tApply and by command in R
This page is based on Mike Marin’s Statslectures video ’tApply Function in R‘ and …. It is part of ‘My notes on R programming’ on my site: https://dataz4s.com/
The tApply and the by commands can be used to apply a function to a subset of a vector or a variable.
# Read in data via read_excel
library(readxl)
LungCapData <- read_excel("C:/Users/Usuario/Documents/dataZ4s/R/MarinLectures/LungCapData.xlsx",
col_types = c("numeric", "numeric", "numeric",
"text", "text", "text"))
# R reads in Smoke, Gender and Caesarean as "text". Needs change to "factor"
# Change Smoke, Gender and Caesarean to factors with as.factor() command
LungCapData$Smoke <- as.factor(LungCapData$Smoke)
LungCapData$Gender <- as.factor(LungCapData$Gender)
LungCapData$Caesarean <- as.factor(LungCapData$Caesarean)
# Checking the data and attaching the dataset
summary(LungCapData)## LungCap Age Height Smoke Gender
## Min. : 0.507 Min. : 3.00 Min. :45.30 no :648 female:358
## 1st Qu.: 6.150 1st Qu.: 9.00 1st Qu.:59.90 yes: 77 male :367
## Median : 8.000 Median :13.00 Median :65.40
## Mean : 7.863 Mean :12.33 Mean :64.84
## 3rd Qu.: 9.800 3rd Qu.:15.00 3rd Qu.:70.30
## Max. :14.675 Max. :19.00 Max. :81.80
## Caesarean
## no :561
## yes:164
##
##
##
## # and attach it
attach(LungCapData)# Subsetting using [ ], can get us the result
mean(Age[Smoke=="no"])## [1] 12.03549mean(Age[Smoke=="yes"])## [1] 14.77922# But the "tapply" is more efficient:
# Age is the variable to apply the mean command to
# Subsetting data with the INDEX command as to status of smoking
# The FUN=mean and we remove NA values with na.rm command
tapply(X=Age, INDEX=Smoke, FUN=mean, na.rm=T)## no yes
## 12.03549 14.77922# Saving in object
m <- tapply(X=Age, INDEX=Smoke, FUN=mean, na.rm=T)# 'simplify' argument is TRUE be default
# When set to "FALSE" the results from above are returned in list format
tapply(X=Age, INDEX=Smoke, FUN=mean, simplify=FALSE)## $no
## [1] 12.03549
##
## $yes
## [1] 14.77922# Using "quantile" function to Age and Smoke
tapply(Age, Smoke, quantile, probs=c(0.2, 0.8))## $no
## 20% 80%
## 8 16
##
## $yes
## 20% 80%
## 12 17# Using the "summary" commandfor smokers and non-smokers
tapply(X=Age, INDEX=Smoke, FUN=summary)## $no
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 3.00 9.00 12.00 12.04 15.00 19.00
##
## $yes
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 10.00 13.00 15.00 14.78 17.00 19.00# we can "subset" based on multiple variables/vectors
# calculate the mean Age for Smoker/NonSmoker and male/female
tapply(X=Age, INDEX=list(Smoke, Gender), FUN=mean, na.rm=T)## female male
## no 12.12739 11.94910
## yes 14.75000 14.81818# Calculating mean age for smokers and non-smokers as per gender
# We are subsetting Smoke and Gender
tapply(X=Age, INDEX=list(Smoke, Gender), mean, na.rm=T)## female male
## no 12.12739 11.94910
## yes 14.75000 14.81818# Subsetting with [], can do the same but less efficiently
mean(Age[Smoke=="no" & Gender=="female"])## [1] 12.12739mean(Age[Smoke=="no" & Gender=="male"])## [1] 11.9491mean(Age[Smoke=="yes" & Gender=="female"])## [1] 14.75mean(Age[Smoke=="yes" & Gender=="male"])## [1] 14.81818# The "by" command does the same as the "tapply" command, but...
# ... returns the result are returned similar to a vector format
by(Age, list(Smoke, Gender), mean, na.rm=T)## : no
## : female
## [1] 12.12739
## ------------------------------------------------------------
## : yes
## : female
## [1] 14.75
## ------------------------------------------------------------
## : no
## : male
## [1] 11.9491
## ------------------------------------------------------------
## : yes
## : male
## [1] 14.81818# Subsetting with "by"
temp <- by(Age, list(Smoke, Gender), mean, na.rm=T)
temp## : no
## : female
## [1] 12.12739
## ------------------------------------------------------------
## : yes
## : female
## [1] 14.75
## ------------------------------------------------------------
## : no
## : male
## [1] 11.9491
## ------------------------------------------------------------
## : yes
## : male
## [1] 14.81818temp[4]## [1] 14.81818# Converting to a vector
c(temp)## [1] 12.12739 14.75000 11.94910 14.81818temp2 <- c(temp)
temp2## [1] 12.12739 14.75000 11.94910 14.81818# Checking it's class
class(temp2)## [1] "numeric"View this content on my page: https://dataz4s.com/r-statistical-programming/tapply-by-command-r/