lags.Rmd

``` r
library(purrr)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(rlang)
#> 
#> Attaching package: 'rlang'
#> The following objects are masked from 'package:purrr':
#> 
#>     %@%, %||%, as_function, flatten, flatten_chr, flatten_dbl,
#>     flatten_int, flatten_lgl, invoke, list_along, modify, prepend,
#>     rep_along, splice

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))
  
}
d <- data_frame(x = seq_len(100))
mutate( d, !!!lags(x, 10) )
#> # A tibble: 100 x 11
#>        x lag_x_01 lag_x_02 lag_x_03 lag_x_04 lag_x_05 lag_x_06 lag_x_07
#>    <int>    <int>    <int>    <int>    <int>    <int>    <int>    <int>
#>  1     1       NA       NA       NA       NA       NA       NA       NA
#>  2     2        1       NA       NA       NA       NA       NA       NA
#>  3     3        2        1       NA       NA       NA       NA       NA
#>  4     4        3        2        1       NA       NA       NA       NA
#>  5     5        4        3        2        1       NA       NA       NA
#>  6     6        5        4        3        2        1       NA       NA
#>  7     7        6        5        4        3        2        1       NA
#>  8     8        7        6        5        4        3        2        1
#>  9     9        8        7        6        5        4        3        2
#> 10    10        9        8        7        6        5        4        3
#> # ... with 90 more rows, and 3 more variables: lag_x_08 <int>,
#> #   lag_x_09 <int>, lag_x_10 <int>
```