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Regional & Metropolitan vars #14
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You probably have to first get the regional IDs and then just do a bit of string interpolation. The example below retrieves disposable income (on PPP basis) for all Swedish regions in 2015 and 2016. Let me know if this still doesn't solve your issue. library(tidyverse)
library(OECD)
struc <- get_data_structure("REGION_ECONOM")
se_regions <- struc$REG_ID %>%
filter(str_detect(id, "SE")) %>%
pull(id) %>%
paste0(collapse = "+")
query <- sprintf("2.%s.SNA_2008.INCOME_DISP.PC_REAL_PPP.ALL.2015+2016", se_regions)
df <- get_dataset("REGION_ECONOM", query)
inner_join(df, struc$REG_ID, by = c("REG_ID" = "id")) %>%
set_names(tolower) %>%
select(reg_id, label, time, obsvalue) # A tibble: 16 x 4
reg_id label time obsvalue
<chr> <chr> <chr> <dbl>
1 SE31 North Middle Sweden 2015 19768
2 SE22 South Sweden 2015 20671
3 SE23 West Sweden 2015 21164
4 SE21 Småland with Islands 2015 20024
5 SE32 Central Norrland 2015 19947
6 SE11 Stockholm 2015 23947
7 SE12 East Middle Sweden 2015 20230
8 SE33 Upper Norrland 2015 20080
9 SE32 Central Norrland 2016 20180
10 SE11 Stockholm 2016 24606
11 SE31 North Middle Sweden 2016 20043
12 SE33 Upper Norrland 2016 20367
13 SE12 East Middle Sweden 2016 20577
14 SE21 Småland with Islands 2016 20503
15 SE22 South Sweden 2016 21021
16 SE23 West Sweden 2016 21766 |
Thank you very much. I was thinking about some link to standard SDMX codes, but I think your approach is a good hack. However,
will lead to
I was looking for something like "ALL_IDs", or "ALL.REGIONS" or similar shortcode on sdmx.org. Obviously, your approach is a great help, just may take a lot of time to loop it through all countries, or country pairs. I wanted to download a panel of regional data, but the SDMX code exporter gives URIs that are even too long for RStudio to handle, not to mention the API. |
You could also try to leave the dimension empty in the query, e.g. df <- get_dataset("PRICES_CPI", "AUS.CPALTT01..M") gives all |
I was wondering if you could include in the vignette an example of filtering regional or metropolitian variables? For this, neither strategy seems to work. The SDMX querry is several pages long and I cannot really work with it. The other filtering method for me does not seem to work. However, without effective filtering the data table exceeds the API limit.
Is there a way to access, for example, any of the regional GDP variables with the package?
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