Use function in groupby with variable column name in R using dplyr [duplicate]

Question

I have a dataframe:

df <- data.frame(Category = c(rep("A", 3), rep("B", 3)), Value = rnorm(6))
df
 Category       Value
1        A -0.94968814
2        A  2.56687061
3        A -0.15665153
4        B -0.47647105
5        B  0.83015076
6        B -0.03744522

Now I want to add another column which is the mean per Category. This can be done with the dplyr package really easy:

df %>% group_by(Category) %>% 
  summarize(mean = mean(Value))

Now in piece of code my problem is: I can't use mean(Value), but I have a variable name that knows the column name: columnName = "Value" But this unfortunately won't work:

columnName = "Value"

df %>% group_by(Category) %>% 
  summarize(mean = mean(columnName))

Warning messages: 1: In mean.default("Value") : argument is not numeric or logical: returning NA 2: In mean.default("Value") :
argument is not numeric or logical: returning NA

How can I pass the column name with the variable?

mean(df[,columnName]) this code worked for me, when using the same variables as you did. — Benjamin Mohn
– Benjamin Mohn, Commented Dec 21, 2016 at 10:06
No, that doesn't work. It has to be mean of the groups, not the mean of the column. — user2874583
– user2874583, Commented Dec 21, 2016 at 10:08
It is not using the package dplyr but it works like this: tapply(df[,columnName],df$Category, mean) — Benjamin Mohn
– Benjamin Mohn, Commented Dec 21, 2016 at 10:14
please use set.seed when using such functions as rnorm to create data frames so we can double check results — Sotos
– Sotos, Commented Dec 21, 2016 at 10:16
This is called standard evaluation. There hundreds are of dupes regarding this on SO. Please read vignette("nse"). One way to achieve this is library(lazyeval) ; dots <- interp(~ mean(columnName), columnName = as.name("Value")) ; df %>% group_by(Category) %>% summarise_(.dots = dots) — David Arenburg
– David Arenburg, Commented Dec 21, 2016 at 10:17

Ronak Shah · Accepted Answer · 2016-12-21 10:10:58Z

2

We can use get with aggregate

aggregate(get(columnName)~Category, df, mean)

#    Category get(columnName)
#1        A      -0.5490751
#2        B      -0.2594670

answered Dec 21, 2016 at 10:10

Ronak Shah

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1 Comment

user2874583 Over a year ago

This works thanks! But I was looking for a solution within the dplyr package. Do you know if that is possible too?

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