Using dplyr to summarize by multiple groups - r

Question

I'm trying to use dplyr to summarize a dataset based on 2 groups: "year" and "area". This is how the dataset looks like:
Year Area Num
1 2000 Area 1 99
2 2001 Area 3 85
3 2000 Area 1 60
4 2003 Area 2 90
5 2002 Area 1 40
6 2002 Area 3 30
7 2004 Area 4 10
...
The end result should look something like this:
Year Area Mean
1 2000 Area 1 100
2 2000 Area 2 80
3 2000 Area 3 89
4 2001 Area 1 80
5 2001 Area 2 85
6 2001 Area 3 59
7 2002 Area 1 90
8 2002 Area 2 88
...
Excuse the values for "mean", they're made up.
The code for the example dataset:
df <- structure(list(
Year = c(2000, 2001, 2000, 2003, 2002, 2002, 2004),
Area = structure(c(1L, 3L, 1L, 2L, 1L, 3L, 4L),
.Label = c("Area 1", "Area 2", "Area 3", "Area 4"),
class = "factor"),
Num = structure(c(7L, 5L, 4L, 6L, 3L, 2L, 1L),
.Label = c("10", "30", "40", "60", "85", "90", "99"),
class = "factor")),
.Names = c("Year", "Area", "Num"),
class = "data.frame", row.names = c(NA, -7L))
df$Num <- as.numeric(df$Num)
Things I've tried:
df.meanYear <- df %>%
group_by(Year) %>%
group_by(Area) %>%
summarize_each(funs(mean(Num)))
But it just replaces every value with the mean, instead of the intended result.
If possible please do provide alternate means (i.e. non-dplyr) methods, because I'm still new with R.

Answer 1

Is this what you are looking for?
library(dplyr)
df <- group_by(df, Year, Area)
df <- summarise(df, avg = mean(Num))

Answer 2

We can use data.table
library(data.table)
setDT(df)[, .(avg = mean(Num)) , by = .(Year, Area)]

Answer 3

I had a similar problem in my code, I fixed it with the .groups attribute:
df %>%
group_by(Year,Area) %>%
summarise(avg = mean(Num), .groups="keep")
Also verified with the added example (as.numeric corrupted Num values, so I used as.numeric(as.character(df$Num)) to fix it):
Year Area avg
<dbl> <fct> <dbl>
1 2000 Area 1 79.5
2 2001 Area 3 85
3 2002 Area 1 40
4 2002 Area 3 30
5 2003 Area 2 90
6 2004 Area 4 10