UPDATE: THE BLOG/SITE HAS MOVED TO GITHUB. THE NEW LINK FOR THE BLOG/SITE IS patilv.github.io and THE LINK TO THIS POST IS: http://bit.ly/1jJ6f7v. PLEASE UPDATE ANY BOOKMARKS YOU MAY HAVE.
In this post, I use a simulated dataset (7 variables -3 factor and 4 numeric - and a sample size of 50) to create graphs/charts using base R, and replicate them using ggplot2, and rCharts. This is not an attempt to create an exhaustive database of graphs/charts of all possible combinations, but it was an exercise to generate some of the common ones (in my view). These include dot plots, histograms, box plots, bar charts, scatter plots, density curves, and line graphs and a few more. I am sure the code can be further optimized and it could use some finishing touches with many things like legends, axes labels, and color, but at the core, I think it does its job. Pages of the 3 versions of graphs/charts were generated using slidify. Thanks to Ramnath Vaidyanathan for having answers to all questions and to the kind rCharts, ggplot2, and R community for the free knowledge base available on the Internet. The code for these pages can be found on github. Please click on this link for the analysis: http://bit.ly/18aWx3e
In this post, I use a simulated dataset (7 variables -3 factor and 4 numeric - and a sample size of 50) to create graphs/charts using base R, and replicate them using ggplot2, and rCharts. This is not an attempt to create an exhaustive database of graphs/charts of all possible combinations, but it was an exercise to generate some of the common ones (in my view). These include dot plots, histograms, box plots, bar charts, scatter plots, density curves, and line graphs and a few more. I am sure the code can be further optimized and it could use some finishing touches with many things like legends, axes labels, and color, but at the core, I think it does its job. Pages of the 3 versions of graphs/charts were generated using slidify. Thanks to Ramnath Vaidyanathan for having answers to all questions and to the kind rCharts, ggplot2, and R community for the free knowledge base available on the Internet. The code for these pages can be found on github. Please click on this link for the analysis: http://bit.ly/18aWx3e
No comments:
Post a Comment