So, if one wishes to apply an operation row by row in dplyr, one can use the rowwise
function, for example: Applying a function to every row of a table using dplyr?
Is there a unrowwise
function which you can use to stop doing operations row by row? Currently, it seems adding a group_by
after the rowwise
removes row operations, e.g.
data.frame(a=1:4) %>% rowwise() %>% group_by(a) # ... # Warning message: # Grouping rowwise data frame strips rowwise nature
Does this mean one should use group_by(1)
if you wish to explicitly remove rowwise
?
rowwise() allows you to compute on a data frame a row-at-a-time. This is most useful when a vectorised function doesn't exist. Most dplyr verbs preserve row-wise grouping.
rowwise() is just a special form of grouping, so if you want to remove it from a data frame, just call ungroup() .
Syntax: mutate(new-col-name = rowSums(.)) The rowSums() method is used to calculate the sum of each row and then append the value at the end of each row under the new column name specified. The argument . is used to apply the function over all the cells of the data frame.
rowwise (not comparable) By rows; one row at a time.
As found in the comments and the other answer, the correct way of doing this is to use ungroup()
.
The operation rowwise(df)
sets one of the classes of df
to be rowwise_df
. We can see the methods on this class by examining the code here, which gives the following ungroup
method:
#' @export ungroup.rowwise_df <- function(x) { class(x) <- c( "tbl_df", "data.frame") x }
So we see that ungroup
is not strictly removing a grouped structure, instead it just removes the rowwise_df
class added from the rowwise
function.
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