[r] How to count how many values per level in a given factor?

I have a data.frame mydf with about 2500 rows. These rows correspond to 69 classes of objects in colum 1 mydf$V1, and I want to count how many rows per object class I have. I can get a factor of these classes with:

objectclasses = unique(factor(mydf$V1, exclude="1"));

What's the terse R way to count the rows per object class? If this were any other language I'd be traversing an array with a loop and keeping count but I'm new to R programming and am trying to take advantage of R's vectorised operations.

In case I just want to know how many unique factor levels exist in the data, I use:

length(unique(df$factorcolumn))

Use the package plyr with lapply to get frequencies for every value (level) and every variable (factor) in your data frame.

library(plyr)
lapply(df, count)

We can use summary on factor column:

summary(myDF$factorColumn)

One more approach would be to apply n() function which is counting the number of observations

library(dplyr)
library(magrittr)
data %>% 
  group_by(columnName) %>%
  summarise(Count = n())

Here 2 ways to do it:

set.seed(1)
tt <- sample(letters,100,rep=TRUE)

## using table
table(tt)
tt
a b c d e f g h i j k l m n o p q r s t u v w x y z 
2 3 3 3 2 4 6 1 6 5 6 4 7 2 2 2 5 4 5 3 8 4 5 4 3 1 
## using tapply
tapply(tt,tt,length)
a b c d e f g h i j k l m n o p q r s t u v w x y z 
2 3 3 3 2 4 6 1 6 5 6 4 7 2 2 2 5 4 5 3 8 4 5 4 3 1 

Using plyr package:

library(plyr)

count(mydf$V1)

It will return you a frequency of each value.

Using data.table

 library(data.table)
 setDT(dat)[, .N, keyby=ID] #(Using @Paul Hiemstra's `dat`)

Or using dplyr 0.3

 res <- count(dat, ID)
 head(res)
 #Source: local data frame [6 x 2]

 #  ID n
 #1  a 2
 #2  b 3
 #3  c 3
 #4  d 3
 #5  e 2
 #6  f 4

Or

  dat %>% 
      group_by(ID) %>% 
      tally()

Or

  dat %>% 
      group_by(ID) %>%
      summarise(n=n())