How do i subtract 2 columns in a .csv file in R? - r

Question

How to subtract 2 colmun in a .csv file uploaded in R?
I have named the new column using reading <- $started_time- $ended_time

Answer 1

Since you do not post any example data I post an example based on the iris built-in dataset: You can simply use - to subtract vector of the same length (if the length is not the same the shorter vector will be recycled).
You can select the column from your dataset with the $ operator or with [] operator
data(iris)
#assigning the result to a new column
iris$subtraction <- iris$Sepal.Length-iris$Sepal.Width
iris$subtraction <- iris[,1]-iris[,2]
#assigning the result to a new variable
subtraction <- iris[,1]-iris[,2]
subtraction <- iris$Sepal.Length-iris$Sepal.Width
EDIT
a mincrobenchmark of 3 equivalent solutions:
library(microbenchmark)
library(data.table)
library(dplyr)
library(ggplot2)
#prepare simulation ------------------------------------------------------------
#number of rows to be tested
nr <- seq(100000,10000000,100000)
#initialize an list to store results
time <- as.list(rep(NA,100))
#benchmark
for (i in 1:length(nr)) {
set.seed(5)
#create data
df <- data.frame(x=rnorm(nr[i]),y=rnorm(nr[i]))
dt <- data.table(x=rnorm(nr[i]),y=rnorm(nr[i]))
#benchmark
x <- print(microbenchmark(
base=df$new.col <- df$x-df$y,
DT=dt <- dt[,new.col:=x-y],
dplyr=df %>% mutate(new.col=x-y),
times = 10
))
#store results
time[[i]] <- x[,c(1,4)]
}
#discard the first 4 elements because they run in microsenconds
bench <- do.call(rbind,time[5:100])
#add the number of rows as column
bench$nrow <- rep(nr[5:100],each=3)
ggplot(bench,aes(x=nrow,y=mean,group=expr,col=expr))+
geom_smooth(se=F)+
theme_minimal()+
xlab("# rows")+
ylab("time (milliseconds)")
As you can see, for this simple task both the base and data.table solutions are equivalent, while the mutate solution is a bit slower. However, the entire simulation runs in a minute and the single operations in few milliseconds.
my PC has 16Gb RAM and 12 cores.
EDIT
After the OP asked for a Date case, here a small example with date as POSIXct class:
day <- Sys.Date()
hm <- merge(0:23, seq(0, 45, by = 15))
datetime <- merge(last7days, chron(time = paste(hm$x, ':', hm$y, ':', 0)))
colnames(datetime) <- c('date', 'time')
# create datetime
dt <- as.POSIXct(paste(datetime$date, datetime$time))
df <- data.frame(x=sample(dt,200000,replace = T),y=sample(dt,200000,replace = T))
microbenchmark(df$x-df$y)
the operation runs in a few milliseconds, as expected:
Unit: milliseconds
expr min lq mean median uq max neval
df$x - df$y 1.459801 1.544301 2.755227 1.624501 1.845401 62.7416 100