## File: activate.Rd

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r-cran-tidygraph 1.2.0-1
 1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556 % Generated by roxygen2: do not edit by hand % Please edit documentation in R/activate.R \name{activate} \alias{activate} \alias{active} \alias{\%N>\%} \alias{\%E>\%} \title{Determine the context of subsequent manipulations} \usage{ activate(.data, what) active(x) lhs \%N>\% rhs lhs \%E>\% rhs } \arguments{ \item{.data, x, lhs}{A tbl_graph or a grouped_tbl_graph} \item{what}{What should get activated? Possible values are \code{nodes} or \code{edges}.} \item{rhs}{A function to pipe into} } \value{ A tbl_graph } \description{ As a \link{tbl_graph} can be considered as a collection of two linked tables it is necessary to specify which table is referenced during manipulations. The \code{activate} verb does just that and needs affects all subsequent manipulations until a new table is activated. \code{active} is a simple query function to get the currently acitve context. In addition to the use of \code{activate} it is also possible to activate nodes or edges as part of the piping using the \verb{\%N>\%} and \verb{\%E>\%} pipes respectively. Do note that this approach somewhat obscures what is going on and is thus only recommended for quick, one-line, fixes in interactive use. } \note{ Activate will ungroup a grouped_tbl_graph. } \examples{ gr <- create_complete(5) \%>\% activate(nodes) \%>\% mutate(class = sample(c('a', 'b'), 5, TRUE)) \%>\% activate(edges) \%>\% arrange(from) # The above could be achieved using the special pipes as well gr <- create_complete(5) \%N>\% mutate(class = sample(c('a', 'b'), 5, TRUE)) \%E>\% arrange(from) # But as you can see it obscures what part of the graph is being targeted }