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

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 ¹desk_calories, ²total_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))

CodePudding user response：

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))

CodePudding user response：

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))