Regular expressions in R

In my last post, I showed a few things I had figured out recently related to regular expressions. By now, you have also figured out that I like figuring things out in R, and application of regular expressions is one of these things.

Using the reshape package in R for pivot-table-like functionality

A little more than a week ago, I wrote about creating pivot tables in Microsoft Excel and I also mentioned that I would explain how to do similar calculations by using R. This post will explain how to achieve similar results in R by using the reshape package.

I had initially started experimenting with the reshape package several months ago when I was trying to figure out how to reshape data from wide to long formats. However, once I started experimenting with it, I realized I had misunderstood what the reshape package was designed to do. Now that I finally have a grasp of what can be done using the package, I thought I would share what I’ve found using a few examples.

Quickly reshaping data from `wide` to `long` formats in R

A lot of the times, students at the Academy enter data in a “wide” format (since it is a very natural way to enter data in a spreadsheet). Let’s say, for example, that they were collecting data for a household, and for each person, they were collecting information on three variables. Assume also that they were only collecting information about five household members. They might end up with a first row of column names something like “HouseholdID” | “member.01” | “member.02” | “member.03” | “member.04” | “member.05” | “variable1.01” | “variable1.02” | “variable1.03” | “variable1.04” | “variable1.05” | “variable2.01” | “variable2.02” … and so on. Sometimes, however, we may find it more useful to have our data in a “long” format. This post tells you how to quickly do that using R.