boulder is designed for querying and downloading data from Estonian Health Statistics And Health Research Database (TAI). Name ‘Boulder’ is from Brand Estonia toolbox boulders.
bouldeR: In our nature, the giant erratic boulders appear unexpectedly in the forest or on the beach. In our visual communication, they play a similar disruptive role. The use of boulders is not compulsory. Brand Estonia
Package has two main functions get_all_tables()
and pull_table()
.
get_all_tables()
downloads list of available database tables andpull_table()
downloads your table of interest based on table name.Table descriptions are available in ‘Title’ column of data frame produced by get_all_tables()
. By default get_all_tables()
uses local table supplied with the package. To download fresh list of database tables from TAI use local = FALSE
argument.
pull_table()
converts “.” and “..”, apparently denoting missing values, to NA-s, and filters out some summary rows, generally coded by “0”-s, to reduce table size in attempt to avoid hitting size limit of POST request. Otherwise, variables and their names are not modified, as prepended dots “.”, “..” to the variable names indicate their hierarchy. It’s strongly advisable to compare downloaded table to the table available on the TAI website.
Package interacts with pxweb API at TAI. There is also official pxweb API package rOpenGov/pxweb allowing interactive browsing through databases.
Parse data from json file manually downloaded from Estonian Health Statistics Database into a data frame.
library(boulder)
path_to_PK10.json <- system.file("extdata", "PK10.json", package = "boulder", mustWork = TRUE)
pk10 <- json_to_df(path_to_PK10.json)
#> Data source is Estonian Cancer Registry.
Download table “RK01” from database:
# load library
library(boulder)
# check available tables
tabs <- get_all_tables(lang = "en")
tabs
#> # A tibble: 1,688 x 6
#> Database Node Name Title Updated url
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 01Rahvastik Abortions RK01 Abortio… 2017-06… http:…
#> 2 01Rahvastik Abortions RK11 Abortio… 2017-11… http:…
#> 3 01Rahvastik Abortions RK20 Abortio… 2017-06… http:…
#> 4 01Rahvastik Abortions RK30 Abortio… 2017-06… http:…
#> 5 01Rahvastik Abortions RK40 Abortio… 2017-06… http:…
#> 6 01Rahvastik Abortions RK50 Use of … 2017-06… http:…
#> 7 01Rahvastik Abortions RK61 Legally… 2017-06… http:…
#> 8 01Rahvastik Abortions RK62 Abortio… 2017-06… http:…
#> 9 01Rahvastik Abortions RK63 Abortio… 2017-06… http:…
#> 10 01Rahvastik Births and breastfed infants SR01 Live bi… 2017-10… http:…
#> # ... with 1,678 more rows
# dowload table of interest
rk01 <- pull_table("RK01", lang = "en")
rk01
#> # A tibble: 3,876 x 4
#> Year County `Age group` value
#> <chr> <chr> <chr> <dbl>
#> 1 2000 Estonia All age groups 15331
#> 2 2000 Estonia 10-14 20.0
#> 3 2000 Estonia 15-17 689
#> 4 2000 Estonia 18-19 1168
#> 5 2000 Estonia 20-24 3701
#> 6 2000 Estonia 25-29 3545
#> 7 2000 Estonia 30-34 2940
#> 8 2000 Estonia 35-39 2158
#> 9 2000 Estonia 40-44 996
#> 10 2000 Estonia 45-49 110
#> # ... with 3,866 more rows
# look at the table title and date of last update
comment(rk01)
#> Title Updated
#> "Abortions by age group and county" "2017-06-06T10:16:55"