Week 5 Lab Practice

{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE)

### LECTURE 5 - LAB PRACTICE ###
### VALLI SUPPRAMANIAM (17053409) ###

# 1. Create a dataframe called mydata

mydata <- data.frame (
  v1 = c(49,80,79,41,41,52,28,8,76,8),
  v2 = c(95,46,3,100,1,59,65,82,17,20),
  v3 = c(32,96,48,96,61,54,36,18,73,67),
  v4 = c(11,56,96,48,47,84,5,84,47,16),
  v5 = c(21,41,73,47,6,20,69,77,26,79),
  v6 = c(3,46,90,42,89,48,78,82,16,65),
  gender = c("F","F","M","F","M","M","F","M","M","F"),
  age = c(82,2,64,93,28,28,71,68,46,1)
)


# 2. Create newdata

myvars <-c("v1", "v2", "v3")
newdata <-mydata[myvars]
newdata

# datakeep <-mydata (sample code to keep mydata)


# 3. Create and keep newdata1

myvars1 <- names(mydata) %in% c("v4","v5", "v6", "gender", "age")
newdata1 <- mydata[myvars1]
newdata1

datakeep <-newdata1


# 4. Exclude column 3 and 5 from mydata and keep in newdata2

newdata2 <- mydata[c(-3,-5)]
newdata2


# 5. Remove the same columns using NULL value

newdata3 <-mydata
newdata3$v3 <- newdata3$v5 <- NULL
newdata3


# 6. Data for newdata5 and newdataGA

newdata5 <- mydata[1:5,]
newdata5

newdataGA <- mydata[ which(mydata$gender=="F" & mydata$age >65),]
newdataGA