-
- This program is free software: you can redistribute it and/or modify
- it under the terms of the GNU Affero General Public License as published
- by the Free Software Foundation, either version 3 of the License, or
- (at your option) any later version.
-
- This program is distributed in the hope that it will be useful,
- but WITHOUT ANY WARRANTY; without even the implied warranty of
- MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- GNU Affero General Public License for more details.
-
- You should have received a copy of the GNU Affero General Public License
- along with this program. If not, see .
-
-Also add information on how to contact you by electronic and paper mail.
-
- If your software can interact with users remotely through a computer
-network, you should also make sure that it provides a way for users to
-get its source. For example, if your program is a web application, its
-interface could display a "Source" link that leads users to an archive
-of the code. There are many ways you could offer source, and different
-solutions will be better for different programs; see section 13 for the
-specific requirements.
-
- You should also get your employer (if you work as a programmer) or school,
-if any, to sign a "copyright disclaimer" for the program, if necessary.
-For more information on this, and how to apply and follow the GNU AGPL, see
-.
diff --git a/NAMESPACE b/NAMESPACE
index 818b965..8e9465d 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -24,7 +24,6 @@ export(count_calc)
export(cp)
export(d)
export(get_summary_calculation_names)
-export(hss)
export(instat_comment)
export(link)
export(mNSE)
@@ -47,7 +46,6 @@ export(p70)
export(p75)
export(p80)
export(p90)
-export(pc)
export(proportion_calc)
export(pss)
export(rNSE)
diff --git a/R/data_book.R b/R/data_book.R
index cd4bb5f..c309542 100644
--- a/R/data_book.R
+++ b/R/data_book.R
@@ -245,18 +245,18 @@
#' \item{\code{link_between_containing(from_data_frame, containing_columns, to_data_frame)}}{This function returns columns in `to_data_frame` corresponding to `containing_columns` in `from_data_frame` if a link exists between them.}
#' \item{\code{view_link(link_name)}}{Displays the details of a specified link.}
#'
-#' \item{\code{apply_calculation(calc)}{Apply a Calculation to Data in the DataBook}}
-#' \item{\code{save_calculation(end_data_frame, calc)}{Save a Calculation to a Data Frame}}
-#' \item{\code{apply_instat_calculation(calc, curr_data_list, previous_manipulations = list(), param_list = list())}{Apply an Instat Calculation}}
-#' \item{\code{run_instat_calculation(calc, display = TRUE, param_list = list())}{Run an Instat Calculation and Display Results}}
-#' \item{\code{get_corresponding_link_columns(first_data_frame_name, first_data_frame_columns, second_data_frame_name)}{Get Corresponding Link Columns}}
-#' \item{\code{get_link_columns_from_data_frames(first_data_frame_name, first_data_frame_columns, second_data_frame_name, second_data_frame_columns)}{Get Link Columns Between Data Frames}}
-#' \item{\code{save_calc_output(calc, curr_data_list, previous_manipulations)}{Save the Output of a Calculation}}
+#' \item{\code{apply_calculation(calc)}}{Apply a Calculation to Data in the DataBook}
+#' \item{\code{save_calculation(end_data_frame, calc)}}{Save a Calculation to a Data Frame}
+#' \item{\code{apply_instat_calculation(calc, curr_data_list, previous_manipulations = list(), param_list = list())}}{Apply an Instat Calculation}
+#' \item{\code{run_instat_calculation(calc, display = TRUE, param_list = list())}}{Run an Instat Calculation and Display Results}
+#' \item{\code{get_corresponding_link_columns(first_data_frame_name, first_data_frame_columns, second_data_frame_name)}}{Get Corresponding Link Columns}
