Why does summarize or mutate not work with group_by when I load `plyr` after `dplyr`?

Question

Note: The title of this question has been edited to make it the canonical question for issues when plyr functions mask their dplyr counterparts. The rest of the question remains unchanged.

---

Suppose I have the following data:

dfx <- data.frame(
  group = c(rep('A', 8), rep('B', 15), rep('C', 6)),
  sex = sample(c("M", "F"), size = 29, replace = TRUE),
  age = runif(n = 29, min = 18, max = 54)
)

With the good old plyr I can create a little table summarizing my data with the following code:

require(plyr)
ddply(dfx, .(group, sex), summarize,
      mean = round(mean(age), 2),
      sd = round(sd(age), 2))

The output look like this:

  group sex  mean    sd
1     A   F 49.68  5.68
2     A   M 32.21  6.27
3     B   F 31.87  9.80
4     B   M 37.54  9.73
5     C   F 40.61 15.21
6     C   M 36.33 11.33

I'm trying to move my code to dplyr and the %>% operator. My code takes DF then group it by group and sex and then summarise it. That is:

dfx %>% group_by(group, sex) %>% 
  summarise(mean = round(mean(age), 2), sd = round(sd(age), 2))

But my output is:

  mean   sd
1 35.56 9.92

What am I doing wrong?

Answer 1

The problem here is that you are loading dplyr first and then plyr, so plyr's function summarise is masking dplyr's function summarise. When that happens you get this warning:

library(plyr)
    Loading required package: plyr
------------------------------------------------------------------------------------------
You have loaded plyr after dplyr - this is likely to cause problems.
If you need functions from both plyr and dplyr, please load plyr first, then dplyr:
library(plyr); library(dplyr)
------------------------------------------------------------------------------------------

Attaching package: ‘plyr’

The following objects are masked from ‘package:dplyr’:

    arrange, desc, failwith, id, mutate, summarise, summarize

So in order for your code to work, either detach plyr detach(package:plyr) or restart R and load plyr first and then dplyr (or load only dplyr):

library(dplyr)
dfx %>% group_by(group, sex) %>% 
  summarise(mean = round(mean(age), 2), sd = round(sd(age), 2))
Source: local data frame [6 x 4]
Groups: group

  group sex  mean    sd
1     A   F 41.51  8.24
2     A   M 32.23 11.85
3     B   F 38.79 11.93
4     B   M 31.00  7.92
5     C   F 24.97  7.46
6     C   M 36.17  9.11

Or you can explicitly call dplyr's summarise in your code, so the right function will be called no matter how you load the packages:

dfx %>% group_by(group, sex) %>% 
  dplyr::summarise(mean = round(mean(age), 2), sd = round(sd(age), 2))