Rcbpp

Overview

R utilities to streamline CBPP research, including functions for generating commonly used variables, creating paths to files in the SharePoint datasets library, and computing basic weighted statistics. Rcbpp also includes data that frequently come in handy, including state FIPS codes (along with corresponding state names and postal abbreviations) and calendar year averages of the CPI-U-RS.

Installation

To install Rcbpp, run the following code:

# install.packages("devtools")
devtools::install_github("CenterOnBudget/Rcbpp")

Example

library(Rcbpp)
library(tidyverse)

mar21 <- read_csv(
  file = sp_cps_asec(2021, f = "csv"),
  col_select = c(marsupwt, a_age, spm_resources, spm_povthreshold)
)

mar21 |>
  make_age_group_var("cps_asec") |>
  mutate(
    pop = TRUE, 
    b100 = spm_resources < spm_povthreshold
  ) |>
  group_by(age_group) |>
  summarize(
    across(c(pop, b100), \(x) wt_sum(x, wt = marsupwt)), 
    .groups = "drop"
  ) |>
  mutate(
    across(c(pop, b100), round), 
    pov_rate = b100 / pop
  )
#> # A tibble: 3 × 4
#>   age_group         pop     b100 pov_rate
#>   <fct>           <dbl>    <dbl>    <dbl>
#> 1 Under 18     72777497  7044256   0.0968
#> 2 18 to 64    197582013 17446130   0.0883
#> 3 65 and over  55835929  5290704   0.0948

with(mar21, wt_quantile(a_age, wt = marsupwt, n = 10))
#> 10% 20% 30% 40% 50% 60% 70% 80% 90% 
#>   8  16  24  31  38  46  54  62  71