Trying to aggregate Queried data using a forloop in R - r

Question

I am having a little bit of trouble creating a loop that
sqlQueries every device in the variable "sensorname" (this is roughly 30 elements, but will increase in the future)
takes the data table associated with the device query and puts it into a separate data frame "data1" but keeps adding into it.
Below is my sample loop and a sample of what data1 looks like which is "correct", but not complete. LSF20_3a0925 is the last element in the variable sensorname so essentially the loop runs 30 times each time overwriting the data in variable data1 until it runs for the last time.
library(RODBC)
ch <- odbcConnect("SweetLab", uid='---', pwd='------')
sqlQuery(ch, "use SweetDatabase")
sensorname <- sqlQuery(ch,paste("SELECT site_device.code
FROM site_device, device
WHERE site_device.did=device.id AND
device.name='LSF20'
LIMIT 0, 1000;",
sep="")
)
for(k in 1:length(sensorname[[1]])){
sqlQuery(ch, "use SweetAnalysis")
sql <- na.omit(sqlQuery(ch,paste("select * From ",sensorname[[1]][k],"_Events",sep="")));
if (is.null(sql))
{return(NULL)}
data1 <- merge(sensorname[[1]][k],sql)
}
#############################################
data1
x row_names PeaksP1Time PeaksP1
1 LSF20_3a0925 24 1346781683 5.076920
2 LSF20_3a0925 31 1358444323 0.043240
3 LSF20_3a0925 13 1358444463 0.133170
4 LSF20_3a0925 12 1358445120 5.286443
Any help would be most appretiated I am new to writing code in general so please excuse me if this is a dumb question. I've searched around for a bit on this topic, but honestly wasn't quite sure how to search for this topic.

Answer 1

After some tweaking this looks great!
library(RODBC)
ch <- odbcConnect("SweetLab", uid='***', pwd='******')
sqlQuery(ch, "use SweetDatabase")
sensorname <- sqlQuery(ch,paste("select site_device.code from site_device, device where site_device.did=device.id and device.name='LSF20' LIMIT 0, 1000;",sep=""));
sqlQuery(ch, "use SweetAnalysis")
Datalist <- lapply(sensorname[[1]],function(x){
query <- paste("SELECT PeaksP1Time,PeaksP1 FROM ",x,"_Events",sep="")
dat <- (na.omit(sqlQuery(ch,query)))
data2.nlist<-list(device=x,data=dat)
names(Datalist)<-sensorname$code[1:30]
})
close(ch)
Looking at the structure of this list I get
> str(Datalist[1:3])
List of 3
$ LSF20_39ecf7:List of 1
..$ :'data.frame': 306 obs. of 2 variables:
.. ..$ PeaksP1Time: num [1:306] 1.35e+09 1.35e+09 1.35e+09 1.35e+09 1.35e+09 ...
.. ..$ PeaksP1 : num [1:306] 4.5 4.379 0.706 3 0 ...
$ LSF20_39cd3e:List of 1
..$ :'data.frame': 202 obs. of 2 variables:
.. ..$ PeaksP1Time: num [1:202] 1.35e+09 1.35e+09 1.35e+09 1.35e+09 1.35e+09 ...
.. ..$ PeaksP1 : num [1:202] 0.664 3.235 5.765 4.636 2.936 ...
.. ..- attr(*, "na.action")=Class 'omit' Named int [1:24] 203 204 205 206 207 208 209 210 211 212 ...
.. .. .. ..- attr(*, "names")= chr [1:24] "203" "204" "205" "206" ...
$ LSF20_3a09ac:List of 1
..$ :'data.frame': 42 obs. of 2 variables:
.. ..$ PeaksP1Time: num [1:42] 1.35e+09 1.35e+09 1.35e+09 1.35e+09 1.35e+09 ...
.. ..$ PeaksP1 : num [1:42] 5.589 2.897 2.713 1.706 0.831 ...
Now I'm moving on to the next phase of this which is graphing multiple sets at the same time.
My problem is how do I tell R that it should graph the data with in each list or specific lists. I have a save file of the work history if anyone wants to work with something reproducible.

Answer 2

Ok..without a reproducible example it is not clear what you asked. here how I would do it..
I open the connection
I loop using lapply to create a list
I close the connection
I bind list elements into data.frame. I assume taht you have the same columns for different sensor table.
ch <- odbcConnect("SweetLab", uid='---', pwd='------')
ll <- lapply(sensorname[[1]],function(x){
query <- paste("SELECT * FROM ",x,"_Events",sep="")
dat <- na.omit(sqlQuery(ch,query))
data.frame(sensor=x,dat)
})
close(ch)
data1 <- do.call(rbind,ll)

Answer 3

This is resource intensive, but will work.
# before your for loop
results <- list()
#inside your for loop
for (k ......) {
....
....
results[[k]] <- sql
}
# after your for loop
Data1 <- do.call(rbind, results) # if same schema
# OR
Data1 <- do.call(merge, results) # if different schema