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demo Update and simplify demo
inst/tests Fix tests failing on API nuance and data change
DESCRIPTION Bump version to 0.6.5
LICENSE Strip LICENSE down to template fulfillment
NAMESPACE Reordering and reformatting by devtools
NEWS Add `library(rdatamarket)` step in README Add and Rbuildignore


The rdatamarket package is an R client for the API, fetching the contents and metadata of datasets on 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)

Quick start

Just find the data you want on, then copy the URL from your browser (or a short URL to it) into dmlist or dmseries:

> plot(dmseries("!kqc=17.v.i"))
> plot(dmseries(""))
> l <- dmlist(""))

If you need to go through an HTTP proxy, set it up this way:

> dmCurlOptions(proxy="")

Reading metadata

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("!kqc=17.v.i"))
> print(oil)
Title: "Oil: Production tonnes"
Provider: "BP"
  "Country" (60 values):

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("")
> print(p)
Title: "Male population (thousands)"
Provider: "United Nations" (citing "United Nations Population Division")
  "Country or Area" (229 values):
  "Variant" (5 values):
    "Constant-fertility scenario"
    "Estimate variant"
    "High variant"
    "Low variant"
    "Medium variant" 

Reading data

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 API may truncate extremely large responses).

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