Add rows with total and group means in dplyr

dplyr_add_rows.R

library(dplyr)

# Add Total Mean for numeric variables
iris %>%
  add_row(
    summarise(.,
      Species = "Total mean",
      across(where(is.numeric), mean))
  ) %>%
  tail() # for printing

#>     Sepal.Length Sepal.Width Petal.Length Petal.Width    Species
#> 146     6.700000    3.000000        5.200    2.300000  virginica
#> 147     6.300000    2.500000        5.000    1.900000  virginica
#> 148     6.500000    3.000000        5.200    2.000000  virginica
#> 149     6.200000    3.400000        5.400    2.300000  virginica
#> 150     5.900000    3.000000        5.100    1.800000  virginica
#> 151     5.843333    3.057333        3.758    1.199333 Total mean

library(dplyr)
# Add group mean as new row to data
iris %>%
  group_by(Species) %>%
  group_map(.keep = TRUE,
    ~ add_row(.x,
        summarise(.x,
          Species = paste0(unlist(.y), " mean"),
          across(where(is.numeric), mean),
        )
      )) %>%
  bind_rows() %>%
  tail # for printing

#> # A tibble: 6 x 5
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#>          <dbl>       <dbl>        <dbl>       <dbl> <chr>
#> 1         6.7         3            5.2         2.3  virginica
#> 2         6.3         2.5          5           1.9  virginica
#> 3         6.5         3            5.2         2    virginica
#> 4         6.2         3.4          5.4         2.3  virginica
#> 5         5.9         3            5.1         1.8  virginica
#> 6         6.59        2.97         5.55        2.03 virginica mean

library(dplyr)
# Summarise by group and by total
iris %>%
  bind_rows(.,
    mutate(., Species = "all")) %>%
  group_by(Species) %>%
  summarise(across(.f = mean))

#> # A tibble: 4 x 5
#>   Species    Sepal.Length Sepal.Width Petal.Length Petal.Width
#>   <chr>             <dbl>       <dbl>        <dbl>       <dbl>
#> 1 all                5.84        3.06         3.76       1.20
#> 2 setosa             5.01        3.43         1.46       0.246
#> 3 versicolor         5.94        2.77         4.26       1.33
#> 4 virginica          6.59        2.97         5.55       2.03

# add mean for each groups and total mean as new row to data
library(dplyr)
iris %>%
  bind_rows(.,
    mutate(., Species = "all")) %>%
  group_by(Species) %>%
  group_map(.keep = TRUE,
    ~ add_row(.x,
      summarise(.x,
        Species = paste0(unlist(.y), " mean"),
        across(where(is.numeric), mean),
              )
            )) %>%
  bind_rows() %>%
  group_by(Species) %>% # --|
  slice_tail(n = 2) # ------| for printing

#> # A tibble: 12 x 5
#> # Groups:   Species [8]
#>    Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#>           <dbl>       <dbl>        <dbl>       <dbl> <chr>
#>  1         6.2         3.4          5.4        2.3   all
#>  2         5.9         3            5.1        1.8   all
#>  3         5.84        3.06         3.76       1.20  all mean
#>  4         5.3         3.7          1.5        0.2   setosa
#>  5         5           3.3          1.4        0.2   setosa
#>  6         5.01        3.43         1.46       0.246 setosa mean
#>  7         5.1         2.5          3          1.1   versicolor
#>  8         5.7         2.8          4.1        1.3   versicolor
#>  9         5.94        2.77         4.26       1.33  versicolor mean
#> 10         6.2         3.4          5.4        2.3   virginica
#> 11         5.9         3            5.1        1.8   virginica
#> 12         6.59        2.97         5.55       2.03  virginica mean