How to Add Column Totals to Grouped Summaries in R - r

Question

I'm in the process of creating summaries tables based on subgroups and would love to add an overall summary in a tidyer/more efficient manner.
What I have so far is this. I've created summaries via levels within my factor variables.
library(tidyverse)
df <- data.frame(var1 = 10:18,
var2 = c("A","B","A","B","A","B","A","B","A"))
group_summary <- df %>% group_by(var2) %>%
filter(var2 != "NA") %>%
summarise("Max" = max(var1, na.rm = TRUE),
"Median" = median(var1, na.rm = TRUE),
"Min" = min(var1, na.rm = TRUE),
"IQR" = IQR(var1, na.rm = TRUE),
"Count" = n())
Next I created an overall summary.
Summary <- df %>%
filter(var2 != "NA") %>%
summarise("Max" = max(var1, na.rm = TRUE),
"Median" = median(var1, na.rm = TRUE),
"Min" = min(var1, na.rm = TRUE),
"IQR" = IQR(var1, na.rm = TRUE),
"Count" = n())
Finally, I bound the two objects with dplyr::bind_rows
complete_summary <- bind_rows(Summary, group_summary)
What I've done works but it is very, very verbose and can't be the most efficient way. I tried to use ungroup
group_summary <- df %>% group_by(var2) %>%
filter(var2 != "NA") %>%
summarise("Max" = max(var1, na.rm = TRUE),
"Median" = median(var1, na.rm = TRUE),
"Min" = min(var1, na.rm = TRUE),
"IQR" = IQR(var1, na.rm = TRUE),
"Count" = n()) %>% ungroup %>%
summarise("Max" = max(var1, na.rm = TRUE),
"Median" = median(var1, na.rm = TRUE),
"Min" = min(var1, na.rm = TRUE),
"IQR" = IQR(var1, na.rm = TRUE),
"Count" = n())
but it threw an error:
Evaluation error: object var1 not found.
Thanks in advance for your assistance.

Answer 1

Ideally, if you want to do it in one-chain, this is how you can do by using bind_rows to combine both the results, just like you've done - but removing the temporary objects you created.
library(tidyverse)
#> Warning: package 'tibble' was built under R version 3.5.2
df <- data.frame(var1 = 10:18,
var2 = c("A","B","A","B","A","B","A","B","A"))
df %>% group_by(var2) %>%
filter(var2 != "NA") %>%
summarise("Max" = max(var1, na.rm = TRUE),
"Median" = median(var1, na.rm = TRUE),
"Min" = min(var1, na.rm = TRUE),
"IQR" = IQR(var1, na.rm = TRUE),
"Count" = n()) %>% #ungroup() %>%
bind_rows( df %>% summarise("Max" = max(var1, na.rm = TRUE),
"Median" = median(var1, na.rm = TRUE),
"Min" = min(var1, na.rm = TRUE),
"IQR" = IQR(var1, na.rm = TRUE),
"Count" = n()))
#> # A tibble: 3 x 6
#> var2 Max Median Min IQR Count
#> <fct> <dbl> <dbl> <dbl> <dbl> <int>
#> 1 A 18 14 10 4 5
#> 2 B 17 14 11 3 4
#> 3 <NA> 18 14 10 4 9
Created on 2019-01-29 by the reprex package (v0.2.1)

Answer 2

Not the most elegant solution either, but simple:
c <- mtcars %>%
mutate(total_mean = mean(wt),
total_median = median(wt)) %>%
group_by(cyl) %>%
summarise(meanweight = mean(wt),
medianweight = median(wt),
total_mean = first(total_mean),
total_median = first(total_median))