+#' \item{\code{get_link_columns_from_data_frames(first_data_frame_name, first_data_frame_columns, second_data_frame_name, second_data_frame_columns)}}{Get Link Columns Between Data Frames}
+#' \item{\code{save_calc_output(calc, curr_data_list, previous_manipulations)}}{Save the Output of a Calculation}
#'
-#' \item{\code{append_summaries_to_data_object(out, data_name, columns_to_summarise, summaries, factors = c(), summary_name, calc, calc_name = "")}{Append Summaries to a Data Object}}
-#' \item{\code{calculate_summary(data_name, columns_to_summarise = NULL, summaries, factors = c(), store_results = TRUE, drop = TRUE, return_output = FALSE, summary_name = NA, result_names = NULL, percentage_type = "none", perc_total_columns = NULL, perc_total_factors = c(), perc_total_filter = NULL, perc_decimal = FALSE, perc_return_all = FALSE, include_counts_with_percentage = FALSE, silent = FALSE, additional_filter, original_level = FALSE, signif_fig = 2, sep = "_", ...)}{Calculate Summaries for a Data Object}}
-#' \item{\code{summary(data_name, columns_to_summarise, summaries, factors = c(), store_results = FALSE, drop = FALSE, return_output = FALSE, summary_name = NA, add_cols = c(), filter_names = c(), ...)}{Perform and Return Summaries for a Data Object}}
-#' \item{\code{summary_table(data_name, columns_to_summarise = NULL, summaries, factors = c(), store_table = FALSE, store_results = FALSE, drop = TRUE, na.rm = FALSE, summary_name = NA, include_margins = FALSE, margins = "outer", return_output = FALSE, treat_columns_as_factor = FALSE, page_by = NULL, signif_fig = 2, na_display = "", na_level_display = "NA", weights = NULL, caption = NULL, result_names = NULL, percentage_type = "none", perc_total_columns = NULL, perc_total_factors = c(), perc_total_filter = NULL, perc_decimal = FALSE, include_counts_with_percentage = FALSE, margin_name = "(All)", additional_filter, ...)}{Generate a Summary Table}}
+#' \item{\code{append_summaries_to_data_object(out, data_name, columns_to_summarise, summaries, factors = c(), summary_name, calc, calc_name = "")}}{Append Summaries to a Data Object}
+#' \item{\code{calculate_summary(data_name, columns_to_summarise = NULL, summaries, factors = c(), store_results = TRUE, drop = TRUE, return_output = FALSE, summary_name = NA, result_names = NULL, percentage_type = "none", perc_total_columns = NULL, perc_total_factors = c(), perc_total_filter = NULL, perc_decimal = FALSE, perc_return_all = FALSE, include_counts_with_percentage = FALSE, silent = FALSE, additional_filter, original_level = FALSE, signif_fig = 2, sep = "_", ...)}}{Calculate Summaries for a Data Object}
+#' \item{\code{summary(data_name, columns_to_summarise, summaries, factors = c(), store_results = FALSE, drop = FALSE, return_output = FALSE, summary_name = NA, add_cols = c(), filter_names = c(), ...)}}{Perform and Return Summaries for a Data Object}
+#' \item{\code{summary_table(data_name, columns_to_summarise = NULL, summaries, factors = c(), store_table = FALSE, store_results = FALSE, drop = TRUE, na.rm = FALSE, summary_name = NA, include_margins = FALSE, margins = "outer", return_output = FALSE, treat_columns_as_factor = FALSE, page_by = NULL, signif_fig = 2, na_display = "", na_level_display = "NA", weights = NULL, caption = NULL, result_names = NULL, percentage_type = "none", perc_total_columns = NULL, perc_total_factors = c(), perc_total_filter = NULL, perc_decimal = FALSE, include_counts_with_percentage = FALSE, margin_name = "(All)", additional_filter, ...)}}{Generate a Summary Table}
#'
#' @export
DataBook <- R6::R6Class("DataBook",
@@ -4759,8 +4759,7 @@ DataBook <- R6::R6Class("DataBook",
#' `save_calculation` method to store the calculation.
#' - The `calc` object typically includes details such as its `name`, `type`, and any parameters
#' or dependencies required to perform the calculation.
