updating demo notebook

NAMESPACE

@@ -18,7 +18,3 @@ export(acro_rename_output)
 export(acro_summarise)
 export(acro_surv_func)
 export(acro_table)
-export(create_factors)
-export(is_excluded)
-export(is_invalid)
-export(to_pandas_categorical)

NEWS.md

@@ -1,3 +1,7 @@
+# acro 0.1.8
+* Added extended support to `acro_table()` to include all parameters from the base R `table()` function.
+* Added additional parameters to `acro_crosstab()`.
+* Introduced `acro_summarise()`, an ACRO wrapper for the tidyverse `summarise()` function.
 
 # acro 0.1.7
 * Added support for installation via conda

R/acro_tables.R

@@ -167,6 +167,8 @@ acro_table <- function(index, columns, dnn = NULL, deparse.level = 0, useNA = "n
   return(table)
 }
 
+#' Create a summary data frame
+#'
 #' Creates a new data frame. It returns one row for each combination of grouping variables; if there are no grouping variables, the output will have a single row summarising all observations in the input
 #'
 #' @param .data A data frame or a data frame extension

R/utils.R

@@ -3,7 +3,7 @@
 #' @param Values to check for empty values in it
 #'
 #' @returns logical vector that shows the places of the empty values
-#' @export
+#' @noRd
 
 is_invalid <- function(Values) {
   # Check for NA or NaN in the object
@@ -16,7 +16,7 @@ is_invalid <- function(Values) {
 #' @param exclude_list Items to exclude from the values
 #'
 #' @returns logical vector that shows the places of the items that needs to be excluded
-#' @export
+#' @noRd
 
 is_excluded <- function(Values, exclude_list) {
   # Catch everything in the exclude list
@@ -43,7 +43,7 @@ is_excluded <- function(Values, exclude_list) {
 #' @param useNA  whether to include NA values in the table
 #'
 #' @returns R vector factor
-#' @export
+#' @noRd
 
 create_factors <- function(Values, useNA) {
   # Check for NAs
@@ -68,7 +68,7 @@ create_factors <- function(Values, useNA) {
 #' @param pd Reference to the Python `pandas` module
 #'
 #' @returns A Python `pandas.Categorical` object
-#' @export
+#' @noRd
 
 to_pandas_categorical <- function(Values, pd) {
   # Build the Pandas Categorical

inst/WORDLIST

@@ -2,36 +2,54 @@ ADR
 Acknowledgement
 Analytics
 Conda
+Crosstab
 EPSRC
 GRAIMATTER
 HDR
 Initialise
 Karnofsky
 MRC
 MyBinder
+OpenML
 RStudio
 SACRO
 SDC
+Summarise
+TRE
+TRE's
 TREs
 TREvolution
 Transformative
 Xplore
 analytics
 auditable
+checksums
 codecov
+coloured
 conda
 crosstab
+csv
 disclosive
+finalise
+finalising
 github
 https
+initialise
 initialised
 json
 numpy
 openml
 pre
+prioritise
 programme
+recognise
+reimplement
 scipy
+statsmodels
+summarise
 summarising
+tidyverse
+toolchain
 www
 xlsx
 yaml