Count number of rows within each group

Question

I have a dataframe and I would like to count the number of rows within each group. I reguarly use the aggregate function to sum data as follows:

df2 <- aggregate(x ~ Year + Month, data = df1, sum)

Now, I would like to count observations but can't seem to find the proper argument for FUN. Intuitively, I thought it would be as follows:

df2 <- aggregate(x ~ Year + Month, data = df1, count)

But, no such luck.

Any ideas?

---

Some toy data:

set.seed(2)
df1 <- data.frame(x = 1:20,
                  Year = sample(2012:2014, 20, replace = TRUE),
                  Month = sample(month.abb[1:3], 20, replace = TRUE))

Answer 1

Create a new variable Count with a value of 1 for each row:

df1["Count"] <-1

Then aggregate dataframe, summing by the Count column:

df2 <- aggregate(df1[c("Count")], by=list(year=df1$year, month=df1$month), FUN=sum, na.rm=TRUE)

Answer 2

We can also use dplyr.

First, some data:

df <- data.frame(x = rep(1:6, rep(c(1, 2, 3), 2)), year = 1993:2004, month = c(1, 1:11))

Now the count:

library(dplyr)
count(df, year, month)
#piping
df %>% count(year, month)

We can also use a slightly longer version with piping and the n() function:

df %>% 
  group_by(year, month) %>%
  summarise(number = n())

or the tally function:

df %>% 
  group_by(year, month) %>%
  tally()

Answer 3

There is also df2 <- count(x, c('Year','Month')) (plyr package)

Answer 4

For my aggregations I usually end up wanting to see mean and "how big is this group" (a.k.a. length). So this is my handy snippet for those occasions;

agg.mean <- aggregate(columnToMean ~ columnToAggregateOn1*columnToAggregateOn2, yourDataFrame, FUN="mean")
agg.count <- aggregate(columnToMean ~ columnToAggregateOn1*columnToAggregateOn2, yourDataFrame, FUN="length")
aggcount <- agg.count$columnToMean
agg <- cbind(aggcount, agg.mean)

Answer 5

You can use by functions as by(df1$Year, df1$Month, count) that will produce a list of needed aggregation.

The output will look like,

df1$Month: Feb
     x freq
1 2012    1
2 2013    1
3 2014    5
--------------------------------------------------------------- 
df1$Month: Jan
     x freq
1 2012    5
2 2013    2
--------------------------------------------------------------- 
df1$Month: Mar
     x freq
1 2012    1
2 2013    3
3 2014    2
> 

Answer 6

An old question without a data.table solution. So here goes...

Using .N

library(data.table)
DT <- data.table(df)
DT[, .N, by = list(year, month)]