- #'
- #' @seealso \code{\link{DataSheet$save_calculation}}
+ #' - See also \code{\link{DataSheet$save_calculation}}
#'
#' @note This method delegates the actual saving of the calculation to the respective
#' data frame's `save_calculation` method, ensuring modularity and separation of concerns.
@@ -5064,9 +5063,9 @@ DataBook <- R6::R6Class("DataBook",
warning(paste0("Type is different for ", by[[i]], " in the two data frames. Setting as numeric in both data frames."))
# Convert factors to numeric if necessary
- if (class(new_data_list[[by[[i]]]]) == "factor") {
+ if (inherits(class(new_data_list[[by[[i]]]]), "factor")) {
new_data_list[[by[[i]]]] <- as.numeric(as.character(new_data_list[[by[[i]]]]))
- } else if (class(curr_data_list[[c_data_label]][[by[[i]]]]) == "factor") {
+ } else if (inherits(class(curr_data_list[[c_data_label]][[by[[i]]]]), "factor")) {
curr_data_list[[c_data_label]][[by[[i]]]] <- as.numeric(as.character(curr_data_list[[c_data_label]][[by[[i]]]]))
} else {
stop(paste0("Type is different for ", by[[i]], " in the two data frames and cannot be coerced."))
diff --git a/R/data_sheet.R b/R/data_sheet.R
index cb76f05..91fe8f2 100644
--- a/R/data_sheet.R
+++ b/R/data_sheet.R
@@ -187,8 +187,8 @@
#'
#' \item{\code{save_calculation(calc)}}{Save a Calculation to the DataSheet.}
#'
-#' \item{\code{merge_data(new_data, by = NULL, type = "left", match = "all")}{Merge New Data with Existing Data}}
-#' \item{\code{calculate_summary(calc, ...)}{Calculate Summaries for Specified Columns}}
+#' \item{\code{merge_data(new_data, by = NULL, type = "left", match = "all")}}{Merge New Data with Existing Data}
+#' \item{\code{calculate_summary(calc, ...)}}{Calculate Summaries for Specified Columns}
#' }
#'
#' @section Active bindings:
diff --git a/R/summary_functions.R b/R/summary_functions.R
index 2084b13..47f4b19 100644
--- a/R/summary_functions.R
+++ b/R/summary_functions.R
@@ -485,7 +485,7 @@ summary_var <- function(x, na.rm = FALSE, weights = NULL, na_type = "", ...) {
if(na.rm && na_type != "" && !na_check(x, na_type = na_type, ...)) return(NA)
else{
if (missing(weights) || is.null(weights)) {
- return(var(x,na.rm = na.rm))
+ return(stats::var(x,na.rm = na.rm))
}
else {
return(Hmisc::wtd.var(x, weights = weights, na.rm = na.rm))
@@ -669,9 +669,9 @@ summary_median <- function(x, na.rm = FALSE, weights = NULL, na_type = "", ...)
