extract_summary: 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 the summary_rows() function. 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)

Value

A list of data frames containing summary data.

Arguments

data: A table object that is created using the gt() function.

Examples

Use sp500 to create a gt table with row groups. 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 = TRUE,
    columns = c(open, high, low, close),
    fns = list(
      min = ~min(.),
      max = ~max(.),
      avg = ~mean(.)
    ),
    formatter = fmt_number,
    use_seps = FALSE
  ) %>%
  extract_summary()
summary_extracted
#> $summary_df_data_list
#> $summary_df_data_list$W02
#> # A tibble: 3 x 8
#>   group_id rowname  date  open  high   low close  week
#>   <chr>    <chr>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 W02      min        NA 2006. 2030. 1992. 2003.    NA
#> 2 W02      max        NA 2063. 2064. 2038. 2062.    NA
#> 3 W02      avg        NA 2035. 2049. 2017. 2031.    NA
#> 
#> $summary_df_data_list$W03
#> # A tibble: 3 x 8
#>   group_id rowname  date  open  high   low close  week
#>   <chr>    <chr>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 W03      min        NA 1992. 2018. 1988. 1993.    NA
#> 2 W03      max        NA 2046. 2057. 2023. 2028.    NA
#> 3 W03      avg        NA 2020. 2033. 2000. 2015.    NA
#> 
#> $summary_df_data_list$W04
#> # A tibble: 3 x 8
#>   group_id rowname  date  open  high   low close  week
#>   <chr>    <chr>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 W04      min        NA 2020. 2029. 2004. 2023.    NA
#> 2 W04      max        NA 2063. 2065. 2051. 2063.    NA
#> 3 W04      avg        NA 2035. 2049. 2023. 2042.    NA
#> 
#> $summary_df_data_list$W05
#> # A tibble: 3 x 8
#>   group_id rowname  date  open  high   low close  week
#>   <chr>    <chr>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 W05      min        NA 2002. 2023. 1989. 1995.    NA
#> 2 W05      max        NA 2050. 2058. 2041. 2057.    NA
#> 3 W05      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")

This image of a table was generated from the first code example in the `extract_summary()` help file.

Function ID