The R Journal: article published in 2016, volume 8:2

rnrfa: An R package to Retrieve, Filter and Visualize Data from the UK National River Flow Archive PDF download
Claudia Vitolo, Matthew Fry and Wouter Buytaert , The R Journal (2016) 8:2, pages 102-116.

Abstract The UK National River Flow Archive (NRFA) stores several types of hydrological data and metadata: daily river flow and catchment rainfall time series, gauging station and catchment informa tion. Data are served through the NRFA web services via experimental RESTful APIs. Obtaining NRFA data can be unwieldy due to complexities in handling HTTP GET requests and parsing responses in JSON and XML formats. The rnrfa package provides a set of functions to programmatically access, filter, and visualize NRFA data using simple R syntax. This paper describes the structure of the rnrfa package, including examples using the main functions gdf() and cmr() for flow and rainfall data, respectively. Visualization examples are also provided with a shiny web application and functions provided in the package. Although this package is regional specific, the general framework and structure could be applied to similar databases.

Received: 2016-01-29; online 2017-01-03
CRAN packages: rnrfa, rnoaa, waterData, RNCEP, shiny, leaflet, rmarkdown, DT, dplyr, cowplot, plyr, httr, xml2, stringr, xts, rjson, ggmap, ggplot2, rgdal, sp, ggrepel, devtools, microbenchmark, cranlogs, evd, outliers, spacetime, sos4R , CRAN Task Views implied by cited CRAN packages: WebTechnologies, Spatial, SpatioTemporal, ReproducibleResearch, Distributions, Econometrics, Environmetrics, ExtremeValue, Finance, Graphics, Phylogenetics, TimeSeries


CC BY 4.0
This article is licensed under a Creative Commons Attribution 3.0 Unported license .

@article{RJ-2016-036,
  author = {Claudia Vitolo and Matthew Fry and Wouter Buytaert},
  title = {{rnrfa: An R package to Retrieve, Filter and Visualize Data
          from the UK National River Flow Archive}},
  year = {2016},
  journal = {{The R Journal}},
  url = {https://journal.r-project.org/archive/2016/RJ-2016-036/index.html},
  pages = {102--116},
  volume = {8},
  number = {2}
}