Logo Questions Linux Laravel Mysql Ubuntu Git Menu
 

How to create lag variables

Tags:

r

lag

I want to create lagged variable for a variable pm10 and used the following code. However, I could not get what I wanted. How could I create a lag of pm10?

df2$l1pm10 <- lag(df2$pm10, -1, na.pad = TRUE)
df2$l1pm102 <- lag(df2$pm10, 1)

dput(df2)
structure(list(var1 = 1:10, pm10 = c(26.956073733, NA, 32.838694951, 
39.9560737332, NA, 40.9560737332, 33.956073733, 28.956073733, 
32.348770798, NA), l1pm10 = structure(c(26.956073733, NA, 32.838694951, 
39.9560737332, NA, 40.9560737332, 33.956073733, 28.956073733, 
32.348770798, NA), .Tsp = c(2, 11, 1))), .Names = c("var1", "pm10", 
"l1pm10"), row.names = c("1", "2", "3", "4", "5", "6", "7", "8", 
"9", "10"), class = "data.frame")
like image 580
WangoR Avatar asked Aug 09 '15 13:08

WangoR


2 Answers

In base R the function lag() is useful for time series objects. Here you have a dataframe and the situation is somewhat different.

You could try the following, which I admit is not very elegant:

df2$l1pm10 <- sapply(1:nrow(df2), function(x) df2$pm10[x+1])
df2$l1pm102 <- sapply(1:nrow(df2), function(x) df2$pm10[x-1])
#> df2
#   var1     pm10   l1pm10  l1pm102
#1     1 26.95607       NA         
#2     2       NA 32.83869 26.95607
#3     3 32.83869 39.95607       NA
#4     4 39.95607       NA 32.83869
#5     5       NA 40.95607 39.95607
#6     6 40.95607 33.95607       NA
#7     7 33.95607 28.95607 40.95607
#8     8 28.95607 32.34877 33.95607
#9     9 32.34877       NA 28.95607
#10   10       NA       NA 32.34877

An alternative consists in using the Lag() function (with capital "L") from the Hmiscpackage:

library(Hmisc)
df2$l1pm10 <- Lag(df2$pm10, -1)
df2$l1pm102 <- Lag(df2$pm10, +1)
#> df2
#   var1     pm10   l1pm10  l1pm102
#1     1 26.95607       NA       NA
#2     2       NA 32.83869 26.95607
#3     3 32.83869 39.95607       NA
#4     4 39.95607       NA 32.83869
#5     5       NA 40.95607 39.95607
#6     6 40.95607 33.95607       NA
#7     7 33.95607 28.95607 40.95607
#8     8 28.95607 32.34877 33.95607
#9     9 32.34877       NA 28.95607
#10   10       NA       NA 32.34877
like image 197
RHertel Avatar answered Sep 18 '22 18:09

RHertel


Another alternative is using the shift-function from the data.table package:

library(data.table)
setDT(df2)[, c("l1pm10","l1pm102") := .(shift(pm10, 1L, fill = NA, type = "lag"),
                                        shift(pm10, 1L, fill = NA, type = "lead"))]

this gives:

> df2
    var1     pm10   l1pm10  l1pm102
 1:    1 26.95607       NA       NA
 2:    2       NA 26.95607 32.83869
 3:    3 32.83869       NA 39.95607
 4:    4 39.95607 32.83869       NA
 5:    5       NA 39.95607 40.95607
 6:    6 40.95607       NA 33.95607
 7:    7 33.95607 40.95607 28.95607
 8:    8 28.95607 33.95607 32.34877
 9:    9 32.34877 28.95607       NA
10:   10       NA 32.34877       NA

Used data:

df2 <- structure(list(var1 = 1:10, pm10 = c(26.956073733, NA, 32.838694951, 
39.9560737332, NA, 40.9560737332, 33.956073733, 28.956073733, 
32.348770798, NA)), .Names = c("var1", "pm10"), row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10"), class = "data.frame")
like image 32
Jaap Avatar answered Sep 18 '22 18:09

Jaap