All posts (Page 125 of 131)
rplos is an R package to facilitate easy search and full-text retrieval from all Public Library of Science (PLOS) articles, and we have a little feature which aren’t sure if is useful or not. I don’t actually do any text-mining for my research, so perhaps text-mining folks can give some feedback.
You can quickly get a lot of results back using rplos, so perhaps it is useful to quickly browse what you got. What better tool than a browser to browse? Enter highplos and highbrow. highplos uses the Solr capabilities of the PLOS search API, and lets you get back a string with the term you searched for highlighted (by default with <em> tag for italics).
The Global Biodiversity Information Facility (GBIF) is a warehouse of species occurrence data - collecting data from a lot of different sources. Our package rgbif allows you to interact with GBIF from R. We interact with GBIF via their Application Programming Interface, or API. Our last version on CRAN (v0.3) interacted with the older version of their API - this version interacts with the new version of their API. However, we also retained functions that interact with the old API....
We are building a taxonomic toolbelt for R called taxize - which gives you programmatic access to many sources of taxonomic data on the web. We just pushed a new version to CRAN (v0.1.5) with a lot of changes (see here for a rundown). Here are a few highlights of the changes.
Note: the windows binary may not be available yet…
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Install and load taxize
install.packages("taxize")
library(taxize)
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Taxonomic identifiers
Each taxonomic service has their own unique ID for a taxon. We had a way to get ITIS and NCBI identifiers before - we now have functions for Tropicos, EOL, and the Catalogue of Life.
...We have previously written about creating interactive maps on the web from R, with the interactive maps on Github. See here, here, here, and here.
A different approach is to use CartoDB, a freemium service with sql interface to your data tables that provides a map to visualize data in those tables. They released an R interace to their sql API on Github here - which we can use to make an interactive map from R.
We’ll first get some data from GBIF, ~500 occurrences of Puma concolor in the US, then push that data to a CartoDB table. There are a couple more non-programmatic steps in this workflow than with pushing geojson file to Github as outlined in the previous linked above (i.e., going to the CartoDB site and making a visualization, and making it public).
...Previously on this blog we have discussed making geojson maps and uploading to Github for interactive visualization with USGS BISON data, and with GBIF data, and on my own personal blog. This is done using a file format called geojson, a file format based on JSON (JavaScript Object Notation) in which you can specify geographic data along with any other metadata.
In two the previous posts about geojson, I described how you could get data from the USGS BISON API using our rbison package, and from the GBIF API using the rgbif package, then make a geojson file, and send to Github. In both examples, the data were points. What about polygons? This is a relatively common use case in which an area is defined on a map instead of points - and polygons are supported in geojson. How do we do this with the R to geojson to Github workflow?
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