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Read sdmx data into dataframes from either a local SDMX-ML file or from a SDMX web-service:
<-
u "https://stats.oecd.org/restsdmx/sdmx.ashx/GetData/HH_DASH/..Q"
<- readsdmx::read_sdmx(u) d
The RapidXML C++ library is used to parse the data.
From CRAN:
install.packages("readsdmx")
From GitHub:
::install_github("mdequeljoe/readsdmx") devtools
The follow data message types are supported:
For the above example (locally):
download.file(u, path <- tempfile(fileext = ".xml"), quiet = TRUE)
::microbenchmark(
microbenchmarkreadsdmx = readsdmx::read_sdmx(path),
rsdmx = as.data.frame(rsdmx::readSDMX(path, FALSE)),
times = 5L,
unit = "s"
)
#> Unit: seconds
#> expr min lq mean median uq max neval
#> readsdmx 0.152 0.153 0.159 0.161 0.165 0.165 5
#> rsdmx 23.955 24.578 24.732 24.937 25.005 25.185 5
pandasdmx (python)
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.