extract_summary | R Documentation |
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.
extract_summary(data)
data |
A table object that is created using the |
A list of data frames containing summary data.
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 × 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 × 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 × 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 × 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")
13-5
Other Export Functions:
as_latex()
,
as_raw_html()
,
as_rtf()
,
gtsave()
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