else{
if(missing(weights) || is.null(weights)) {
if (stringr::str_detect(class(x), pattern = "ordered") || stringr::str_detect(class(x), pattern = "Date")) {
- return(quantile(x, na.rm = na.rm, probs = 0.5, type = 1)[[1]])
+ return(stats::quantile(x, na.rm = na.rm, probs = 0.5, type = 1)[[1]])
} else {
- return(median(x, na.rm = na.rm))
+ return(stats::median(x, na.rm = na.rm))
}
} else {
return(Hmisc::wtd.quantile(x, weights = weights, probs = 0.5, na.rm = na.rm))
@@ -698,9 +698,9 @@ summary_quantile <- function(x, na.rm = FALSE, weights = NULL, probs, na_type =
else {
if(missing(weights) || is.null(weights)) {
if (stringr::str_detect(class(x), pattern = "ordered") || stringr::str_detect(class(x), pattern = "Date")) {
- return(quantile(x, na.rm = na.rm, probs = probs, type = 1)[[1]])
+ return(stats::quantile(x, na.rm = na.rm, probs = probs, type = 1)[[1]])
} else {
- return(quantile(x, na.rm = na.rm, probs = probs)[[1]])
+ return(stats::quantile(x, na.rm = na.rm, probs = probs)[[1]])
}
}
else {
@@ -913,7 +913,7 @@ summary_outlier_limit <- function(x, coef = 1.5, bupperlimit = TRUE, bskewedcalc
}
if(na.rm && na_type != "" && !na_check(x, na_type = na_type, ...)) return(NA)
else{
- quart <- quantile(x, na.rm = na.rm)
+ quart <- stats::quantile(x, na.rm = na.rm)
Q1 <- quart[[2]]
Q3 <- quart[[4]]
IQR <- Q3 - Q1
@@ -1077,7 +1077,7 @@ summary_cor <- function(x, y, na.rm = FALSE, na_type = "", weights = NULL, metho
if (na.rm && na_type != "" && !na_check(x, na_type = na_type, ...)) return(NA)
else {
if (missing(weights) || is.null(weights)) {
- return(cor(x = x, y = y, use = cor_use, method = method))
+ return(stats::cor(x = x, y = y, use = cor_use, method = method))
}
else {
weights::wtd.cor(x = x, y = y, weight = weights)[1]
@@ -1103,7 +1103,7 @@ summary_cov <- function(x, y, na.rm = FALSE, weights = NULL, na_type = "", metho
if(na.rm && na_type != "" && !na_check(x, na_type = na_type, ...)) return(NA)
else{
if (missing(weights) || is.null(weights)) {
- return(cov(x = x, y = y, use = use, method = method))
+ return(stats::cov(x = x, y = y, use = use, method = method))
}
if (length(weights) != length(x))
stop("'x' and 'weights' must have the same length")
@@ -1245,7 +1245,7 @@ proportion_calc <- function(x, prop_test = "==", prop_value, As_percentage = FAL
}
}
else {
- remove.na <- na.omit(x)
+ remove.na <- stats::na.omit(x)
y <- remove.na[eval(parse(text = paste("remove.na", prop_value, sep = prop_test)))]
if (!As_percentage){
return(round(length(y)/length(remove.na), digits = 2))
@@ -1277,7 +1277,7 @@ count_calc <- function(x, count_test = "==", count_value, na.rm = FALSE, na_type
return(length(x[eval(parse(text = paste("x", count_value, sep = count_test)))]))
}
else{
- y <- na.omit(x)
+ y <- stats::na.omit(x)
return(length(y[eval(parse(text = paste("y", count_value, sep = count_test)))]))
}
}
@@ -1298,11 +1298,11 @@ standard_error_mean <- function(x, na.rm = FALSE, na_type = "", ...){
else{
if (!na.rm){
if(sum(is.na(x) > 0)) return(NA)
- return(sd(x)/sqrt(length(x)))
+ return(stats::sd(x)/sqrt(length(x)))
}
else{
- y <- na.omit(x)
- return(sd(y)/sqrt(length(y)))
+ y <- stats::na.omit(x)
+ return(stats::sd(y)/sqrt(length(y)))
}
}
}
@@ -1603,39 +1603,39 @@ VE <- function(x, y, na.rm = FALSE, na_type = "", ...){
}
}
-#' Calculate Percent Correct
-#'
-#' Computes the percent correct using the `verification::verify` function.
-#'
-#' @param x Observed values.
-#' @param y Predicted values.
-#' @param frcst.type Character. The type of forecast (e.g., "binary").
-#' @param obs.type Character. The type of observation (e.g., "binary").
-#' @param ... Additional arguments passed to `verification::verify`.
-#' @return The percent correct.
-#' @export
-pc <- function(x, y, frcst.type, obs.type, ...){
- A <- verification::verify(obs = x, pred = y, frcst.type = frcst.type, obs.type = obs.type)
- return(A$pc)
-}
-
-#' Calculate Heidke Skill Score
-#'
-#' Computes the Heidke skill score using the `verification::verify` function.
-#'
-#' @inheritParams pc
-#' @return The Heidke skill score.
