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.
To install Rcbpp, run the following code:
# install.packages("devtools")
devtools::install_github("CenterOnBudget/Rcbpp")
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
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