R Code for googleVis Demo

January 12, 2011
By

(This article was first published on Econometric Sense, and kindly contributed to R-bloggers)

# ------------------------------------------------------------------
# | PROGRAM NAME: googleVis_R
# | DATE: 1/12/11
# | CREATED BY: Matt Bogard
# | PROJECT FILE:
# |----------------------------------------------------------------
# | PURPOSE: Tutorial for creating Motion Charts in R with the GoogleVis package
# |
# |
# |
# |------------------------------------------------------------------
# | COMMENTS: See the following references for more details
# |
# | 1: http://blog.revolutionanalytics.com/2011/01/create-motion-charts-in-r-with-the-googlevis-package.html
# | 2: http://stackoverflow.com/questions/4646779/embedding-googlevis-charts-into-a-web-site/4649753#4649753
# | 3: http://cran.r-project.org/web/packages/googleVis/googleVis.pdf
# | 4: for more info on accessing the google API and data format requirements:
# | http://code.google.com/apis/visualization/documentation/gallery/motionchart.html#Data_Format
# |
# |
# |------------------------------------------------------------------
# | DATA USED: via google & iris data set
# |
# |
# |------------------------------------------------------------------
# | CONTENTS:
# |
# | PART 1: motion chart using googleVis data
# | PART 2: motion chart using your own data- this case
# | the well know iris data set (a default R data set)
# | PART 3:
# | PART 4:
# | PART 5:
# |
# |-----------------------------------------------------------------
# | UPDATES:
# |
# |
# ------------------------------------------------------------------


# *------------------------------------------------------------------*
# | set R working directory- this is where your data file will go
# | with the script for creating the visualization
# *------------------------------------------------------------------*


setwd("C:\\your directory\\R Data")


# *------------------------------------------------------------------*
# | install the googleVis package (as with any package, this only has
# | to be done forthe initial first use
# *------------------------------------------------------------------*

install.packages('googleVis')


# *------------------------------------------------------------------*
# | call the googleVis library
# *------------------------------------------------------------------*


library(googleVis)

# *-----------------------------------------------------------------*
# |
# |
# |
# | PART 1: motion chart using googleVis data
# |
# |
# |
# *------------------------------------------------------------------*


# *------------------------------------------------------------------*
# | create googelVis data object
# *------------------------------------------------------------------*


M <- gvisMotionChart(Fruits, "Fruit", "Year")


# *------------------------------------------------------------------*
# | look at data object- this includes the script that
# | will be used if you want to publish on your web page/blog
# *------------------------------------------------------------------*


print(M)

# *------------------------------------------------------------------*
# | plot the visualization-this command will open your default browser
# | and produce the visualization - this may not work depending on your
# | security and browser settings
# *------------------------------------------------------------------*

plot(M)


# *------------------------------------------------------------------*
# | create the data object that contains everything necessary to create the
# | chart on your web site/blog
# *------------------------------------------------------------------*


M$html$chart

# *------------------------------------------------------------------*
# | save the data object, which is an html file in your R
# | data directory
# *------------------------------------------------------------------*

cat(M$html$chart, file="tmp.html")

# from this point you can open the file in say, notepad++ and copy the
# script into your blog or web page and the motion chare will be functional



# *-----------------------------------------------------------------*
# |
# |
# |
# | PART 2: motion chart using your own data- this case
# | the well know iris data set (a default R data set)
# |
# |
# |
# *------------------------------------------------------------------*




# *------------------------------------------------------------------*
# | take a look at the data
# *------------------------------------------------------------------*

names(iris)
print(iris)


# simulate a time variable and add it to the data set

iris$time <- rep(1:50, 3)
names(iris)

# *------------------------------------------------------------------*
# | create googelVis data object
# *------------------------------------------------------------------*

r <- gvisMotionChart(iris, "Species", "time")

# *------------------------------------------------------------------*
# | look at data object- this includes the script that
# | will be used if you want to publish on your web page/blog
# *------------------------------------------------------------------*

names(r)
print(r)

# *------------------------------------------------------------------*
# | plot the visualization-this command will open your default browser
# | and produce the visualization - this may not work depending on your
# | security and browser settings
# *------------------------------------------------------------------*

plot(r)

# *------------------------------------------------------------------*
# | create the data object that contains everything necessary to create the
# | chart on your web site/blog
# *------------------------------------------------------------------*


r$html$chart

# *------------------------------------------------------------------*
# | save the data object, which is an html file in your R
# | data directory
# *------------------------------------------------------------------*

cat(r$html$chart, file="tmp2.html")

To leave a comment for the author, please follow the link and comment on his blog: Econometric Sense.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Tags: ,

Comments are closed.