googleVis

Version 0.7.0 of the googleVis R package has been released, adding a new function for Gantt charts. Gantt charts are helpful to illustrates a project schedule and its dependencies. Following the Google documentation the project has to be broken down into task IDs, task names, resources, start date, end dates, task duration (in milliseconds), how far the task has been completed (in percent), and finally any dependencies to other tasks IDs.

It’s been while since the last update on googleVis. Well, the Google Chart Tools are fairly settled now, but some time ago Google added Word Trees: A word tree depicts multiple parallel sequences of words. It could be used to show which words most often follow or precede a target word (e.g., “Cats are…”) or to show a hierarchy of terms (e.g., a decision tree). Google word trees are able to process large amounts of text quickly.

We released googleVis version 0.6.1 on CRAN last week. The update fixes issues with setting certain options, following the switch from RJSONIO to jsonlite. Screen shot of some of the Google Charts New to googleVis? The package provides an interface between R and the Google Charts Tools, allowing you to create interactive web charts from R without uploading your data to Google.

We released googleVis version 0.5.8 on CRAN last week. The update is a maintenance release for the forthcoming release of R 3.2.0. Screen shot of some of the Google Charts New to googleVis? The package provides an interface between R and the Google Charts Tools, allowing you to create interactive web charts from R without uploading your data to Google.

Version 0.5.6 of googleVis was released on CRAN over the weekend. This version fixes a bug in gvisMotionChart. Its arguments xvar, yvar, sizevar and colorvar were not always picked up correctly. Thanks to Juuso Parkkinen for reporting this issue. Example: Love, or to love A few years ago Martin Hilpert posted an interesting case study for motion charts. Martin is a linguist and he researched how the usage of words in American English changed over time, e.

The Google Charts API is quite powerful and via googleVis you can access it from R. Here is an example that demonstrates how you can zoom into your chart. In the example below I set the maximum zoom level to 5% of the chart. Drag and pan with a left mouse button to zoom in; use a right mouse click to zoom out again. The functionality is available in other core charts as well, such as line, column and bar charts. For more configuration options of the explorer settings visit the Google documentation. Loading R code

Earlier this week we released googleVis 0.5.5 on CRAN. The package provides an interface between R and Google Charts, allowing you to create interactive web charts from R. This is mainly a maintenance release, updating documentation and minor issues. Screen shot of some of the Google Charts New to googleVis? Review the examples of all googleVis charts on CRAN.

Recently we released googleVis 0.5.3 on CRAN. The package provides an interface between R and Google Charts, allowing you to create interactive web charts from R. Screen shot of some of the Google Charts Although this is mainly a maintenance release, I’d like to point out two changes: Default chart width is set to ‘automatic’ instead of 500 pixels.

At the end of March Google released a new version of the Chart Tools API with new options for point shapes and line brushes. The arguments are called pointShape and lineDashStyle and can be set directly via googleVis. We published googleVis 0.5.2 on CRAN yesterday with added examples for those new options in gvisLineChart and gvisScatterChart. Note, these options can be used with most chart types as well, also in combination.

GoogleVis 0.5.1 was released on CRAN yesterday. New Features New functions gvisSankey, gvisAnnotationChart, gvisHistogram, gvisCalendar and gvisTimeline to support the new Google charts of the same names (without ‘gvis’). New demo Trendlines showing how trend-lines can be added to Scatter-, Bar-, Column-, and Line Charts. New demo Roles showing how different column roles can be used in core charts to highlight data.

After my posts on timeline, Sankey and calendar charts, this will be the last to introduce new chart types of the developer version of googleVis. Today I will give examples for the new annotation charts and histograms. Annotation charts Annotation charts have been part of the Google Chart tools for a long time and googleVis as well. However, in the past only a flash based version was available (gvisAnnotatedTimeLine in googleVis).

