How does one stop using rowwise in dplyr?

RDplyr

R Problem Overview


So, if one wishes to apply an operation row by row in dplyr, one can use the rowwise function, for example: https://stackoverflow.com/questions/21818181/applying-a-function-to-every-row-of-a-table-using-dplyr/24728107#24728107

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?

R Solutions


Solution 1 - R

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][1], 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.

[1]: http://ungroup.rowwise_df%20%3C-%20function(x)%20%7B%20%20%20class(x)%20%3C-%20c( "tbl_dfquot;, quot;data.framequot;) x } quot;"

Solution 2 - R

Just use ungroup()

The following produces a warning:

data.frame(a=1:4) %>% rowwise() %>% 
  group_by(a)
#Warning message:
#Grouping rowwise data frame strips rowwise nature

This does not produce the warning:

data.frame(a=1:4) %>% rowwise() %>% 
  ungroup() %>% 
  group_by(a)

Solution 3 - R

You can use as.data.frame(), like below

> data.frame(a=1:4) %>% rowwise() %>% group_by(a)
# A tibble: 4 x 1
# Groups:   a [4]
      a
* <int>
1     1
2     2
3     3
4     4
Warning message:
Grouping rowwise data frame strips rowwise nature 

> data.frame(a=1:4) %>% rowwise() %>% as.data.frame() %>% group_by(a)
# A tibble: 4 x 1
# Groups:   a [4]
      a
* <int>
1     1
2     2
3     3
4     4

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Content TypeOriginal AuthorOriginal Content on Stackoverflow
QuestionAlexView Question on Stackoverflow
Solution 1 - RAlexView Answer on Stackoverflow
Solution 2 - RRtistView Answer on Stackoverflow
Solution 3 - RishonestView Answer on Stackoverflow