The rdatamarket package is an R client for the DataMarket.com
API, fetching the contents and metadata
of datasets on DataMarket.com into R.
To install the package:
> install.packages("rdatamarket")
(If you are on Linux and get error messages involving RCurl, you may need
to install a package called libcurl4-openssl-dev or similar, to get RCurl
working.)
... and then load the package:
> library(rdatamarket)
Just find the data you want on datamarket.com, then copy the URL from your
browser (or a short URL to it) into dmlist or dmseries:
> plot(dmseries("http://datamarket.com/data/set/17tm/#ds=17tm!kqc=17.v.i"))
> plot(dmseries("http://data.is/nyFeP9"))
> l <- dmlist("http://data.is/nyFeP9"))
If you need to go through an HTTP proxy, set it up this way:
> dmCurlOptions(proxy="http://outproxy.mycompany.com")
Get a dataset object (find the ID in a datamarket URL, or just paste in the whole URL if you like):
> oil <- dminfo("17tm")
> oil <- dminfo("http://datamarket.com/data/set/17tm/#ds=17tm!kqc=17.v.i"))
> print(oil)
Title: "Oil: Production tonnes"
Provider: "BP"
Dimensions:
"Country" (60 values):
"Algeria"
"Angola"
"Argentina"
"Australia"
"Azerbaijan"
[...]
See all the values of the Country dimension:
> oil$dimensions[[1]]$values
a "Algeria"
17 "Angola"
d "Argentina"
z "Australia"
1l "Azerbaijan"
1b "Brazil"
v "Brunei"
1h "Cameroon"
13 "Canada"
1o "Chad"
[...]
Here's a dataset with two dimensions (besides time):
> p<-dminfo("http://datamarket.com/data/set/12r9/male-population-thousands")
> print(p)
Title: "Male population (thousands)"
Provider: "United Nations" (citing "United Nations Population Division")
Dimensions:
"Country or Area" (229 values):
"Afghanistan"
"Africa"
"Albania"
"Algeria"
"Angola"
[...]
"Variant" (5 values):
"Constant-fertility scenario"
"Estimate variant"
"High variant"
"Low variant"
"Medium variant"
From that last dataset, fetch the UN's population prediction for Sweden and Somalia in the constant-fertility scenario (note the “(thousands)” in the dataset title):
> dmseries(p, 'Country or Area'=c("Somalia", "Sweden"),
Variant="Constant-fertility scenario")
Somalia Sweden
2010-07-01 4642.070 4613.551
2015-07-01 5357.233 4725.918
2020-07-01 6211.305 4840.434
2025-07-01 7243.572 4942.865
2030-07-01 8490.929 5021.646
2035-07-01 9990.910 5083.680
2040-07-01 11793.524 5144.685
2045-07-01 13966.319 5211.212
2050-07-01 16597.110 5281.437
> dmlist(p, 'Country or Area'=c("Somalia", "Sweden"),
Variant="Constant-fertility scenario")
Country.or.Area Variant Year Value
1 Somalia Constant-fertility scenario 2010 4642.070
2 Somalia Constant-fertility scenario 2015 5357.233
3 Somalia Constant-fertility scenario 2020 6211.305
4 Somalia Constant-fertility scenario 2025 7243.572
5 Somalia Constant-fertility scenario 2030 8490.929
6 Somalia Constant-fertility scenario 2035 9990.910
7 Somalia Constant-fertility scenario 2040 11793.524
8 Somalia Constant-fertility scenario 2045 13966.319
9 Somalia Constant-fertility scenario 2050 16597.110
10 Sweden Constant-fertility scenario 2010 4613.551
11 Sweden Constant-fertility scenario 2015 4725.918
12 Sweden Constant-fertility scenario 2020 4840.434
13 Sweden Constant-fertility scenario 2025 4942.865
14 Sweden Constant-fertility scenario 2030 5021.646
15 Sweden Constant-fertility scenario 2035 5083.680
16 Sweden Constant-fertility scenario 2040 5144.685
17 Sweden Constant-fertility scenario 2045 5211.212
18 Sweden Constant-fertility scenario 2050 5281.437
The above demonstrates dimension filtering; dimensions and their values can
be specified by their $id or their $title, to fetch the data filtered to
specific values of a dimension. If no filtering is specified, all of the
dataset is fetched (careful: some datasets are enormous, and the DataMarket.com
API may truncate extremely large responses).