My little series of posts about the new googleVis charts continues with calendar charts. Google’s calendar charts are still in beta, but they provide already a nice heat map visualisation of calendar year data. The current development version of googleVis supports this new function via gvisCalendar. Here is an example displaying daily stock price data. Loading For the code below to run you will require the developer version (≥ 0.

Sankey diagrams are great for visualising flows from one set of data values to another. Although named after Irish Captain Matthew Henry Phineas Riall Sankey, who used this type of diagram in 1898 to show the energy efficiency of a steam engine, the best know Sankey diagram is probably Charles Minard’s Map of Napoleon’s Russian Campaign of 1812, which he actually produced in 1869. Thomas Rahlf: Datendesign mit R The above example from Thomas Rahlf’s book Datendesign mit R shows that Minard’s plot can be reproduced with base graphics in R.

Last year at the Google I/O conference Mitchell Foley presented new developments of the Google Chart Tools API and one of the new features he mentioned were timeline charts (about 6 min into the talk). Timeline charts are a great way of visualising different dates/events over time and are now also supported by googleVis from version 0.5.0 onwards (currently only available from GitHub). Here is an example, showing classroom allocation in the afternoon.

After nearly 4 years of developing googleVis on Google Code with SVN we decided to move to GitHub. The main reason was that Google stopped the facility of hosting pre-CRAN builds of the package for user testing. The devtools package on the other hand makes it really easy to install packages from source hosted on GitHub. Additionally, we hope that GitHub will make collaboration with others more effective. Thus, bookmark http://github.

In my previous post, I presented a preview version of googleVis that provided an integration with RStudio’s Viewer pane (introduced with version 0.98.441). Over 80% in my little survey favoured the new default output mechanism of googleVis within RStudio. Hence, I uploaded googleVis 0.4.7 on CRAN over the weekend. However, there were also some thoughtful comments, which suggested that the RStudio Viewer pane is not always the best option. Indeed, Flash charts and gvisMerge output will still be displayed in your default browser, but also if you work on larger charts and with smaller screen, then the browser might still be the better option compared to the Viewer pane - of course you can launch the browser from the Viewer pane as well.

The preview version 0.98.441 of RStudio introduced a new viewer pane to render local web content and with that it allows me to display googleVis charts within RStudio rather than in a separate browser window. I think this is a rather nice feature and hence I have updated the plot method in googleVis to use the RStudio viewer pane as the default output. If you use another editor, or if the plot is using one of the Flash based charts, then the browser is still the default display.

Changing the plotting width in bar-, column- and combo-charts of googleVis works identical and is defined by the bar.groupWidth argument. The dot in the argument means that it has to be split in R into bar=“{groupWidth:‘10%’}”. Example library(googleVis) cc <- gvisColumnChart(head(Population,10), xvar="Country", yvar="Population", options=list(seriesType="bars", legend="top", bar="{groupWidth:'10%'}", width=500, height=450), chartid="thincolumns") plot(cc) Your browser doesn’t support iframes. Session Info R version 3.0.1 (2013-05-16) Platform: x86_64-apple-darwin10.8.0 (64-bit) locale: [1] en_GB.

The guys at Google continue to update and enhance the Chart Tools API. One new recent feature is a pie chart with a hole, or as some call them: donut charts. Thankfully the new functionality is being achieved through new options for the existing pie chart, which means that those new features are available in R via googleVis as well, without the need of writing new code. Doughnut chart example With the German election coming up soon, here is the composition of the current parliament.

Over the weekend googleVis 0.4.4 found its way to CRAN. The function gvisTable gained a new argument formats that allow users to define the formats numbers displayed in tables. Thanks to J. Buros, who contributed the code. Example Loading Session Info R version 3.0.1 (2013-05-16) Platform: x86_64-apple-darwin10.8.0 (64-bit) locale: [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8 attached base packages: [1] stats graphics grDevices utils datasets methods [7] base other attached packages: [1] googleVis_0.

