pottR is a personal utility package that brings together functions I regularly use in my work—primarily for data summarisation, presentation, and formatting.
The aim of this package is twofold:
- To simplify repetitive workflows in my day-to-day R projects.
- To build confidence and familiarity with R package development best practices.
You can install the development version of pottR directly from GitHub:
# Install devtools if not already installed
# install.packages("devtools")
devtools::install_github("jasonpott/pottR")
usethis::use_logo("pottr_hex.png")Below is an example showing several utility functions in action, applied
to the built-in mtcars dataset.
library(pottR)
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
library(gt)
mtcars |>
group_by(cyl) |>
summarise(
mileage = pottR::mean_sd(mpg),
med_disp = pottR::med_iqr(disp),
pro_with_more_than_3_gears = pottR::prop_n_greater(
variable = gear,
value_of_interest = 3,
rounding_value = 1
),
pro_with_3_gears = pottR::prop_n(
variable = gear,
value_of_interest = 3,
rounding_value = 1
)
)
#> # A tibble: 3 × 5
#> cyl mileage med_disp pro_with_more_than_3…¹ pro_with_3_gears
#> <dbl> <chr> <chr> <chr> <chr>
#> 1 4 26.6636363636364 ( 4.… 108 [ … 100% (n =11) 9.1% (n = 1)
#> 2 6 19.7428571428571 ( 1.… 167.6 … 100% (n =7) 28.6% (n = 2)
#> 3 8 15.1 ( 2.560048076471… 350.5 … 100% (n =14) 85.7% (n = 12)
#> # ℹ abbreviated name: ¹pro_with_more_than_3_gearsMIT © Jason Pott