The goal of ubigeosperu is to have an easy way to get the peruvian ubigeos into R. The data has been collected from CONCYTEC’s GitHub repository.
You can install the released version of ubigeosperu from CRAN with:
## This will work when the package is published into CRAN
install.packages("ubigeosperu")And the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("calderonsamuel/ubigeosperu")This is a basic example which shows you how to solve a common problem:
library(ubigeosperu)
library(dplyr)ubigeosperu contains a single dataframe object containing the peruvian ubigeos codes.
dim(ubigeos)
#> [1] 1876 18The ubigeos dataset is a tibble.
ubigeos
#> # A tibble: 1,876 x 18
#> cod_dep_inei desc_dep_inei cod_prov_inei desc_prov_inei cod_ubigeo_inei
#> <chr> <chr> <chr> <chr> <chr>
#> 1 01 AMAZONAS 0101 CHACHAPOYAS 010101
#> 2 01 AMAZONAS 0101 CHACHAPOYAS 010102
#> 3 01 AMAZONAS 0101 CHACHAPOYAS 010103
#> 4 01 AMAZONAS 0101 CHACHAPOYAS 010104
#> 5 01 AMAZONAS 0101 CHACHAPOYAS 010105
#> 6 01 AMAZONAS 0101 CHACHAPOYAS 010106
#> 7 01 AMAZONAS 0101 CHACHAPOYAS 010107
#> 8 01 AMAZONAS 0101 CHACHAPOYAS 010108
#> 9 01 AMAZONAS 0101 CHACHAPOYAS 010109
#> 10 01 AMAZONAS 0101 CHACHAPOYAS 010110
#> # … with 1,866 more rows, and 13 more variables: desc_ubigeo_inei <chr>,
#> # cod_dep_reniec <chr>, desc_dep_reniec <chr>, cod_prov_reniec <chr>,
#> # desc_prov_reniec <chr>, cod_ubigeo_reniec <chr>, desc_ubigeo_reniec <chr>,
#> # cod_dep_sunat <chr>, desc_dep_sunat <chr>, cod_prov_sunat <chr>,
#> # desc_prov_sunat <chr>, cod_ubigeo_sunat <chr>, desc_ubigeo_sunat <chr>You can access the tidy version and pipe it!
ubigeos_tidy %>%
filter(lugar == "CHORRILLOS", nivel == "Distrito")
#> # A tibble: 3 x 4
#> lugar nivel entidad ubigeo
#> <chr> <chr> <chr> <chr>
#> 1 CHORRILLOS Distrito INEI 150108
#> 2 CHORRILLOS Distrito RENIEC 140108
#> 3 CHORRILLOS Distrito SUNAT 150108
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