I posted about the various googleVis axis options for base charts, such as line, bar and area charts earlier, but I somehow forgot to mention how to set the axes limits. Unfortunately, there are no arguments such as ylim and xlim. Instead, the Google Charts axes options are set via hAxes and vAxes, with h and v indicating the horizontal and vertical axis. More precisely, I have to set viewWindowMode : ‘explicit’ and set the viewWindow to the desired min and max values.

Today Diego and I will give our googleVis tutorial at useR!2013 in Albacete, Spain. googleVis Tutorial at useR! 2013 We will cover: Introduction and motivation Google Chart Tools R package googleVis Concepts of googleVis Case studies googleVis on shiny

The Google Charts Tools provide two kinds of heat map charts for geographical data, the Flash based Geomap and the HTML5/SVG based Geochart. I prefer the Geochart as it doesn’t require Flash, but so far there have been two shortcomings with it: I couldn’t add additional tooltip information and the default Mercator projection shows Greenland the size of Africa. Both of those issues seemed to have been resolved by Google.

Setting axis options in googleVis charts can be a bit tricky. Here I present two examples where I set several options to customise the layout of a line and combo chart with two axes. The parameters have to be set in line with the Google Chart Tools API, which uses a JavaScript syntax. In googleVis chart options are set via a list in the options argument. Some of the list items can be a bit more complex, often wrapped in {} brackets, e.

The guys at RStudio have done a fantastic job with shiny. It is really easy to build web apps with R using shiny. With the help of Joe Cheng from RStudio we figured out a way to make googleVis work on shiny as well. This allows you to make use of the Google Charts Tools in your shiny app directly from R. What I present here are three initial examples which seem to work in most browsers.

I am very grateful to all who provided feedback over the last two weeks and tested the previous versions 0.3.1 and 0.3.2, which were not released on CRAN. So, what changed since version 0.3.2? Not much, but plot.gvis didn’t open a browser window when options(gvis.plot.tag) were not set to NULL, but the user explicitly called plot.gvis with tag NULL. Thanks to Sebastian Kranz for reporting this bug. Additionally the vignette has been updated and includes an extended section on knitr.

After last week’s kerfuffle I hope the roll out of googleVis version 0.3.2 will be smooth. To test the water I release this version into the wild here and if it doesn’t get shot down in the next days, then I shall try to upload it to CRAN. I am mindful of the CRAN policy, so please get in touch or add comments below if you find any show stoppers.

Version 0.3.0 of the googleVis package for R has been released on CRAN on 20 October 2012. With this version we have been able to speed up the code considerably. The transformation of R data frames into JSON works significantly faster. The execution of the gvisMotionChart function in the World Bank demo is over 35 times faster. Thanks to ideas by Wei Luo and in particular to Sebastian Kranz for providing the code.

Today I feel very lucky, as I have been invited to the Royal Statistical Society conference to give a tutorial on interactive web graphs with R and googleVis. I prepared my slides with RStudio, knitr, pandoc and slidy, similar to my Cambridge R talk. You can access the RSS slides online here and you find the original R-Markdown file on github. You will notice some HTML code in the file, which I had to use to overcome my knowledge gaps of Markdown or its limitations.

The next version of the googleVis package has been released on the project site and CRAN. This version provides updates to the package vignette and a new example for the gvisMerge function. The new sections of the vignette have been featured on this blog in more detail earlier: Using googleVis with knitr (Link to post) Using Rook with googleVis (Link to post) Using Reduce with gvisMerge to display several charts on a page (Link to post) Additionally two little bugs were fixed: Data frames with one row only were not displayed in a chart.

