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)
}
}
Related
I have tried the following but the output brings an argument stating,
Error in append("0") : argument "values" is miss
for (rowz in final_data$Ingridients) {
Cobalt_row<-lst()
if (sum(str_detect(rowz, 'Cobalt'))>0) {
Cobalt_row.append(1)
} else {
Cobalt_row<-append(0)
}
print(Cobalt_row)
}
I intended to loop through the list and generate a boolean of ones and twos depending on
whether or not I had the value.
Please help
Without the data, I can't test it, but this should work:
Cobalt_row<-lst()
k <- 1
for (rowz in final_data$Ingridients) {
Cobalt_row[[k]] <- ifelse(str_detect(rowz, 'Cobalt'), 1, 0)
k <- k+1
}
or even simpler if you need a list:
Cobalt_row <- as.list(as.numeric(str_detect(final_data$Ingredients, "Cobalt")))
enter image description here
I know there exists function 'unique' which works similar to what I want to make, but I want to make this function.
I want this function finally returns 'result' which contains unique elements of input vector.
But I don't know why this function's result is totally different from my expect.
Why c which is to combine before result and new unique element is not working.
Please tell me how to fix my code.
Thank you.
I think what you expect might be something like below, where result should be an argument of m_uni:
m_uni <- function(x,result = c()) {
if (class(x)=='numeric'| class(x)=='character') {
if (length(x) <= 1){
return(result)
} else {
if (x[length(x)] %in% result) {
x <- x[-length(x)]
m_uni(x,result)
} else {
result <- c(result,x[length(x)])
x <- x[-length(x)]
m_uni(x,result)
}
}
} else {
return('This function only gets numeric or character vector')
}
}
such that
> m_uni(x)
[1] 0 4 5 -2
I'm new to R and keep trying to think of it like JS, but it's definitely nothing like it. I need to take each value in column 1 and compare it to it's counter part in column 2.
For example: If the fifth item in column 1 is "Subaru" I need to see what the fifth item in column 2 is. If in column 2 the zip code is 24153, do one thing, if it's 24060 do something else.
With JS I would just run a for loop and do something like
for(i; i < name.length; i++){
if(name[i] == "Subaru" && zipcode[i] == 24153){
do this
} else if (blah blah){
blah blah blah
}
}
But you can't use i to get the index of each column in R because in an R for loop i is the value...right?
I tried nesting for loops but I have 7,000+ items in the database and cycling through all those twice is killer, even with breaks because the inner loop always starts back at 1.
I tried also putting them in a list but for some reason that's not working. Here are the two methods I've tried so far.
names = data$model
zips = data$zipcode
mylist <- list()
mylist[[1]] <- names
mylist[[2]] <- zips
r = 0
while (r <= length(mylist[[1]])) {
print(mylist[[1]][r])
print(mylist[[2]][r])
if(!is.na(mylist[[1]][r])){
if(mylist[[1]][r] == "Subaru" & mylist[[2]][r] == "24153"){
print(mylist[[1]][r])
}
}
}
And the nested for loops
names = data$model
zips = data$zipcode
for (j in names) {
if(!is.na(j)){
for (k in zips) {
if(!is.na(k)){
if(j == "Subaru" & k == "24153"){
print(j)
break
} else if(j == "Subaru" & k == "24060"){
print(j)
break
} else if(j == "Subaru" & k == "24019"){
print(j)
break
}
}
}
}
}
Any tips or ideas are welcome. I feel like I'm looking at it the wrong way.
Yes your for loop is in more of a java format. Try something like this:
for(i in 1:nrow(data){
if(name[i] == "Subaru" & zipcode[i] == 24153){
foo
}else if{
bar
}}
Disclaimer: This is a question regarding an assignment for a Coursera course.
I'm having trouble coming up with a way to create a new column that differentiates between weekdays and weekends in my data set. I'm using a nested if/else statement within a for loop. The problem is the output makes every row 'weekday'. Does anyone see something glaringly wrong with my code? My end goal is to create a new factor variable that is either "weekend" or "weekday."
df4 <- mutate(df4, day = weekdays(df4$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'
}
}
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.