extract_summary: Extract a summary list from a *gt* object

In gt: Easily Create Presentation-Ready Display Tables

Extract a summary list from a gt object

Description

Get a list of summary row data frames from a gt_tbl object where summary rows were added via summary_rows(). The output data frames contain the group_id and rowname columns, whereby rowname contains descriptive stub labels for the summary rows.

Usage

extract_summary(data)

Arguments

data	The gt table data object ⁠obj:<gt_tbl>⁠ // required This is the gt table object that is commonly created through use of the gt() function.

Value

A list of data frames containing summary data.

Examples

Use a modified version of sp500 the dataset to create a gt table with row groups and row labels. Create summary rows labeled as min, max, and avg for every row group with summary_rows(). Then, extract the summary rows as a list object.

summary_extracted <-
  sp500 |>
  dplyr::filter(date >= "2015-01-05" & date <="2015-01-30") |>
  dplyr::arrange(date) |>
  dplyr::mutate(week = paste0("W", strftime(date, format = "%V"))) |>
  dplyr::select(-adj_close, -volume) |>
  gt(
    rowname_col = "date",
    groupname_col = "week"
  ) |>
  summary_rows(
    groups = everything(),
    columns = c(open, high, low, close),
    fns = list(
      min = ~min(.),
      max = ~max(.),
      avg = ~mean(.)
    ),
  ) |>
  extract_summary()

summary_extracted
#> $summary_df_data_list
#> $summary_df_data_list$W02
#> # A tibble: 3 x 9
#>   group_id row_id rowname  date  open  high   low close  week
#>   <chr>    <chr>  <chr>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 W02      min    min        NA 2006. 2030. 1992. 2003.    NA
#> 2 W02      max    max        NA 2063. 2064. 2038. 2062.    NA
#> 3 W02      avg    avg        NA 2035. 2049. 2017. 2031.    NA
#> 
#> $summary_df_data_list$W03
#> # A tibble: 3 x 9
#>   group_id row_id rowname  date  open  high   low close  week
#>   <chr>    <chr>  <chr>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 W03      min    min        NA 1992. 2018. 1988. 1993.    NA
#> 2 W03      max    max        NA 2046. 2057. 2023. 2028.    NA
#> 3 W03      avg    avg        NA 2020. 2033. 2000. 2015.    NA
#> 
#> $summary_df_data_list$W04
#> # A tibble: 3 x 9
#>   group_id row_id rowname  date  open  high   low close  week
#>   <chr>    <chr>  <chr>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 W04      min    min        NA 2020. 2029. 2004. 2023.    NA
#> 2 W04      max    max        NA 2063. 2065. 2051. 2063.    NA
#> 3 W04      avg    avg        NA 2035. 2049. 2023. 2042.    NA
#> 
#> $summary_df_data_list$W05
#> # A tibble: 3 x 9
#>   group_id row_id rowname  date  open  high   low close  week
#>   <chr>    <chr>  <chr>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 W05      min    min        NA 2002. 2023. 1989. 1995.    NA
#> 2 W05      max    max        NA 2050. 2058. 2041. 2057.    NA
#> 3 W05      avg    avg        NA 2030. 2039. 2009. 2021.    NA

Use the summary list to make a new gt table. The key thing is to use dplyr::bind_rows() and then pass the tibble to gt().

summary_extracted |>
  unlist(recursive = FALSE) |>
  dplyr::bind_rows() |>
  gt(groupname_col = "group_id") |>
  cols_hide(columns = row_id)

Function ID

13-8

Function Introduced

v0.2.0.5 (March 31, 2020)

See Also

Other table export functions: as_gtable(), as_latex(), as_raw_html(), as_rtf(), as_word(), extract_body(), extract_cells(), gtsave()

gt documentation built on April 12, 2025, 1:26 a.m.