R: Erroneous adding column, misclassifies instances - r

I 've got an R assignment in which I have to add a column to my matrix. It's about dates(time zones), I use dplyr and lubridate libraries.
So I want from the below table to according to the state column to add its OlsonName(i.e. NSW -> Australia/NSW)
Event.ID Database Date.Time Nearest.town State *OlsonName*
1 20812 Wind 23/11/1975 07:00 SYDNEY NSW *Australia/NSW*
2 20813 Tornado 02/12/1975 14:00 BARHAM NSW *Australia/NSW*
I implement that with a function and a loop:
#function
addOlsonNames <- function(aussieState,aussieTown){
if(aussieState=="NSW"){
if(aussieTown=="BROKEN HILL"){
value <- "Australia/Broken_Hill";
}else{
value <- "Australia/NSW"
}
}else if(aussieState=="QLD"){
value <- "Australia/Queensland"
}else if(aussieState=="NT"){
value <- "Australia/North"
}else if(aussieState=="SA"){
value <- "Australia/South"
}else if(aussieState=="TAS"){
value <- "Australia/Tasmania"
}else if(aussieState=="VIC"){
value <- "Australia/Victoria"
}else if(aussieState=="WA"){
value <- "Australia/West"
}else if(aussieState=="ACT"){
value <- "Australia/ACT"
}
else{
value <- "NAN"
}
return(value)
}
#loop
for(i in 1:nrow(aussieStorms)){
aussieStorms$OlsonName[i] <- addOlsonNames(State[i],Nearest.town[i])
}
Most of the instances are classified correctly like on my table above but some of the instances are misclassified(i.e. State~TAS -> OlsonName~Australia/West. Altough I have some State~TAS -> OlsonName~Australia/Tasmania).
Seems strange to me. What might be the issue ?
Update:
I also tried mutate() and that's what I got:
aus1 <- mutate(aussieStorms,OlsonXYZ = addOlsonNames(State,Nearest.town))
Warning messages:
1: In if (aussieState == "NSW") { :
the condition has length > 1 and only the first element will be used
2: In if (aussieTown == "BROKEN HILL") { :
the condition has length > 1 and only the first element will be used

If Ben Bolker's comment is right then the problem is in here:
for(i in 1:nrow(aussieStorms)){
aussieStorms$OlsonName[i] <- addOlsonNames(State[i],Nearest.town[i])
}
in that the values passed to addOlsonNames are not coming from rows of the aussieStorms data frame. If R isn't giving an error, then it must be getting State[i] from another object called State in your R workspace. Similarly for Nearest.town. If those objects aren't the same as the ones in your aussieStorms data frame, that would explain the apparent misclassification.
[Its also possible that you've used attach on a data frame at some point, and State is being got from that. But attaching data frames is a bad idea as you can see here...]
Ben's solution, ie making them aussieStorms$State and aussieStorms$Nearest.town look good to me.

Related

Nested for-loop with if statement

This is the code that I am trying to run and it's taking a while.
Districts is a data frame of 39299 rows and 16 columns and lm_data is a data frame of 59804 rows and 16 variables. I want to set up a new variable in lm_data called tentativeStartDate which takes on the value of districts$firstDay[j] if a couple of conditions are meant. Is there a more efficient way to do this?
for (i in 1: nrow(lm_data)){
for (j in 1: nrow(districts)){
if (lm_data$DISTORGID[i] == districts$DISTORGID[j] & lm_data$gradeCode[i] == districts$gradeCode[j]){
lm_data$tentativeStartDate[i] = districts$firstDay[j]
}
}
}
Not sure if this will work since I can't test it, but if it does work it should be much faster.
# get the indices
idx <- which(lm_data$DISTORGID == districts$DISTORGID & lm_data$gradeCode == districts$gradeCode)
lm_data$tentativeStartDate[idx] <- districts$firstDay[idx]

R for loop returns NULL instead of expected values

i<-c(1:44)
diff_arbeitnehmer <- for(x in i){if(x == 44) {diff_arbeitnehmer[x] <- 0} else{diff_arbeitnehmer[x] <- 100/erwerbstaetige[x,2]*erwerbstaetige[x,4]-100/erwerbstaetige[x+1,2]*erwerbstaetige[x+1,4]}}
My data frame has 44 entriess
I am using R script could someone tell me what could be the reason?
I am lost with this
I can't run your code because I don't have your data frame, but maybe the reason is because you are trying to assing a for loop into the variable diff_arbeitnehmer. I did this change and hope that know it works:
i<-c(1:44)
diff_arbeitnehmer <- c()
for(x in i){
if(x == 44){
diff_arbeitnehmer[x] <- 0
} else{
diff_arbeitnehmer[x] <- 100/erwerbstaetige[x,2]*erwerbstaetige[x,4]-100/erwerbstaetige[x+1,2]*erwerbstaetige[x+1,4]
}
}
An advice is to take a look if the assignment in the last condition is right, maybe you need to put some parenthesis.

