Summarize expression block constructor

This block allows to add new variables by summarizing over groups using R expressions (see dplyr::summarize()). Changes are applied after clicking the submit button.

Usage

new_summarize_expr_block(
  exprs = list(count = "dplyr::n()"),
  by = character(),
  unpack = FALSE,
  ...
)

Arguments

exprs

Reactive expression returning character vector of expressions

by

Columns to define grouping

unpack

Logical flag to unpack data frame columns from helper functions. When TRUE, expressions that return data frames will have their columns unpacked into separate columns. When FALSE, data frames are kept as nested list-columns. Default is FALSE.

...

Additional arguments forwarded to blockr.core::new_block()

Value

A block object for summarize operations

Details

For no-code summarization using dropdowns, see new_summarize_block().

Unpacking Helper Function Results

When unpack = TRUE, helper functions that return data frames will have their columns unpacked into separate columns in the result. This is useful for helper functions like stat_label() that return multiple statistics as columns.

# Without unpacking (default)
new_summarize_expr_block(
  exprs = list(stats = "helper_func(...)"),
  unpack = FALSE
)
# Result: Creates nested list-column "stats" containing the data frame

# With unpacking
new_summarize_expr_block(
  exprs = list(stats = "helper_func(...)"),
  unpack = TRUE
)
# Result: Columns from helper_func() are unpacked into separate columns

See also

blockr.core::new_transform_block()

Examples

# Create a summarize expression block
new_summarize_expr_block()
#> <summarize_expr_block<transform_block<block>>>
#> Name: "Summarize expr"
#> Data inputs: "data"
#> Initial block state:
#>  $ exprs :List of 1
#>   ..$ count: chr "dplyr::n()"
#>  $ by    : chr(0)
#>  $ unpack: logi FALSE
#> Constructor: blockr.dplyr::new_summarize_expr_block()

if (interactive()) {
  # Basic usage with mtcars dataset
  library(blockr.core)
  serve(new_summarize_expr_block(), list(data = mtcars))

  # With a custom dataset
  df <- data.frame(x = 1:5, y = letters[1:5])
  serve(new_summarize_expr_block(), list(data = df))

  # Using unpack to expand helper function results
  # Define the helper in your environment first
  calc_stats <- function(df) {
    data.frame(
      mean_x = mean(df$x),
      mean_y = mean(df$y),
      sum_x = sum(df$x),
      sum_y = sum(df$y)
    )
  }

  # With unpacking enabled
  serve(
    new_summarize_expr_block(
      exprs = list(stats = "calc_stats(pick(everything()))"),
      by = "group",
      unpack = TRUE
    ),
    list(data = data.frame(x = 1:6, y = 10:15, group = rep(c("A", "B"), 3)))
  )
  # Result: group, mean_x, mean_y, sum_x, sum_y (columns unpacked)
}