R help - Apr 2019 - Multiple Lags with Dplyr

Dear All,
I refer to the excellent post at

https://purrple.cat/blog/2018/03/02/multiple-lags-with-tidy-evaluation/

What I want to do is to create a function capable, ? la dplyr, to
generate new columns which are a lagged version of existing columns in
a data frame.
For instance, you can do this manually as


d2 <- tibble(x1 =1:10, x2=10:19,  x3=50:59)


d3 <- d2%>%mutate(x1lag1=lag(x1, 1), x1lag2=lag(x1,2))


but this becomes quickly tedious when you need to take several lags of
different columns.
One solution in the link above is the following


lags <- function(var, n=10){
  var <- enquo(var)
  
  indices <- seq_len(n)
  map( indices, ~quo(lag(!!var, !!.x)) ) %>% 
    set_names(sprintf("lag_%s_%02d", quo_text(var), indices))
  
}


d4 <- d2 %>% 
  mutate( !!!lags(x1, 3), !!!lags(x2,3) )


does anybody know how this could be made more general? I mean that I
would like to take a fixed number of lags of a list of columns (x1 and
x2, for instance), just by passing the list of columns and without
repeating the commands for x1 and x2.
Any suggestion is appreciated.
Cheers

Lorenzo

lag.zoo supports vector-based lags on zoo objects.
A few caveats:

- dplyr's lag clobbers the base R lag (which you need to
invoke lag's methods) so if you have dplyr loaded be sure
to refer to stats::lag.

- dplyr's lag works backwards relative to the standard set
in base R so dplyr::lag(x, 1) corresponds to stat::lag(x, -1) in
base R

- zoo follows base R's standard

- you can use as.data.frame or fortify.zoo to convert a zoo
object to a data frame if you need that.  The first one
drops the time index and the second one includes it.

  library(zoo)
  stats::lag(zoo(d2$x1), 0:-2)

giving this zoo object:

   lag0 lag-1 lag-2
1     1    NA    NA
2     2     1    NA
3     3     2     1
4     4     3     2
5     5     4     3
6     6     5     4
7     7     6     5
8     8     7     6
9     9     8     7
10   10     9     8


On Tue, Apr 23, 2019 at 9:10 AM Lorenzo Isella <lorenzo.isella at
gmail.com> wrote:
>
> Dear All,
> I refer to the excellent post at
>
> https://purrple.cat/blog/2018/03/02/multiple-lags-with-tidy-evaluation/
>
> What I want to do is to create a function capable, ? la dplyr, to
> generate new columns which are a lagged version of existing columns in
> a data frame.
> For instance, you can do this manually as
>
>
> d2 <- tibble(x1 =1:10, x2=10:19,  x3=50:59)
>
>
> d3 <- d2%>%mutate(x1lag1=lag(x1, 1), x1lag2=lag(x1,2))
>
>
> but this becomes quickly tedious when you need to take several lags of
> different columns.
> One solution in the link above is the following
>
>
> lags <- function(var, n=10){
>   var <- enquo(var)
>
>   indices <- seq_len(n)
>   map( indices, ~quo(lag(!!var, !!.x)) ) %>%
>     set_names(sprintf("lag_%s_%02d", quo_text(var), indices))
>
> }
>
>
> d4 <- d2 %>%
>   mutate( !!!lags(x1, 3), !!!lags(x2,3) )
>
>
> does anybody know how this could be made more general? I mean that I
> would like to take a fixed number of lags of a list of columns (x1 and
> x2, for instance), just by passing the list of columns and without
> repeating the commands for x1 and x2.
> Any suggestion is appreciated.
> Cheers
>
> Lorenzo
>
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