How to get summaries at different levels

[stat_geek]

Hi all,

I'm creating a bunch of basic status reports and one of things I'm finding tedious is adding a total row to all my tables. I'm currently using the Tidyverse approach and this is an example of my current code. What I'm looking for is an option to have a few different levels included by default.

#load into RStudio viewer (not required)
iris = iris

#summary at the group level
summary_grouped = iris %>% 
       group_by(Species) %>%
       summarize(mean_s_length = mean(Sepal.Length),
                 max_s_width = max(Sepal.Width))

#summary at the overall level
summary_overall = iris %>% 
  summarize(mean_s_length = mean(Sepal.Length),
            max_s_width = max(Sepal.Width)) %>%
  mutate(Species = "Overall")
 
#append results for report       
summary_table = rbind(summary_grouped, summary_overall)

Doing this multiple times over is very tedious.

I kind of want:

summary_overall = iris %>% 
       group_by(Species, total = TRUE) %>%
       summarize(mean_s_length = mean(Sepal.Length),
                 max_s_width = max(Sepal.Width))

FYI - if you're familiar with SAS I'm looking for the same type of functionality available via a class, ways or types statements in proc means that let me control the level of summarization and get multiple levels in one call.

Any help is appreciated. I know I can create my own function, but was hoping there is something that already exists.

[mishabalyasin]

I'm 90% certain there is something like this in janitor package, but I've written my own function:

library(tidyverse)
create_summaries <- function(.data, ...){
  .data <- .data %>%
    dplyr::mutate(overall = "overall")
  
  dots <- rlang::quos(overall, !!!rlang::enquos(...))
  
  grouping_vars <- purrr::accumulate(dots, c)
  
  purrr::map_dfr(grouping_vars, function(vars){
    name <- paste0(purrr::flatten(purrr::map(vars, rlang::as_label)), collapse = "_")
    
    .data %>%
      dplyr::group_by(!!!vars) %>%
      dplyr::summarise(mean_s_length = mean(Sepal.Length),
                       max_s_width = max(Sepal.Width)) %>%
      dplyr::mutate(summarization_level = name)
  }) %>%
    dplyr::select(summarization_level, max_s_width, mean_s_length)
}

create_summaries(iris, Species, Petal.Length) 
#> Warning: Unquoting language objects with `!!!` is deprecated as of rlang 0.4.0.
#> Please use `!!` instead.
#> 
#>   # Bad:
#>   dplyr::select(data, !!!enquo(x))
#> 
#>   # Good:
#>   dplyr::select(data, !!enquo(x))    # Unquote single quosure
#>   dplyr::select(data, !!!enquos(x))  # Splice list of quosures
#> 
#> This warning is displayed once per session.
#> # A tibble: 52 x 3
#>    summarization_level          max_s_width mean_s_length
#>    <chr>                              <dbl>         <dbl>
#>  1 ~_overall                            4.4          5.84
#>  2 overall_Species                      4.4          5.01
#>  3 overall_Species                      3.4          5.94
#>  4 overall_Species                      3.8          6.59
#>  5 overall_Species_Petal.Length         3.6          4.6 
#>  6 overall_Species_Petal.Length         3            4.3 
#>  7 overall_Species_Petal.Length         4            5.4 
#>  8 overall_Species_Petal.Length         3.9          4.84
#>  9 overall_Species_Petal.Length         4.2          4.92
#> 10 overall_Species_Petal.Length         4.4          5.15
#> # … with 42 more rows

^{Created on 2019-06-21 by the reprex package (v0.3.0)}

You pass it all the variables that you want it to group by and then it creates summaries at combination of each level. You can definitely improve it by creating a way to pass in summary functions, but I thought it might be a good start for you. I might come back to it tomorrow

[aosmith]

FYI, cross-posting is fine questions on this site, we just ask that you link to the question on other sites. See the FAQ on cross-posting.

Here's the link to the same question on Stack Overflow: dataframe - Summarize data at different aggregate levels - R and tidyverse - Stack Overflow.

[stat_geek]

I think that first link is incorrect? Thanks for the note though!