-#' @export
-hss <- function(x, y, frcst.type, obs.type, ...){
- A <- verification::verify(obs = x, pred = y, frcst.type = frcst.type, obs.type = obs.type)
- return(A$hss)
-}
+# This repetition causes issue in package
+# #' Calculate Percent Correct
+# #'
+# #' Computes the percent correct using the `verification::verify` function.
+# #'
+# #' @param x Observed values.
+# #' @param y Predicted values.
+# #' @param frcst.type Character. The type of forecast (e.g., "binary").
+# #' @param obs.type Character. The type of observation (e.g., "binary").
+# #' @param ... Additional arguments passed to `verification::verify`.
+# #' @return The percent correct.
+# #' @export
+# pc <- function(x, y, frcst.type, obs.type, ...){
+# A <- verification::verify(obs = x, pred = y, frcst.type = frcst.type, obs.type = obs.type)
+# return(A$pc)
+# }
+# #' Calculate Heidke Skill Score
+# #'
+# #' Computes the Heidke skill score using the `verification::verify` function.
+# #'
+# #' @inheritParams PC
+# #' @return The Heidke skill score.
+# #' @export
+# hss <- function(x, y, frcst.type, obs.type, ...){
+# A <- verification::verify(obs = x, pred = y, frcst.type = frcst.type, obs.type = obs.type)
+# return(A$hss)
+# }
#' Calculate Pierce Skill Score
#'
#' Computes the Pierce skill score using the `verification::verify` function.
#'
-#' @inheritParams pc
+#' @inheritParams PC
#' @return The Pierce skill score.
#' @export
pss <- function(x, y, frcst.type, obs.type, ...){
@@ -1647,7 +1647,7 @@ pss <- function(x, y, frcst.type, obs.type, ...){
#'
#' Computes the Gerrity score using the `verification::verify` function.
#'
-#' @inheritParams pc
+#' @inheritParams PC
#' @return The Gerrity score.
#' @export
GS <- function(x, y, frcst.type, obs.type, ...){
@@ -1659,7 +1659,7 @@ GS <- function(x, y, frcst.type, obs.type, ...){
#'
#' Computes the probability of detection (PODy) using the `verification::verify` function.
#'
-#' @inheritParams pc
+#' @inheritParams PC
#' @return The probability of detection.
#' @export
PODy <- function(x, y, frcst.type, obs.type, ...){
@@ -1671,7 +1671,7 @@ PODy <- function(x, y, frcst.type, obs.type, ...){
#'
#' Computes the threat score using the `verification::verify` function.
#'
-#' @inheritParams pc
+#' @inheritParams PC
#' @return The threat score.
#' @export
TS <- function(x, y, frcst.type, obs.type, ...){
@@ -1683,7 +1683,7 @@ TS <- function(x, y, frcst.type, obs.type, ...){
#'
#' Computes the equitable threat score using the `verification::verify` function.
#'
-#' @inheritParams pc
+#' @inheritParams PC
#' @return The equitable threat score.
#' @export
ETS <- function(x, y, frcst.type, obs.type, ...){
@@ -1695,7 +1695,7 @@ ETS <- function(x, y, frcst.type, obs.type, ...){
#'
#' Computes the false alarm ratio using the `verification::verify` function.
#'
-#' @inheritParams pc
+#' @inheritParams PC
#' @return The false alarm ratio.
#' @export
FAR <- function(x, y, frcst.type, obs.type, ...){
@@ -1707,7 +1707,7 @@ FAR <- function(x, y, frcst.type, obs.type, ...){
#'
#' Computes the Heidke skill score using the `verification::verify` function.
#'
-#' @inheritParams pc
+#' @inheritParams PC
#' @return The Heidke skill score.
#' @export
HSS <- function(x, y, frcst.type, obs.type, ...){
@@ -1719,7 +1719,11 @@ HSS <- function(x, y, frcst.type, obs.type, ...){
#'
#' Computes the percent correct using the `verification::verify` function.
#'
-#' @inheritParams pc
+#' @param x Observed values.
