I would like to create variable names dynamically while using dplyr; although, I’d be fine with a non-dplyr solution as well.
For Example:
data(iris)
Here is a data.table approach. I chose columns with numbers in this case. What you want to do is to choose column names and create new column names in advance. Then, you apply shift(), which works like lag() and lead() in the dplyr package, to each of the columns you chose.
library(data.table)
# Crate a df for this demo.
mydf <- iris
# Choose columns that you want to apply lag() and create new colnames.
cols = names(iris)[sapply(iris, is.numeric)]
anscols = paste("lag_", cols, sep = "")
# Apply shift() to each of the chosen columns.
setDT(mydf)[, (anscols) := shift(.SD, 1, type = "lag"),
.SDcols = cols]
Sepal.Length Sepal.Width Petal.Length Petal.Width Species lag_Sepal.Length lag_Sepal.Width
1: 5.1 3.5 1.4 0.2 setosa NA NA
2: 4.9 3.0 1.4 0.2 setosa 5.1 3.5
3: 4.7 3.2 1.3 0.2 setosa 4.9 3.0
4: 4.6 3.1 1.5 0.2 setosa 4.7 3.2
5: 5.0 3.6 1.4 0.2 setosa 4.6 3.1
---
146: 6.7 3.0 5.2 2.3 virginica 6.7 3.3
147: 6.3 2.5 5.0 1.9 virginica 6.7 3.0
148: 6.5 3.0 5.2 2.0 virginica 6.3 2.5
149: 6.2 3.4 5.4 2.3 virginica 6.5 3.0
150: 5.9 3.0 5.1 1.8 virginica 6.2 3.4
lag_Petal.Length lag_Petal.Width
1: NA NA
2: 1.4 0.2
3: 1.4 0.2
4: 1.3 0.2
5: 1.5 0.2
---
146: 5.7 2.5
147: 5.2 2.3
148: 5.0 1.9
149: 5.2 2.0
150: 5.4 2.3