Calculating distance using latitude and longitude error [duplicate]

When working with R I frequently get the error message "subscript out of bounds". For example:
# Load necessary libraries and data
library(igraph)
library(NetData)
data(kracknets, package = "NetData")
# Reduce dataset to nonzero edges
krack_full_nonzero_edges <- subset(krack_full_data_frame, (advice_tie > 0 | friendship_tie > 0 | reports_to_tie > 0))
# convert to graph data farme
krack_full <- graph.data.frame(krack_full_nonzero_edges)
# Set vertex attributes
for (i in V(krack_full)) {
for (j in names(attributes)) {
krack_full <- set.vertex.attribute(krack_full, j, index=i, attributes[i+1,j])
}
}
# Calculate reachability for each vertix
reachability <- function(g, m) {
reach_mat = matrix(nrow = vcount(g),
ncol = vcount(g))
for (i in 1:vcount(g)) {
reach_mat[i,] = 0
this_node_reach <- subcomponent(g, (i - 1), mode = m)
for (j in 1:(length(this_node_reach))) {
alter = this_node_reach[j] + 1
reach_mat[i, alter] = 1
}
}
return(reach_mat)
}
reach_full_in <- reachability(krack_full, 'in')
reach_full_in
This generates the following error Error in reach_mat[i, alter] = 1 : subscript out of bounds.
However, my question is not about this particular piece of code (even though it would be helpful to solve that too), but my question is more general:
What is the definition of a subscript-out-of-bounds error? What causes it?
Are there any generic ways of approaching this kind of error?
This is because you try to access an array out of its boundary.
I will show you how you can debug such errors.
I set options(error=recover)
I run reach_full_in <- reachability(krack_full, 'in')
I get :
reach_full_in <- reachability(krack_full, 'in')
Error in reach_mat[i, alter] = 1 : subscript out of bounds
Enter a frame number, or 0 to exit
1: reachability(krack_full, "in")
I enter 1 and I get
Called from: top level
I type ls() to see my current variables
1] "*tmp*" "alter" "g"
"i" "j" "m"
"reach_mat" "this_node_reach"
Now, I will see the dimensions of my variables :
Browse[1]> i
[1] 1
Browse[1]> j
[1] 21
Browse[1]> alter
[1] 22
Browse[1]> dim(reach_mat)
[1] 21 21
You see that alter is out of bounds. 22 > 21 . in the line :
reach_mat[i, alter] = 1
To avoid such error, personally I do this :
Try to use applyxx function. They are safer than for
I use seq_along and not 1:n (1:0)
Try to think in a vectorized solution if you can to avoid mat[i,j] index access.
EDIT vectorize the solution
For example, here I see that you don't use the fact that set.vertex.attribute is vectorized.
You can replace:
# Set vertex attributes
for (i in V(krack_full)) {
for (j in names(attributes)) {
krack_full <- set.vertex.attribute(krack_full, j, index=i, attributes[i+1,j])
}
}
by this:
## set.vertex.attribute is vectorized!
## no need to loop over vertex!
for (attr in names(attributes))
krack_full <<- set.vertex.attribute(krack_full,
attr, value = attributes[,attr])
It just means that either alter > ncol( reach_mat ) or i > nrow( reach_mat ), in other words, your indices exceed the array boundary (i is greater than the number of rows, or alter is greater than the number of columns).
Just run the above tests to see what and when is happening.
Only an addition to the above responses: A possibility in such cases is that you are calling an object, that for some reason is not available to your query. For example you may subset by row names or column names, and you will receive this error message when your requested row or column is not part of the data matrix or data frame anymore.
Solution: As a short version of the responses above: you need to find the last working row name or column name, and the next called object should be the one that could not be found.
If you run parallel codes like "foreach", then you need to convert your code to a for loop to be able to troubleshoot it.
If this helps anybody, I encountered this while using purr::map() with a function I wrote which was something like this:
find_nearby_shops <- function(base_account) {
states_table %>%
filter(state == base_account$state) %>%
left_join(target_locations, by = c('border_states' = 'state')) %>%
mutate(x_latitude = base_account$latitude,
x_longitude = base_account$longitude) %>%
mutate(dist_miles = geosphere::distHaversine(p1 = cbind(longitude, latitude),
p2 = cbind(x_longitude, x_latitude))/1609.344)
}
nearby_shop_numbers <- base_locations %>%
split(f = base_locations$id) %>%
purrr::map_df(find_nearby_shops)
I would get this error sometimes with samples, but most times I wouldn't. The root of the problem is that some of the states in the base_locations table (PR) did not exist in the states_table, so essentially I had filtered out everything, and passed an empty table on to mutate. The moral of the story is that you may have a data issue and not (just) a code problem (so you may need to clean your data.)
Thanks for agstudy and zx8754's answers above for helping with the debug.
I sometimes encounter the same issue. I can only answer your second bullet, because I am not as expert in R as I am with other languages. I have found that the standard for loop has some unexpected results. Say x = 0
for (i in 1:x) {
print(i)
}
The output is
[1] 1
[1] 0
Whereas with python, for example
for i in range(x):
print i
does nothing. The loop is not entered.
I expected that if x = 0 that in R, the loop would not be entered. However, 1:0 is a valid range of numbers. I have not yet found a good workaround besides having an if statement wrapping the for loop
This came from standford's sna free tutorial
and it states that ...
# Reachability can only be computed on one vertex at a time. To
# get graph-wide statistics, change the value of "vertex"
# manually or write a for loop. (Remember that, unlike R objects,
# igraph objects are numbered from 0.)
ok, so when ever using igraph, the first roll/column is 0 other than 1, but matrix starts at 1, thus for any calculation under igraph, you would need x-1, shown at
this_node_reach <- subcomponent(g, (i - 1), mode = m)
but for the alter calculation, there is a typo here
alter = this_node_reach[j] + 1
delete +1 and it will work alright
What did it for me was going back in the code and check for errors or uncertain changes and focus on need-to-have over nice-to-have.

