8/27/2021
53

The Tapply-Thompson Community Center program began in 1946 through the vision and hard work of A.B. Thompson and “Wink” Tapply who understood the importance of providing a safe and nurturing environment in which children and families could participate in recreational activities. Stg.interestingthings.com — Featured in Old Things By Jennifer Billock Apr 8, 2020 By Ariel Wodarcyk Mar 27, 2020 By Steve Spears Mar 24, 2020 By H.G. Tapply Oct 25, 2019 By Seth Richards Oct 25, 2019. When FUN is present, tapply calls FUN for each cell that has any data in it. If FUN returns a single atomic value for each cell (e.g., functions mean or var) and when simplify is TRUE, tapply returns a multi-way array containing the values. Dec 06, 2019 tapply()函数.

  1. Tapply Function In R
  2. William Tapply Brady Coyne Series
  3. R Aggregate Vs Tapply
  4. Tapply Fun
  5. Tapply Function
  6. Tapply Function R

Long beaches, dramatic coloured-sand cliffs, natural sandblows, rocky headlands and pristine freshwater lakes and streams are some of K'gari's (Fraser Island’s) spectacular natural features.

Tapply Function In R

R Programming

  • R Data Structures
    • Vectors
  • Reading and Writing Data to and from R
  • Control Structure
  • Loop Functions
  • Data Frames and dplyr Package

tapply in R

Apply a function to each cell of a ragged array, that is to each (non-empty) group of values given by a unique combination of the levels of certain factors. Basically, tapply() applies a function or operation on subset of the vector broken down by a given factor variable.

To understand clearly lets imagine you have height of 1000 people ( 500 male and 500 females), and you want to know the average height of males and females from this sample data. To deal with this problem you can group height by the gender, height of 500 males, and height of 500 females, and later calculate the average height for males and females.

To get the help file type the following code.

?tapply

To see the arguments of tapply() function type str(tapply) in the console.

str(tapply)

Output:

function (X, INDEX, FUN = NULL, …, default = NA, simplify = TRUE)

  1. INDEX is a factor or a list of factors (or else they are coerced to factors)
  2. FUN is a function to be applied
  3. … contains other arguments to be passed FUN
  4. simplify, should we simplify the result or not?
Tapply

Example:

x<-runif(20, min=155, max=180) #simulate 20 random heights
y<-gl(2, 10, labels = c('Male', 'Female')) #Generate factors by specifying the pattern of their levels.
tapply(x, y, mean)

Output:

Male Female
168.4516 163.8848

Tapply

Example 2:

Tapply list

There are already some built-in datasets are available in R. Here we will use mtcars dataset. You can always get the help file by typing ?mtcars. We are interested in seeing the avg mpg for the various transmission types and number of cylinders in car. This is nothing but avg mpg grouped by transmission type and the number of cylinders in car.

?mtcars
data(mtcars)
str(mtcars)

How do i find my ip address. Output:

‘data.frame’: 32 obs. of 11 variables:
$ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 …
$ cyl : num 6 6 4 6 8 6 8 4 4 6 …
$ disp: num 160 160 108 258 360 …
$ hp : num 110 110 93 110 175 105 245 62 95 123 …
$ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 …
$ wt : num 2.62 2.88 2.32 3.21 3.44 …
$ qsec: num 16.5 17 18.6 19.4 17 …
$ vs : num 0 0 1 1 0 1 0 1 1 1 …
$ am : num 1 1 1 0 0 0 0 0 0 0 …
$ gear: num 4 4 4 3 3 3 3 4 4 4 …
$ carb: num 4 4 1 1 2 1 4 2 2 4 …

tapply(mtcars$mpg, list(mtcars$cyl, mtcars$am), mean)

Output:

0 1
4 22.900 28.07500
6 19.125 20.56667
8 15.050 15.40000

Example 3:

William Tapply Brady Coyne Series

Now another example will be shown using iris data set. Check the structure of the data set using str(iris). we want to calculate the mean of the Sepal Length for each Species.

?iris
data(iris)
str(iris)

Output:

‘data.frame’: 150 obs. of 5 variables:
$ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 …
$ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 …
$ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 …
$ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 …
$ Species : Factor w/ 3 levels “setosa”,”versicolor”,.: 1 1 1 1 1 1 1 1 1 1 …

tapply(iris$Sepal.Length, iris$Species, mean)

Output:

setosa versicolor virginica
5.006 5.936 6.588

R Aggregate Vs Tapply

Similarly, you can calculate the mean of the Petal Length for each Species.

Tapply Fun

tapply(iris$Petal.Length, iris$Species, mean)

Tapply Function

Output:

Tapply Function R

setosa versicolor virginica
1.462 4.260 5.552