Count number of rows within each group

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))

Solution 1:

Current best practice (tidyverse) is:

require(dplyr)
df1 %>% count(Year, Month)

Solution 2:

Following @Joshua's suggestion, here's one way you might count the number of observations in your df dataframe where Year = 2007 and Month = Nov (assuming they are columns):

nrow(df[,df$YEAR == 2007 & df$Month == "Nov"])

and with aggregate, following @GregSnow:

aggregate(x ~ Year + Month, data = df, FUN = length)

Solution 3:

dplyr package does this with count/tally commands, or the n() function:

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()

Solution 4:

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)]