#> 8 z England, Wales and Northern Ireland
#> 9 z Outside of England and unknown
#> 10 z Outside of the United Kingdom and unknown
# Get all PCon names and codes for 2024
fetch_pcons(2024) |>
head() # show first 5 rows only
#> pcon_code pcon_name
#> 1 S14000045 Midlothian
#> 2 S14000027 Na h-Eileanan an Iar
#> 3 S14000021 East Renfrewshire
#> 4 S14000048 North Ayrshire and Arran
#> 5 S14000051 Orkney and Shetland
#> 6 E14001440 Redcar
# Get All LADs in Scotland in 2017
fetch_lads(2017, "Scotland") |>
head() # show first 5 rows only
#> lad_code lad_name
#> 1 S12000019 Midlothian
#> 2 S12000015 Fife
#> 3 S12000014 Falkirk
#> 4 S12000013 Na h-Eileanan Siar
#> 5 S12000018 Inverclyde
#> 6 S12000011 East Renfrewshire
# Get all LAs in Scotland and Northern Ireland in 2022
fetch_las(2022, c("Scotland", "Northern Ireland")) |>
head() # show first 5 rows only
#> new_la_code la_name
#> 1 N09000003 Belfast
#> 2 N09000004 Causeway Coast and Glens
#> 3 N09000002 Armagh City, Banbridge and Craigavon
#> 4 N09000005 Derry City and Strabane
#> 5 N09000001 Antrim and Newtownabbey
#> 6 N09000006 Fermanagh and Omagh
# Get all Welsh wards for 2021
fetch_wards(2021, "Wales") |>
head() # show first 5 rows only
#> ward_code ward_name
#> 1 W05000981 Aethwy
#> 2 W05000982 Bro Aberffraw
#> 3 W05000983 Bro Rhosyr
#> 4 W05000107 Tregarth & Mynydd Llandygai
#> 5 W05000984 Caergybi
#> 6 W05000985 Canolbarth Môn
# The following have no specific years available and return all values
fetch_regions()
#> region_code region_name
#> 1 E12000001 North East
#> 2 E12000002 North West
#> 3 E12000003 Yorkshire and The Humber
#> 4 E12000004 East Midlands
#> 5 E12000005 West Midlands
#> 6 E12000006 East of England
#> 7 E12000007 London
#> 8 E12000008 South East
#> 9 E12000009 South West
#> 10 E13000001 Inner London
#> 11 E13000002 Outer London
#> 12 z Outside of England and unknown
#> 13 z Outside of the United Kingdom and unknown
#> 14 z Outside of England
#> 15 z Outside of United Kingdom
#> 16 z Unknown
fetch_countries()
#> country_code country_name
#> 1 E92000001 England
#> 2 K02000001 United Kingdom
#> 3 K03000001 Great Britain
#> 4 K04000001 England and Wales
#> 5 N92000002 Northern Ireland
#> 6 S92000003 Scotland
#> 7 W92000004 Wales
#> 8 z England, Wales and Northern Ireland
#> 9 z Outside of England and unknown
#> 10 z Outside of the United Kingdom and unknownFor more details on all the functions available in this package, and examples of how to use them, please see our dfeR package reference documentation.