Gaug.es is a paid service for website analytics. It doesn't do as much as Google Analytics, but its super simple and clean, and has a great iPhone app, and an Android app. Each website you want to track is tracked under its own gauge.
Most functions have the same format in which you pass in the id for a gauge (i.e, a website you are tracking), and your API key (see authentication below). Some functions give back data on your site overall and in that case you don't pass in a date, but others can be quieried per date or a range of dates, in which case you can pass in dates. There is one plotting function (vis_gauge
) that gives a nice default plot. But of course you can easily make your own plots.
See the Gaug.es API documentation here http://get.gaug.es/documentation/
rgauges
is listed as one of the Gaug.es API libraries here, along with libraries for Ruby and Node.js
Get your own API key in your Gaug.es 'My Account' page and put in your .Rprofile file under the name 'GaugesKey' or some other name (you can specify keyname
in function calls - but if you put in as 'GaugesKey' you're all set and don't need to bother with the keyname
parameter).
You can alternatively pass in your key using the key
parameter in each function.
Note that in the below examples I'm using my key from my .Rprofile file, so you don't see it being passed in the function call.
More stable version from CRAN
install.packages("rgauges")
Development version from Github
install.packages("devtools")
library(devtools)
install_github("rgauges", "ropensci")
library(rgauges)
Information on yourself.
gs_me()
## $user
## $user$id
## [1] "4eddbafb613f5d5139000001"
##
## $user$email
## [1] "myrmecocystus@gmail.com"
##
## $user$name
## [1] "Scott Chamberlain"
##
## $user$first_name
## [1] "Scott"
##
## $user$last_name
## [1] "Chamberlain"
##
## $user$urls
## $user$urls$self
## [1] "https://secure.gaug.es/me"
##
## $user$urls$gauges
## [1] "https://secure.gaug.es/gauges"
##
## $user$urls$clients
## [1] "https://secure.gaug.es/clients"
Traffic on a gauges ID
gs_traffic(id = "4efd83a6f5a1f5158a000004")
## $metadata
## $metadata$date
## [1] "2014-03-14"
##
## $metadata$views
## [1] 381
##
## $metadata$people
## [1] 207
##
## $metadata$urls
## $metadata$urls$older
## [1] "https://secure.gaug.es/gauges/4efd83a6f5a1f5158a000004/traffic?date=2014-02-01"
##
## $metadata$urls$newer
## NULL
##
##
##
## $data
## date views people
## 1 2014-03-01 43 18
## 2 2014-03-02 28 16
## 3 2014-03-03 20 12
## 4 2014-03-04 38 15
## 5 2014-03-05 29 17
## 6 2014-03-06 18 14
## 7 2014-03-07 15 12
## 8 2014-03-08 23 15
## 9 2014-03-09 16 9
## 10 2014-03-10 68 51
## 11 2014-03-11 26 15
## 12 2014-03-12 43 26
## 13 2014-03-13 11 9
## 14 2014-03-14 3 3
Information on screen/browser resolutions
gs_reso(id = "4efd83a6f5a1f5158a000004")
## $browser_height
## title views
## 1 600 166
## 2 768 78
## 3 480 57
## 4 900 57
## 5 1024 22
##
## $browser_width
## title views
## 1 1280 134
## 2 1024 93
## 3 1600 55
## 4 1440 38
## 5 800 28
## 6 320 18
## 7 480 9
## 8 2000 5
##
## $screen_width
## title views
## 1 1280 132
## 2 1600 95
## 3 1440 84
## 4 1024 38
## 5 320 10
## 6 2000 10
## 7 800 8
## 8 480 4
You'll need to load ggplot2
library(ggplot2)
out <- gs_gauge_detail(id = "4efd83a6f5a1f5158a000004")
vis_gauge(out)
## Using time as id variables
## Using date as id variables
## Using date as id variables
## NULL
Lists the people that have access to a Gauge.
gs_shares(id = "4efd83a6f5a1f5158a000004")
## $shares
## $shares[[1]]
## $shares[[1]]$id
## [1] "4eddbafb613f5d5139000001"
##
## $shares[[1]]$email
## [1] "myrmecocystus@gmail.com"
##
## $shares[[1]]$name
## [1] "Scott Chamberlain"
##
## $shares[[1]]$first_name
## [1] "Scott"
##
## $shares[[1]]$last_name
## [1] "Chamberlain"
##
## $shares[[1]]$type
## [1] "user"
##
## $shares[[1]]$urls
## $shares[[1]]$urls$remove
## [1] "https://secure.gaug.es/gauges/4efd83a6f5a1f5158a000004/shares/4eddbafb613f5d5139000001"
Gets referrers for a gauge, paginated.