Cant I use subset() in Function() after generating data frame with ddplyr

This is an assignment question everybody in my class solved it through split,apply I want to use different approach and used ddplyr and got stuck.
Here I have to generate a function best("State","Outcome"), o/p is Hospital name with lowest Mortality rate in the state entered.
eg-best("TX","heart failure") o/p-"CYPRESS"
MYCODE-
In the above steps Ihave read the file & subsetted the desired columns in data1
library(plyr)
data2 <- ddply(data1,.(State, Hospital.Name),
summarise, Heart.Attack=min(as.numeric(HA,na.rm=TRUE)))
data3 <- data2[complete.cases(data2),]
best <- function(State,outcome)
{
if(! State %in% data3$State) {
stop("invalid state")
} else if(State %in% data3$State && outcome == "Heart Attack") {
data4 <- subset(data3, State %in% data3$State, select=c(Hospital.Name))
return(nrow(data4))
}
}
Here when I am trying to return only those Hospitalnames which are in the entered function I am getting all the hospital names, If I assign the value manually then I get the correct no. of rows. I cant understand why its not taking value directly from function State%in%data3$State.
Well the error resolved...
I introduced empty character vector in loop,assigned the State value to it and then compared.

Error in *tmp*[[j]] : subscript out of bounds

Apologies for long post! I'm new to R and have been working hard to improve my command of the language. I stumbled across this interesting project on modelling football results: http://www1.maths.leeds.ac.uk/~voss/projects/2010-sports/JamesGardner.pdf
I keep running into problems when I run the code to Simulate a Full Season (first mentioned page 36, appendix page 59):
Games <- function(parameters)
{
teams <- rownames(parameters)
P <- parameters$teams
home <- parameters$home
n <- length(teams)
C <- data.frame()
row <- 1
for (i in 1:n) {
for (j in 1:n) {
if (i != j) {
C[row,1] <- teams[i]
C[row,2] <- teams[j]
C[row,3] <- rpois(1, exp(P[i,]$Attack - P[j,]$Defence + home))
C[row,4] <- rpois(1, exp(P[j,]$Attack - P[i,]$Defence))
row <- row + 1
}
}
}
return(C)
}
Games(TeamParameters)
The response I get is
Error in `*tmp*`[[j]] : subscript out of bounds
When I attempt a traceback(), this is what I get:
3: `[<-.data.frame`(`*tmp*`, row, 1, value = NULL) at #11
2: `[<-`(`*tmp*`, row, 1, value = NULL) at #11
1: Games(TeamParameters)
I don't really understand what the error means and I would appreciate any help. Once again, apologies for the long post but I'm really interested in this project and would love to learn what the problem is!
The data.frame objects are not extendable by row with the [<-.data.frame operation. (You would need to use rbind.) You should create an object that has sufficient space, either a pre-dimensioned matrix or data.frame. If "C" is an object of 0 rows, then trying to assign to row one will fail. There is a function named "C", so you might want to make its name something more distinct. It also seems likely that there are more efficient methods than the double loop but you haven't describe the parameter object very well.
You may notice that the Appendix of that paper you cited shows how to pre-dimension a dataframe:
teams <- sort(unique(c(games[,1], games[,2])), decreasing = FALSE)
T <- data.frame(Team=teams, ... )
... and the games-object was assumed to already have the proper number of rows and the results of computations were assigning new column values. The $<- operation will succeed if there is no current value for that referenced column.

Resources