The goal of statbank is to …
Installation
You can install the released version of statbank from CRAN with:
# install.packages("statbank")And the development version from GitHub with:
# install.packages("remotes")
remotes::install_github("akselthomsen/statbank")Example
This is a basic example which shows you how to solve a common problem:
library(statbank)
#>
#> Attaching package: 'statbank'
#> The following object is masked from 'package:stats':
#>
#> filter
## basic example code
x <- tbl_dst(table_id = "FOLK1B", lang = "en")
class(x)
#> [1] "tbl_dst" "list"
x
#> # A tibble: 6 x 6
#> OMRÅDE KØN ALDER STATSB TID INDHOLD
#> <chr> <chr> <chr> <chr> <chr> <dbl>
#> 1 000 TOT IALT 0000 2008K1 5475791
#> 2 084 TOT IALT 0000 2008K1 1645825
#> 3 101 TOT IALT 0000 2008K1 509861
#> 4 147 TOT IALT 0000 2008K1 93444
#> 5 155 TOT IALT 0000 2008K1 13261
#> 6 185 TOT IALT 0000 2008K1 40016
x %>% head()
#> # A tibble: 6 x 6
#> OMRÅDE KØN ALDER STATSB TID INDHOLD
#> <chr> <chr> <chr> <chr> <chr> <dbl>
#> 1 000 TOT IALT 0000 2008K1 5475791
#> 2 084 TOT IALT 0000 2008K1 1645825
#> 3 101 TOT IALT 0000 2008K1 509861
#> 4 147 TOT IALT 0000 2008K1 93444
#> 5 155 TOT IALT 0000 2008K1 13261
#> 6 185 TOT IALT 0000 2008K1 40016
x %>% tail()
#> # A tibble: 6 x 6
#> OMRÅDE KØN ALDER STATSB TID INDHOLD
#> <chr> <chr> <chr> <chr> <chr> <dbl>
#> 1 846 2 100OV 5999 2020K4 0
#> 2 773 2 100OV 5999 2020K4 0
#> 3 840 2 100OV 5999 2020K4 0
#> 4 787 2 100OV 5999 2020K4 0
#> 5 820 2 100OV 5999 2020K4 0
#> 6 851 2 100OV 5999 2020K4 0
x %>%
sample_n(8) %>%
show_query() %>%
print() %>%
use_bulk_download()
#> <JSON>
#> {
#> "table": "FOLK1B",
#> "lang": "en",
#> "format": "CSV",
#> "delimiter": "Semicolon",
#> "ValuePresentation": "Code",
#> "variables": [
#> {
#> "code": "OMRÅDE",
#> "values": [
#> "607"
#> ]
#> },
#> {
#> "code": "KØN",
#> "values": [
#> "2",
#> "TOT"
#> ]
#> },
#> {
#> "code": "ALDER",
#> "values": [
#> "10-14",
#> "95-99"
#> ]
#> },
#> {
#> "code": "STATSB",
#> "values": [
#> "5356",
#> "5122",
#> "5402"
#> ]
#> },
#> {
#> "code": "TID",
#> "values": [
#> "2011K3"
#> ]
#> }
#> ]
#> }
#>
#> # A tibble: 6 x 6
#> OMRÅDE KØN ALDER STATSB TID INDHOLD
#> <chr> <chr> <chr> <chr> <chr> <dbl>
#> 1 607 2 10-14 5356 2011K3 0
#> 2 607 2 10-14 5122 2011K3 0
#> 3 607 2 95-99 5356 2011K3 0
#> 4 607 2 95-99 5122 2011K3 0
#> 5 607 TOT 10-14 5356 2011K3 0
#> 6 607 TOT 10-14 5122 2011K3 0
#> # A tibble: 0 x 6
#> # ... with 6 variables: OMRÅDE <chr>, KØN <chr>, ALDER <chr>, STATSB <chr>,
#> # TID <chr>, INDHOLD <dbl>
tbl_dst(table_id = "FOLK1B", lang = "en") %>%
select(TID) %>%
filter(stringr::str_detect(TID, "K4")) %>%
collect()
#> # A tibble: 13 x 2
#> TID INDHOLD
#> <chr> <dbl>
#> 1 2008K4 5505995
#> 2 2009K4 5532531
#> 3 2010K4 5557709
#> 4 2011K4 5579204
#> 5 2012K4 5599665
#> 6 2013K4 5623501
#> 7 2014K4 5655750
#> 8 2015K4 5699220
#> 9 2016K4 5745526
#> 10 2017K4 5778570
#> 11 2018K4 5806015
#> 12 2019K4 5827463
#> 13 2020K4 5837213
x %>%
use_long_names()
#> # A tibble: 6 x 6
#> REGION SEX AGE CITIZENSHIP TIME NUMBER
#> <chr> <chr> <chr> <chr> <chr> <dbl>
#> 1 000 TOT IALT 0000 2008K1 5475791
#> 2 084 TOT IALT 0000 2008K1 1645825
#> 3 101 TOT IALT 0000 2008K1 509861
#> 4 147 TOT IALT 0000 2008K1 93444
#> 5 155 TOT IALT 0000 2008K1 13261
#> 6 185 TOT IALT 0000 2008K1 40016
