How to use Group_By() on multiple columns to sum the rest of the columns

Question

This is similar to Using group by on multiple columns but I'm not too sure how to apply it to my case.

Here is the head of my data I would like to group_by(Date, Participant Code), and then sum all the other columns.

head(all_ergo)
# A tibble: 6 × 10
  Date       time_bike distance bike_calories   power `Participant Code` time_active time_total desk_ca…¹ total…²
  <date>         <dbl>    <dbl>         <dbl>   <dbl> <chr>                    <dbl>      <dbl>     <dbl>   <dbl>
1 2022-04-12       120        0             0 0.00613 AE1_01                     360        360      11.0    11.0
2 2022-04-12       120        0             0 0.00613 AE1_01                    1920       1920      58.6    58.6
3 2022-04-12       120        0             0 0.00613 AE1_01                    3480       3480     106.    106. 
4 2022-04-12       120        0             0 0.00613 AE1_01                    3540       3540     108.    108. 
5 2022-04-12       120        0             0 0.00580 AE1_01                     360        360      11.0    11.0
6 2022-04-12       120        0             0 0.00580 AE1_01                    1920       1920      58.6    58.6
# … with abbreviated variable names ¹​desk_calories, ²​total_calories

Here I used a similar code, but I can't figure out how to expand it to grouping by 2 columns

Summary_PRE <- workday_PRE%>% group_by(Date) %>% mutate_if(is.character,as.numeric) %>% summarise(across(Axis1:Counter,sum))
Summary_PRE <- subset (Summary_PRE, select = -c(Axis1,Axis2,Axis3,VM))

Answer 1

I cant think in any short code way, but maybe as a temp solution you can specify all the columns in the summarise, like this:

df <- df %>%
  group_by(Date, `Participant Code`) %>%
  summarise(time_bike = sum(time_bike),
            distance = sum(distance),
            bike_calories = sum(bike_calories))

Answer 2

Here is what I came up with:

all_ergo <- all_ergo %>% group_by(`Date`, `Participant Code`) %>% mutate_if(is.character,as.numeric) %>% summarise(across(time_bike:total_calories,sum))