add x lagged value to a tbl [duplicate] - r

Question

This question already has answers here:
Adding multiple lag variables using dplyr and for loops
(2 answers)
Closed 4 years ago.
I have a tibble like this:
df <- tibble(value = rnorm(500))
how can I add x (e.g. x = 10) lagged values to this tbl (ideally in a dplyr pipe)? I want to add these lagged variables as new columns.
I can do it for a single lag:
lag_df <- df %>%
mutate(value_lag = lag(value, n = 1)) %>% # first lag
filter(!is.na(value_lag)) # remove NA
doing it manually for 3 lags would look like this:
lag_df <- df %>%
mutate(value_lag1 = lag(value, n = 1)) %>% # first lag
mutate(value_lag2 = lag(value, n = 2)) %>% # second lag
mutate(value_lag3 = lag(value, n = 3)) %>% # third lag
filter(!is.na(value_lag1)) # remove NA
filter(!is.na(value_lag2)) # remove NA
filter(!is.na(value_lag3)) # remove NA

Answer 1

Not a complete dplyr solution but one way is to create a column for each lagged value and cbind it to the original daatframe and remove the rows with NA values with na.omit()
library(dplyr)
cbind(df, sapply(1:10, function(x) lag(df$value, n = x))) %>%
na.omit()
An ugly attempt to keep it completely in tidyverse with my broken skills
library(tidyverse)
tibble(n=1:10) %>% mutate(output = map2(list(df),n ,function(x,y){
x %>% mutate(value = lag(value,y))
})) %>% spread(n,output) %>% unnest() %>% na.omit()
The base R method is much cleaner than this but there should definitely be a better way to do it than this.
And a bit shorter version
map2(list(df), 1:10, function(x, y) {
x %>% mutate(value = lag(value,y))
}) %>%
bind_cols() %>% na.omit()