UC Business Analytics R Programming Guide

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tapply Function

tapply() is used to apply a function over subsets of a vector. It is primarily used when we have the following circumstances:

  1. A dataset that can be broken up into groups (via categorical variables - aka factors)
  2. We desire to break the dataset up into groups
  3. Within each group, we want to apply a function

The arguments to tapply() are as follows:

  • x is a vector
  • INDEX is a factor or a list of factors (or else they are coerced to factors)
  • FUN is a function to be applied
  • ... contains other arguments to be passed FUN
  • simplify, should we simplify the result?
# syntax of tapply function
tapply(x, INDEX, FUN, ..., simplify = TRUE)

To provide an example we’ll use the built in mtcars dataset and calculate the mean of the mpg variable grouped by the cyl variable.

# show first few rows of mtcars
head(mtcars)
##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

# get the mean of the mpg column grouped by cylinders 
tapply(mtcars$mpg, mtcars$cyl, mean)
##        4        6        8 
## 26.66364 19.74286 15.10000

Now let’s say you want to calculate the mean for each column in the mtcars dataset grouped by the cylinder categorical variable. To do this you can embed the tapply function within the apply function.

# get the mean of all columns grouped by cylinders 
apply(mtcars, 2, function(x) tapply(x, mtcars$cyl, mean))
##        mpg cyl     disp        hp     drat       wt     qsec        vs
## 4 26.66364   4 105.1364  82.63636 4.070909 2.285727 19.13727 0.9090909
## 6 19.74286   6 183.3143 122.28571 3.585714 3.117143 17.97714 0.5714286
## 8 15.10000   8 353.1000 209.21429 3.229286 3.999214 16.77214 0.0000000
##          am     gear     carb
## 4 0.7272727 4.090909 1.545455
## 6 0.4285714 3.857143 3.428571
## 8 0.1428571 3.285714 3.500000