Basic summary functions

In this section, table() and aggregate() will be covered. They are basic processing functions that come in the base package.

• table(): This creates a contingency table with the specified vectors. Although its output is of the table type, it works similar to an array:

  sample.data <-data.frame(var1 =rep(c("Male","Female"),10), var2 =rep(c("A","B","C","D")))
  example.table<-table(sample.data$var1, sample.data$var2)
  example.table
  ##         
  ##          A B C D
  ##   Female 0 5 0 5
  ##   Male   5 0 5 0
  example.table[2,2]
  ## [1] 0
  

  The output of table() can be indexed in the same way as an array.

• aggregate(): This performs one or more functions over a vector split by a factor variable. aggregate() has basically two ways of usage:

  • With vectors: One or more vectors are passed to the x argument while one or more factor vectors are passed in the by argument. FUN is the aggregation function to be used:

    > data(iris)
    > aggregate(iris$Sepal.Length, by=list(iris$Species...