+#' @param y Predicted values.
+#' @param frcst.type Character. The type of forecast (e.g., "binary").
+#' @param obs.type Character. The type of observation (e.g., "binary").
+#' @param ... Additional arguments passed to `verification::verify`.
#' @return The percent correct.
#' @export
PC <- function(x, y, frcst.type, obs.type, ...){
@@ -1731,7 +1735,7 @@ PC <- function(x, y, frcst.type, obs.type, ...){
#'
#' Computes the bias using the `verification::verify` function.
#'
-#' @inheritParams pc
+#' @inheritParams PC
#' @return The bias.
#' @export
BIAS <- function(x, y, frcst.type, obs.type, ...){
diff --git a/man/DataBook.Rd b/man/DataBook.Rd
index 7cbd01e..e289efb 100644
--- a/man/DataBook.Rd
+++ b/man/DataBook.Rd
@@ -251,25 +251,22 @@ their existence in both data frames.
\item{\code{link_between_containing(from_data_frame, containing_columns, to_data_frame)}}{This function returns columns in \code{to_data_frame} corresponding to \code{containing_columns} in \code{from_data_frame} if a link exists between them.}
\item{\code{view_link(link_name)}}{Displays the details of a specified link.}
-\item{\code{apply_calculation(calc)}{Apply a Calculation to Data in the DataBook}}
-\item{\code{save_calculation(end_data_frame, calc)}{Save a Calculation to a Data Frame}}
-\item{\code{apply_instat_calculation(calc, curr_data_list, previous_manipulations = list(), param_list = list())}{Apply an Instat Calculation}}
-\item{\code{run_instat_calculation(calc, display = TRUE, param_list = list())}{Run an Instat Calculation and Display Results}}
-\item{\code{get_corresponding_link_columns(first_data_frame_name, first_data_frame_columns, second_data_frame_name)}{Get Corresponding Link Columns}}
-\item{\code{get_link_columns_from_data_frames(first_data_frame_name, first_data_frame_columns, second_data_frame_name, second_data_frame_columns)}{Get Link Columns Between Data Frames}}
-\item{\code{save_calc_output(calc, curr_data_list, previous_manipulations)}{Save the Output of a Calculation}}
-
-\item{\code{append_summaries_to_data_object(out, data_name, columns_to_summarise, summaries, factors = c(), summary_name, calc, calc_name = "")}{Append Summaries to a Data Object}}
-\item{\code{calculate_summary(data_name, columns_to_summarise = NULL, summaries, factors = c(), store_results = TRUE, drop = TRUE, return_output = FALSE, summary_name = NA, result_names = NULL, percentage_type = "none", perc_total_columns = NULL, perc_total_factors = c(), perc_total_filter = NULL, perc_decimal = FALSE, perc_return_all = FALSE, include_counts_with_percentage = FALSE, silent = FALSE, additional_filter, original_level = FALSE, signif_fig = 2, sep = "_", ...)}{Calculate Summaries for a Data Object}}
-\item{\code{summary(data_name, columns_to_summarise, summaries, factors = c(), store_results = FALSE, drop = FALSE, return_output = FALSE, summary_name = NA, add_cols = c(), filter_names = c(), ...)}{Perform and Return Summaries for a Data Object}}
-\item{\code{summary_table(data_name, columns_to_summarise = NULL, summaries, factors = c(), store_table = FALSE, store_results = FALSE, drop = TRUE, na.rm = FALSE, summary_name = NA, include_margins = FALSE, margins = "outer", return_output = FALSE, treat_columns_as_factor = FALSE, page_by = NULL, signif_fig = 2, na_display = "", na_level_display = "NA", weights = NULL, caption = NULL, result_names = NULL, percentage_type = "none", perc_total_columns = NULL, perc_total_factors = c(), perc_total_filter = NULL, perc_decimal = FALSE, include_counts_with_percentage = FALSE, margin_name = "(All)", additional_filter, ...)}{Generate a Summary Table}}
