Christopher Gandrud
(간드루드 크리스토파)

As I go about cleaning and merging data sets with R I often end up creating and using simple functions over and over. When this happens, I stick them in the DataCombine package. This makes it easier for me to remember how to do an operation and others can possibly benefit from simplified and (hopefully) more intuitive code. I've talked about some of the commands in DataCombine in previous posts . In this post I'll give examples for a few more that I've added over the past couple of months. Note: these examples are based on DataCombine version 0.1.11. Here is a brief run down of the functions covered in this post: FindReplace : a function to replace multiple patterns found in a character string column of a data frame. MoveFront : moves variables to the front of a data frame. This can be useful if you have a data frame with many variables and want to move a variable or variables to the front. rmExcept : removes all objects from a work space except those specified...

I often want to quickly create a lag or lead variable in an R data frame. Sometimes I also want to create the lag or lead variable for different groups in a data frame, for example, if I want to lag GDP for each country in a data frame. I've found the various R methods for doing this hard to remember and usually need to look at old blog posts . Any time we find ourselves using the same series of codes over and over, it's probably time to put them into a function. So, I added a new command– slide –to the DataCombine R package (v0.1.5). Building on the shift function TszKin Julian posted on his blog , slide allows you to slide a variable up by any time unit to create a lead or down to create a lag. It returns the lag/lead variable to a new column in your data frame. It works with both data that has one observed unit and with time-series cross-sectional data. Note: your data needs to be in ascending time order with equally spaced time increments. For example 199...

Update (10 March 2013): FillIn is now part of the budding DataCombine package. Sometimes I want to use R to fill in values that are missing in one data frame with values from another. For example, I have data from the World Bank on government deficits. However, there are some country-years with missing data. I gathered data from Eurostat on deficits and want to use this data to fill in some of the values that are missing from my World Bank data. Doing this is kind of a pain so I created a function that would do it for me. It's called FillIn . An Example Here is an example using some fake data. (This example and part of the function was inspired by a Stack Exchange conversation between JD Long and Josh O'Brien.) First let's make two data frames: one with missing values in a variable called fNA . And a data frame with a more complete variable called fFull . # Create data set with missing values naDF <- data.frame(a = sample(c(1,2), 100, rep=TRUE), ...