How to use split() data

Question

I have data that spans over a week roughly that looks like this:

  Date       Time     Axis1 Axis2 Axis3 VM    Standing Stepping Cycling
  <chr>      <chr>    <chr> <chr> <chr> <chr> <chr>    <chr>      <dbl>
1 2022-05-06 14:34:00 0     0     0     0     0        0              0
2 2022-05-06 14:34:01 0     0     0     0     0        0              0
3 2022-05-06 14:34:02 0     0     0     0     0        0              0
4 2022-05-06 14:34:03 0     0     0     0     0        0              0
5 2022-05-06 14:34:04 0     0     0     0     0        0              0
6 2022-05-06 14:34:05 0     0     0     0     0        0              0
# … with 1 more variable: New_Sitting <dbl>

And I'm trying to sum every column per day, this is what I have so far

split(data1, f = data1$Date)
Sum_day <- colSums()

but it gives me an error of:

Error in colSums(2022 - 5 - 6) : 
'x' must be an array of at least two dimensions

So basically I'm not sure how to use the tibbles that are returned from the split() function, maybe I should be using another function to do what I want?

try `dplyr::group_by(data1, date) |> dplyr::summarise(dplyr::across(Axis1:Cycling, sum))` — AndS., May 17 '22 at 14:14
I tried ```group_by(data1,Date) summarise(across(Axis1:New_Sitting,sum))``` and it came back : Error in across() — Richard Michaud Langis, May 17 '22 at 14:41
Did you make sure to include a pipe from the `group_by` to the `summarize`? — AndS., May 18 '22 at 10:44
Yes, seems to be working now, Although I'm now having new issues unrelated to this, thank you — Richard Michaud Langis, May 18 '22 at 14:01

How to use split() data

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