Skip to content

docs: fix typos in GRP.Rd, BY.Rd, and collapse-package.Rd #863

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
LeonidasZhak wants to merge 1 commit into from
Closed

docs: fix typos in GRP.Rd, BY.Rd, and collapse-package.Rd #863

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion man/BY.Rd
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -84,7 +84,7 @@ ml
unlist2d(ml, idcols = "Variable", row.names = "Species")

## data.frame method
BY(num_vars(iris), g, sum) # Also returns a data.fram
BY(num_vars(iris), g, sum) # Also returns a data.frame
BY(num_vars(iris), g, sum, return = 2) # Return as matrix.. also works for computations below
head(BY(num_vars(iris), g, scale))
BY(num_vars(iris), g, fquantile)
Expand Down
2 changes: 1 addition & 1 deletion man/GRP.Rd
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -109,7 +109,7 @@ fungroup(X, \dots)

\item{return.order}{logical. If \code{sort = TRUE}, include the output from \code{\link{radixorder}} in the created GRP object. This brings performance improvements in \code{gsplit} (and thus also benefits grouped execution of base R functions). }

\item{method}{character. The algorithm to use for grouping: either \code{"radix"}, \code{"hash"} or \code{"auto"}. \code{"auto"} will chose \code{"radix"} when \code{sort = TRUE}, yielding ordered grouping via \code{\link{radixorder}}, and \code{"hash"}-based grouping in first-appearance order via \code{\link{group}} otherwise. It is possibly to put \code{method = "radix"} and \code{sort = FALSE}, which will group character data in first appearance order but sort numeric data (a good hybrid option). \code{method = "hash"} currently does not support any sorting, thus putting \code{sort = TRUE} will simply be ignored.}
\item{method}{character. The algorithm to use for grouping: either \code{"radix"}, \code{"hash"} or \code{"auto"}. \code{"auto"} will choose \code{"radix"} when \code{sort = TRUE}, yielding ordered grouping via \code{\link{radixorder}}, and \code{"hash"}-based grouping in first-appearance order via \code{\link{group}} otherwise. It is possible to put \code{method = "radix"} and \code{sort = FALSE}, which will group character data in first appearance order but sort numeric data (a good hybrid option). \code{method = "hash"} currently does not support any sorting, thus putting \code{sort = TRUE} will simply be ignored.}

\item{group.sizes}{logical. \code{TRUE} tabulates factor levels using \code{\link{tabulate}} to create a vector of group sizes; \code{FALSE} leaves that slot empty when converting from factors.}

Expand Down
4 changes: 2 additions & 2 deletions man/collapse-package.Rd
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -253,7 +253,7 @@ microbenchmark(TRA(mtcars, sds, "/"), sweep(mtcars, 2, sds, "/")) # A remarkable
sds <- fsd(mtcars, f2)
head(TRA(mtcars, sds, "/", f2)) # Groupd scaling (if sd's not needed: fsd(mtcars, f2, TRA = "/"))

# All functions above perserve the structure of matrices / data frames
# All functions above preserve the structure of matrices / data frames
# If conversions are required, use these efficient functions:
mtcarsM <- qM(mtcars) # Matrix from data.frame
head(qDF(mtcarsM)) # data.frame from matrix columns
Expand All @@ -264,7 +264,7 @@ head(qDT(mtcars, "cars")) # Same use a data.frame
## Now let's get some real data and see how we can use this power for data manipulation
head(wlddev) # World Bank World Development Data: 216 countries, 61 years, 5 series (columns 9-13)

# Starting with some discriptive tools...
# Starting with some descriptive tools...
namlab(wlddev, class = TRUE) # Show variable names, labels and classes
fnobs(wlddev) # Observation count
pwnobs(wlddev) # Pairwise observation count
Expand Down