Hi everyone,
I just wanted to bring attention to some of the great work done by the folks at RStudio, highlighted in their recent blog post:
blog.rstudio.org/2016/02/02/tidyr-0-4-0/
I've been using the tidyr package for some time now. It's very handy for converting data between 'wide' and 'long' formats, which is almost a must for data organization. This can make things like plotting or modelling by conditioning variables a breeze. What struck me most about the blog was some of the new features in the latest release of tidyr, particularly the ability to nest and unnest data frames. The ability to store nested R objects based on grouping variables in a data frame (or data table) seems like a real asset.
The other part of this blog that interested me was the 'complete' function. From the help file, this function 'turns implicit missing values into explicit missing values'. Consider an example of a time series with irregular time steps. I created the 'setstep' function in SWMPr to standardize a time series but it seems like the 'complete' function can perform similar tasks. I'm willing to bet that the 'complete' function does the job quicker and more efficiently... the RStudio team really know what they're doing.
Anyway, just wanted to spread the word.
Cheers,
Marcus