Group_by with multiple columns

Asked May 06 '23 at 16:27

Active May 06 '23 at 16:33

Viewed 34 times

I am trying to use dplyr to produce a summary table for 6 different combinations (group1 and group 2).

group1 <-c(TRUE, FALSE, FALSE, TRUE, TRUE, FALSE, TRUE, TRUE, FALSE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE, TRUE, TRUE, FALSE)
group2 <- c(1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3)
pop <- c( 5, 8, 6, 8, 4, 5, 9, 2, 4, 5, 8, 6, 8, 4, 5, 9, 2, 4)

df <- data.frame(group1, group2, pop)
df$group1 <- as.factor(group1)
df$group2 <- as.factor(group2)

Because I turned groups1 and 2 to factors, I was hoping I could use dplyr and do:

library(dplyr)
df %>% 
  group_by(group1, group2) %>%                     
  summarise(mean_pop = mean(pop))

However, I just get this:

  mean_pop
1 5.666667

What am I missing?

edited May 06 '23 at 16:33

Jon Spring

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asked May 06 '23 at 16:27

KT_1

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I'm guessing you have `plyr` loaded, which also has a `summarise` function. Is it resolved if you use `dplyr::summarise(mean_pop = mean(pop))` for your last line? – Jon Spring May 06 '23 at 16:34
See https://stackoverflow.com/a/22801295/6851825 – Jon Spring May 06 '23 at 17:46
```df %>% group_by(group1, group2) %>% dplyr::summarise(mean_pop = mean(pop))``` – M-- May 06 '23 at 19:46

Group_by with multiple columns

0 Answers0