At the R in Finance conference Paul Teetor gave a fantastic talk about Fast(er) R Code. Paul mentioned the common higher-order function Reduce, which I hadn’t used before. Reduce allows me to apply a function successively over a vector. What does that mean? Well, if I would like to add up the figures 1 to 5, I could say: add <- function(x,y) x+y add(add(add(add(1,2),3),4),5) or

Tonight I will give a talk at the Cambridge R user group about googleVis. Following my good experience with knitr and RStudio to create interactive reports, I thought that I should try to create the slides in the same way as well. Christopher Gandrud’s recent post reminded me of deck.js, a JavaScript library for interactive html slides, which I have used in the past, but as Christopher experienced, it is currently not that straightforward to use with R and knitr.

The data of the World Bank is absolutely amazing. I had said this before, but their updated iPhone App gives me a reason to return to this topic. Version 3 of the DataFinder App allows you to visualise the data on your phone, including motion maps, see the screen shot below. Screen shot of DataFinder 3.0 I was intrigued by the by the changes in life expectancy over time around the world.

The German newspaper Süddeutsche Zeitung (SZ) worked together with OpenDataCity to create an online train monitor of the German network: Zugmonitor. This is another great example of the new form of data journalism. The project provides access to data of train delays collected over 150 days between 2 October 2011 and 1 March 2012 and allows you to analyse the delays in more detail. Here is an example showing the delays by station.

The guys behind the Google Visualisation API don’t seem to rest. On 22 February 2012 they released an update of their API. Google added options for a gradient colour axis to bubble chart and a magnifying glass to geo chart, which opens when the user hovers over cluttered markers (excluding IE<=8). Those updates have been incorporated into version 0.2.15 of the googleVis package for R. Examples of new features Here are two examples demonstrating the new features.

Version 0.2.14 of the googleVis package was released on CRAN today. Changes The help files have been checked against changes of the Google Visualisation API, typos in the vignette have been ironed out (thanks to Pat Burns for pointing them out), a new section on dealing with apostrophes in column names has been added and the example in the section “Setting options” has been reviewed. For more details and demos check out the project site.

The financial crisis has put a lot of pressure on countries’ long-term foreign currency credit ratings, with France recently being downgraded by S&P. Wikipedia provides a list of countries by credit ratings as report by US rating agencies S&P, Fitch, Moody’s and Dagong, a Chinese rating agency. So, what does the world look like today through the eyes of those rating agencies? I use the R packages XML and googleVis to read and display the data from Wikipedia with just a few lines.

On 7th December Google published a new version of their Visualisation API. The new version adds a new chart type: Stepped Area Chart and provides improvements to Geo Chart. Now Geo Chart has similar functionality to Geo Map, but while Geo Map requires Flash, Geo Chart doesn’t, as it renders SVG/VML graphics. So it also works on your iOS devices. These new features have been added to the googleVis R package in version 0.

Following on from my article about accessing and plotting World Bank data with R I want to talk about how to change the initial view of a motion chart. Over the last couple of weeks I have been asked a view times how to do this. For instance Stephen O’Grady wanted to create a motion chart, which shows initially a line chart, rather than a bubble chart. Changing the initial settings of a motion chart is actually quite easy, if you know how to.

Over the past couple of days I played around with the data sets of the World Bank, and I have to admit that I am blown away by it. It is amazing, to see what is available on their web site and it is worth visiting their Data Visualisation Tools page. It is fantastic that they provide an API to their data. They have used it to build an iPhone App which is pretty cool.

It seems that you cannot include Google Visualisation Charts into a blog post directly. So, I tried to include the output of a googleVis function as a gadget, but also unsuccessfully. Although you can include gadgets into your site template, it doesn’t seem to work with blog posts. So, here is the trick which works for me: the iframe tag. The following geo map is included as // jsData function gvisDataGeoChartIDb0c403e03f4 () { var data = new google.

Today we published googleVis 0.2.9 on CRAN. The new version updates the package for the new features of the Google Visualisation API and brings a new in-page editor option. Here is a simple example, displaying the participants of the R user Conference 2011 in Warwick by country. Notice the ‘Edit me’ button in the top left corner of the chart, which allows you to change and customise the graph.