Disclaimer: This is a question regarding an assignment for a Coursera course.
I'm having trouble coming up with a way to create a new column that differentiates between weekdays and weekends in my data set. I'm using a nested if/else statement within a for loop. The problem is the output makes every row 'weekday'. Does anyone see something glaringly wrong with my code? My end goal is to create a new factor variable that is either "weekend" or "weekday."
df4 <- mutate(df4, day = weekdays(df4$date))
for (i in df4$day) {
if(i %in% c("Saturday",'Sunday')) {
df4$day_type <- 'weekend'
} else {
df4$day_type <- 'weekday'
}
}
I modify a little bit of your code .(see below)
for (i in 1 : dim(df4)[1]) {
if(df4$day[i] %in% c('Saturday','Sunday')) {
df4$day_type[i] <- 'weekend'
} else {
df4$day_type[i] <- 'weekday'
}
}
Related
I am trying to read.csv a series of file named ("year".csv) from year 2005 to 2007 and writing into database.
However the loop command only consist of "2007L" for element "i" and only read 2007.csv into the dataframe.
Any ideas on how to resolve the issue ?
for(i in c(2005:2007)){
ontime<-read.csv(paste0(i,".csv"), header=TRUE)}
if(i == 2005){
dbWriteTable(conn,"ontimet",ontimet)
} else {
dbWriteTable(conn,"ontimet",ontimet, append= TRUE)
}
}
Something like this might be what you need. I think you just need to assign variables and append in the right place.
You probably need is like this. It produces all three years (or in your case, it would be csv's)
tmp = NULL
for(i in c(2005:2007)){
if(i == 2005){
tmp = append(tmp, i)
} else {
tmp = append(tmp, i)
print(tmp)
}
}
enter image description here
I know there exists function 'unique' which works similar to what I want to make, but I want to make this function.
I want this function finally returns 'result' which contains unique elements of input vector.
But I don't know why this function's result is totally different from my expect.
Why c which is to combine before result and new unique element is not working.
Please tell me how to fix my code.
Thank you.
I think what you expect might be something like below, where result should be an argument of m_uni:
m_uni <- function(x,result = c()) {
if (class(x)=='numeric'| class(x)=='character') {
if (length(x) <= 1){
return(result)
} else {
if (x[length(x)] %in% result) {
x <- x[-length(x)]
m_uni(x,result)
} else {
result <- c(result,x[length(x)])
x <- x[-length(x)]
m_uni(x,result)
}
}
} else {
return('This function only gets numeric or character vector')
}
}
such that
> m_uni(x)
[1] 0 4 5 -2
I'm trying to assign the 'date' of the previous case to a new variable call "LastTripDate", as long as the IDs are the same.
The "datetime" variable has is of class POSIXlc and has the form (%Y-%M-%D %h:%m:%s). Unfortunately my loop below only returns the seconds, not the whole information.
for (i in 2:length(All1[,1]))
{
if(as.numeric(All1$ID[i] == All1$ID[i-1]))
{
All1$LastTripDate1[i] <- as.Date.character(All1$datetime[i-1])
}
else {
All1$LastTripDate[i] == '100'}
}
Thanks!
I have a clunky block of shiny code on server.R side that I feel R syntax ought to allow me make one or two lines and simultaneously more flexible with some kind of lapply or do.call line
if(input$parVary == "area" && as.numeric(input$nTraces) > 3 )
{
area <- c(input$area, input$area2, input$area3, input$area4)
} else if(input$parVary == "area" && as.numeric(input$nTraces) > 2 )
{
area <- c(input$area, input$area2, input$area3)
} else if(input$parVary == "area" && as.numeric(input$nTraces) > 1 )
{
area <- c(input$area, input$area2)
} else
{
area <- input$area
}
But I have spent a day and about a billion different combos of lapply, do.calls, reactive, get, c, and observes around
paste0('input$area', 1:as.numeric(input$nTraces))
I just can't seem to find the right combination or figure out the reactive concept I'm missing. It -seems- to be related to the code not ever including individual input$area1, input$area2, etc... explicit text anywhere in the code?
I spoke a little too soon in comment above. My specific code ended up needing conditional to handle the list versus single value case. But #NicE answer is one I was looking for. Five sections like
if(input$parVary == "area" && as.numeric(input$nTraces) > 1 )
{
area <- lapply(paste0("area",1:as.numeric(input$nTraces)),function(x) input[[x]])
} else
{
area <- input$area1
}
teamed with later
mySolution <- list()
if(input$nTraces =='1')
{
mySolution <- solveCalc(dat=dat,tox=tox,area=area,temp=temp,model=modelIn)
} else
{
mySolution <- switch(input$parVary,
"model" = lapply(modelIn,solveCalc,dat=dat,tox=tox,area=area,temp=temp),
"temp" = lapply(temp,solveCalc,dat=dat,tox=tox,area=area,model=modelIn),
"tox" = lapply(tox,solveCalc,dat=dat,temp=temp,area=area,model=modelIn),
"Vt" = lapply(dat,solveCalc,tox=tox,temp=temp,area=area,model=modelIn),
"area" = lapply(area,solveCalc,dat=dat,tox=tox,temp=temp,model=modelIn)
)
}
Got me just what I wanted.
I am trying to eliminate all rows in excel that have he following features:
First column is an integer
Second column begins with an integer
Third column is empty
The code I have written appears to run indefinitely. CAS.MULT is the name of my dataframe.
for (i in 1:nrow(CAS.MULT)) {
testInteger <- function(x) {
test <- all.equal(x, as.integer(x), check.attributes = FALSE)
if (test == TRUE) {
return (TRUE)
}
else {
return (FALSE)
}
}
if (testInteger(as.integer(CAS.MULT[i,1])) == TRUE) {
if (testInteger(as.integer(substring(CAS.MULT[i,2],1,1))) == TRUE) {
if (CAS.MULT[i,3] == '') {
CAS.MULT <- data.frame(CAS.MULT[-i,])
}
}
}
}
You should be very wary of deleting rows within a for loop, if often leads to undesired behavior. There are a number of ways you could handle this. For instance, you can flag the rows for deletion and then delete them after.
Another thing I noticed is that you are converting your columns to integers before passing them to your function to test if they are integers, so you will be incorrectly returning true for all values passed to the function.
Maybe something like this would work (without a reproducible example it's hard to say if it will work or not):
toDelete <- numeric(0)
for (i in 1:nrow(CAS.MULT)) {
testInteger <- function(x) {
test <- all.equal(x, as.integer(x), check.attributes = FALSE)
if (test == TRUE) {
return (TRUE)
}
else {
return (FALSE)
}
}
if (testInteger(CAS.MULT[i,1]) == TRUE) {
if (testInteger(substring(CAS.MULT[i,2],1,1)) == TRUE) {
if (CAS.MULT[i,3] == '') {
toDelete <- c(toDelete, i)
}
}
}
}
CAS.MULT <- CAS.MULT[-1*toDelete,]
Hard to be sure without testing my code on your data, but this might work. Instead of a loop, the code below uses logical indexing based on the conditions you specified in your question. This is vectorized (meaning it operates on the entire data frame at once, rather than by row) and is much faster than looping row by row:
CAS.MULT.screened = CAS.MULT[!(CAS.MULT[,1] %% 1 == 0 |
as.numeric(substring(CAS.MULT[,2],1,1)) %% 1 == 0 |
CAS.MULT[,3] == ""), ]
For more on checking whether a value is an integer, see this SO question.
One other thing: Just for future reference, for efficiency you should define your function outside the loop, rather than recreating the function every time through the loop.