Create function in R to apply to multiple datasets - r

Question

I have this code, recommended from a Stackoverflow user that works very well. I have
several datasets that I wish to apply this code to.
Would I have to continuously apply each dataset to the code, or is there something else that I can do? (Like store it in some sort of function?)
I have datsets
df1, df2, df3, df4. I do not wish to rbind these datasets.
Dput for each dataset:
structure(list(Date = structure(1:6, .Label = c("1/2/2020 5:00:00 PM",
"1/2/2020 5:30:01 PM", "1/2/2020 6:00:00 PM", "1/5/2020 7:00:01 AM",
"1/6/2020 8:00:00 AM", "1/6/2020 9:00:00 AM"), class = "factor"),
Duration = c(20L, 30L, 10L, 5L, 2L, 8L)), class = "data.frame", row.names = c(NA,
-6L))
CODE:
df %>%
group_by(Date = as.Date(dmy_hms(Date))) %>%
summarise(Total_Duration = sum(Duration), Count = n())
This is what I have been doing for each:(etc)
df1 %>%
group_by(Date = as.Date(dmy_hms(Date))) %>%
summarise(Total_Duration = sum(Duration), Count = n())
df2 %>%
group_by(Date = as.Date(dmy_hms(Date))) %>%
summarise(Total_Duration = sum(Duration), Count = n())
df3 %>%
group_by(Date = as.Date(dmy_hms(Date))) %>%
summarise(Total_Duration = sum(Duration), Count = n())
Is there a way to:
Store_code<-
df %>%
group_by(Date = as.Date(dmy_hms(Date))) %>%
summarise(Total_Duration = sum(Duration), Count = n())
and then apply each dataset easily to this code?
df1(Store_code)
df2(Store_code)
Any suggestion is appreciated.

Answer 1

We can use mget to return all the objects into a list, use map to loop over the list and apply the function
library(dplyr)
library(lubridate)
library(purrr)
f1 <- function(dat) {
dat %>%
group_by(Date = as.Date(dmy_hms(Date))) %>%
summarise(Total_Duration = sum(Duration), Count = n())
}
lst1 <- map(mget(ls(pattern = "^df\\d+$")), f1)
Here, we assume the column names are the same i.e. 'Date', 'Duration' in all the datasets. If it is a different one, then can pass as another argument to function
f2 <- function(dat, datecol, durationcol) {
dat %>%
group_by(Date = as.Date(dmy_hms({{datecol}}))) %>%
summarise(Total_Duration = sum({{durationcol}}), Count = n())
}
and apply the function as
f2(df1, Date, Duration)
Or in the loop
lst1 <- map(mget(ls(pattern = "^df\\d+$")), f2,
datecol = Date, durationcol = Duration)