gs_ref(id = "4efd83a6f5a1f5158a000004", date = "2014-03-10")$data
## url
## 1 http://twitter.com/
## 2 http://bitly.com/
## 3 http://www.r-bloggers.com/r-ecology-workshop-2/
## 4 http://semalt.com/crawler.php?u=http://recology.info
## 5 http://r-ecology.blogspot.com/2011/09/r-tutorial-on-visualizationsgraphics.html
## views host
## 1 24 twitter.com
## 2 2 bitly.com
## 3 2 r-bloggers.com
## 4 2 semalt.com
## 5 1 r-ecology.blogspot.com
## path
## 1 /
## 2 /
## 3 /r-ecology-workshop-2/
## 4 /crawler.php?u=http://recology.info
## 5 /2011/09/r-tutorial-on-visualizationsgraphics.html
Gets browsers and platforms for a gauge.
gs_tech(id = "4efd83a6f5a1f5158a000004")
## $browsers
## browser version views
## 1 Chrome 33.0 114
## 2 Chrome 32.0 20
## 3 Chrome 31.0 3
## 4 Chrome 28.0 3
## 5 Chrome 21.0 2
## 6 Chrome 29.0 2
## 7 Chrome 0.3 1
## 8 Chrome 30.0 1
## 9 Chrome 27.0 1
## 10 Chrome 23.0 1
## 11 Chrome 22.0 1
## 12 Chrome 34.0 1
## 13 Chrome 35.0 1
## 14 Firefox 27.0 99
## 15 Firefox 24.0 15
## 16 Firefox 21.0 9
## 17 Firefox 26.0 9
## 18 Firefox 25.0 1
## 19 Firefox 22.0 1
## 20 Firefox 16.0 1
## 21 Internet Explorer 8.0 25
## 22 Internet Explorer 7.0 9
## 23 Internet Explorer 11.0 6
## 24 Internet Explorer 9.0 5
## 25 Internet Explorer 10.0 3
## 26 Safari 7.0 16
## 27 Safari 7.6 7
## 28 Safari 5.1 4
## 29 Safari 6.0 3
## 30 Safari 6.1 3
## 31 Safari 7.1 1
## 32 Other NA 10
## 33 Opera 4.2 2
## 34 Opera 20.0 1
##
## $platforms
## key title views
## 1 windows Windows 200
## 2 macintosh Macintosh 107
## 3 linux Linux 58
## 4 iphone iPhone 8
## 5 other Other 3
## 6 android Android 3
## 7 ipad iPad 2
head(gs_pageviews(id = "4efd83a6f5a1f5158a000004", fromdate = "2013-11-01",
todate = "2013-11-06"))
## title V1
## 1 Recology 84
## 2 R to GeoJSON 20
## 3 ggplot2 maps with insets 9
## 4 Displaying Your Data in Google Earth Using R2G2 8
## 5 GBIF biodiversity data from R - more functions 12
## 6 R resources 15
Gets top content for a gauge, paginated.
head(gs_content(id = "4efd83a6f5a1f5158a000004", date = "2013-11-01")$data)
## path host views
## 1 / recology.info 5
## 2 /2013/06/geojson/ recology.info 3
## 3 /2012/08/ggplot-inset-map/ recology.info 2
## 4 /2012/10/R2G2-package/ recology.info 2
## 5 /2012/10/rgbif-newfxns/ recology.info 1
## 6 /2013/07/r-resources/ recology.info 1
## title
## 1 Recology
## 2 R to GeoJSON
## 3 ggplot2 maps with insets
## 4 Displaying Your Data in Google Earth Using R2G2
## 5 GBIF biodiversity data from R - more functions
## 6 R resources
## url
## 1 http://recology.info/
## 2 http://recology.info/2013/06/geojson/
## 3 http://recology.info/2012/08/ggplot-inset-map/
## 4 http://recology.info/2012/10/R2G2-package/
## 5 http://recology.info/2012/10/rgbif-newfxns/
## 6 http://recology.info/2013/07/r-resources/
Gets search terms for a gauge, paginated.
gs_terms(id = "4efd83a6f5a1f5158a000004", date = "2014-02-05")$data
## term views
## 1 r markdown twitter bootstrap 3
## 2 geoconcept geojson 2
## 3 recology.com 2
## 4 two sex demographic 1
## 5 r govdat 1
## 6 presenting logistic regression results to administrators 1
## 7 phylometa 1
## 8 http://recology.info/2012/12/taxize/ 1
## 9 recology 1
## 10 gogle r 1
## 11 gbif r 1
## 12 plot climate data r 1
## 13 markdown for rstudio change font 1
## 14 geojson rgdal 1
## 15 species name r 1
Information on locations
head(gs_locations(id = "4efd83a6f5a1f5158a000004")$data)
## title key views region_title region_key region_views
## 1 United States US 136 CA 20 California
## 2 United States US 136 NY 16 New York
## 3 United States US 136 WA 15 Washington
## 4 United States US 136 IL 14 Illinois
## 5 United States US 136 MA 8 Massachusetts
## 6 United States US 136 PA 7 Pennsylvania
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