+\item{\code{apply_calculation(calc)}}{Apply a Calculation to Data in the DataBook}
+\item{\code{save_calculation(end_data_frame, calc)}}{Save a Calculation to a Data Frame}
+\item{\code{apply_instat_calculation(calc, curr_data_list, previous_manipulations = list(), param_list = list())}}{Apply an Instat Calculation}
+\item{\code{run_instat_calculation(calc, display = TRUE, param_list = list())}}{Run an Instat Calculation and Display Results}
+\item{\code{get_corresponding_link_columns(first_data_frame_name, first_data_frame_columns, second_data_frame_name)}}{Get Corresponding Link Columns}
+\item{\code{get_link_columns_from_data_frames(first_data_frame_name, first_data_frame_columns, second_data_frame_name, second_data_frame_columns)}}{Get Link Columns Between Data Frames}
+\item{\code{save_calc_output(calc, curr_data_list, previous_manipulations)}}{Save the Output of a Calculation}
+
+\item{\code{append_summaries_to_data_object(out, data_name, columns_to_summarise, summaries, factors = c(), summary_name, calc, calc_name = "")}}{Append Summaries to a Data Object}
+\item{\code{calculate_summary(data_name, columns_to_summarise = NULL, summaries, factors = c(), store_results = TRUE, drop = TRUE, return_output = FALSE, summary_name = NA, result_names = NULL, percentage_type = "none", perc_total_columns = NULL, perc_total_factors = c(), perc_total_filter = NULL, perc_decimal = FALSE, perc_return_all = FALSE, include_counts_with_percentage = FALSE, silent = FALSE, additional_filter, original_level = FALSE, signif_fig = 2, sep = "_", ...)}}{Calculate Summaries for a Data Object}
+\item{\code{summary(data_name, columns_to_summarise, summaries, factors = c(), store_results = FALSE, drop = FALSE, return_output = FALSE, summary_name = NA, add_cols = c(), filter_names = c(), ...)}}{Perform and Return Summaries for a Data Object}
+\item{\code{summary_table(data_name, columns_to_summarise = NULL, summaries, factors = c(), store_table = FALSE, store_results = FALSE, drop = TRUE, na.rm = FALSE, summary_name = NA, include_margins = FALSE, margins = "outer", return_output = FALSE, treat_columns_as_factor = FALSE, page_by = NULL, signif_fig = 2, na_display = "", na_level_display = "NA", weights = NULL, caption = NULL, result_names = NULL, percentage_type = "none", perc_total_columns = NULL, perc_total_factors = c(), perc_total_filter = NULL, perc_decimal = FALSE, include_counts_with_percentage = FALSE, margin_name = "(All)", additional_filter, ...)}}{Generate a Summary Table}
@export
}
-\seealso{
-\code{\link{DataSheet$save_calculation}}
-}
\section{Active bindings}{
\if{html}{\out{}}
\describe{
@@ -6586,6 +6583,7 @@ This object should include relevant parameters and metadata for the calculation.
\code{save_calculation} method to store the calculation.
\item The \code{calc} object typically includes details such as its \code{name}, \code{type}, and any parameters
or dependencies required to perform the calculation.
+\item See also \code{\link{DataSheet$save_calculation}}
}
}
diff --git a/man/DataSheet.Rd b/man/DataSheet.Rd
index 5c4e155..3f5362a 100644
--- a/man/DataSheet.Rd
+++ b/man/DataSheet.Rd
@@ -232,8 +232,8 @@ Merge New Data with Existing Data
\item{\code{save_calculation(calc)}}{Save a Calculation to the DataSheet.}
-\item{\code{merge_data(new_data, by = NULL, type = "left", match = "all")}{Merge New Data with Existing Data}}
-\item{\code{calculate_summary(calc, ...)}{Calculate Summaries for Specified Columns}}
+\item{\code{merge_data(new_data, by = NULL, type = "left", match = "all")}}{Merge New Data with Existing Data}
+\item{\code{calculate_summary(calc, ...)}}{Calculate Summaries for Specified Columns}
}
}