I fear I've missed some crucial point in my education thus far.
I have a table HR and I've performed functions on it.
For example HR$FTE <- HR$'Std Hrs' / 38 gives me a new column for each employee; working as intended.
However, whenever I try to perform a function when creating a new column it doesn't like that. The question that I posted yesterday is similar in nature where the error result was from returning the whole row.
An example function that doesn't work would be HR$FYEnd <- as.Date(paste(HR$FY + 1,"06","30", sep = "-")). In this case, non-numeric argument to binary operator is returned, as HR$FY is not numeric but rather a column of numeric data. What should be outputted is a set of dates on 30/06.
In Excel (which I'm trying to train myself to leave) the equivalent when dealing with tables would be [#[FY Start]] or something to that effect which demonstrates that you're working with the figure on that row rather than the whole row.
Worked it out - couple of days later.
The step that I was missing was using the mapply/sapply commands. Using these has sorted everything out.
Related
My goal of this code is to create a loop that aggregates each company's word frequency by a certain principle vector I created and adds it to a list. The problem is, after I run this, it only prints the 7 principles that I have rather than the word frequencies along side them. The word frequencies being the certain column of the FREQBYPRINC.AG data frame. Individually, running this code without the loop and just testing out a certain column, it works no problem. For some reason, the loop doesn't want to give me the correct data frames for the list. Any suggestions?
list.agg<-vector("list",ncol(FREQBYPRINC.AG)-2)
for (i in 1:14){
attach(FREQBYPRINC.AG)
list.agg[i]<-aggregate(FREQBYPRINC.AG[,i+1],by=list(Type=principle),FUN=sum,na.rm=TRUE)
}
I really wish I could help. After reading your statement, It seems that to you , you feel that the code should be working and it is not. Well maybe there exists a glitch.
Since you had previously specified list. agg as a list, you need to subset it with double square brackets. Try this one out:
list.agg<-vector("list",ncol(FREQBYPRINC.AG)-2)
for (i in 1:14){
list.agg[[i]]<-aggregate(FREQBYPRINC.AG[,i+1],by=list
(Type=principle),FUN=sum,na.rm=TRUE)}
I did some reading on similar SO questions, but couldn't figure out how to resolve my error.
I have written the following string of code:
points[paste0(score.avail,"_pts")] <-
Map('*', points[score.avail], mget(paste0(score.avail,'_m')) )
Essentially, I have a list of columns in the 'points' data frame, defined by 'score.avail'. I am multiplying each of the columns by a respective constant, defined as the paste0(score.avail, '_m') expression. It appends new fields based on the multiplication, given by paste0(score.avail, "_pts") expression.
I have used this function before in a similar setup with no issues. However, I am now getting the following error:
Error in .Primitive("*")(dots[[1L]][[1L]], dots[[2L]][[1L]]) :
non-numeric argument to binary operator
I'm pretty sure R is telling me that one of the fields I'm trying to multiply is not numeric. However, I have checked all my fields, and they are numeric. I have even tried running a line as.numeric(score.avail) but that doesn't help. I also ran the following to remove NA's in the fields (before the Map function above).
for(col in score.avail){
points[is.na(get(col)) & (data.source == "average" |
data.source == "averageWeighted"), (col) := 0]}
The thing that stumps me is that this expression has worked with no issues before.
Update
I did some more digging by separating out each component of my original function. I'm getting odd output when running points[score.avail]. Previously when I ran this, it would return just the columns for all of my rows. Now, however, I'm getting none of the rows in my original data frame -- rather, it is imputing the column names in the 'score.avail' list as rows and filling in NA's everywhere (this is clearly the source of my problem).
I think this is because I'm using the object I'm pointing to is a data.table with keyvars set. Previously with this function, I had been pointing to a data frame.
Off to try a few more things.
Another Update
I was able to solve my problem by copying the 'points' object using as.data.frame(). However, I will leave the question open to see if anyone knows how to reset the data table key vars so that the function I specified above will work.
I was able to solve my problem by copying the 'points' object using as.data.frame(). Apparently classifying the object as a data.table was causing my headaches.
I have a dataset in stata and I want to take it to R, but there are some missing values in state and they are represented using a period. I want to get the data into R which I do by loading the foreign package and then I use read.table() function. How do I convert the periods in state which are genuinely missing to NA in R?
If i understand you correctly, you first load the Foreign-Package for loading a .dta-File, correct?
library("foreign")
Then you would read in your Data by using:
myRFile <- read.dta(file="someStataFile.dta")
You are asking for a way that the missing operator from Stata, often denoted by a dot ., is converted to the missing operator in R, NA, also correct?
One thing to know here is, that Stata handles missing values "behind the scenes" in multiple ways. There are actually about 27 different missing operators in Stata, which are usually not distinguishable for the user. You do not need to know them for you problem though, because read.dta() handles them itself.
To learn how you can tackle a simple problem like this yourself in the future, you always need to check the help file for your function first:
help(read.dta)
Here you see, that the function handles the extensive missing-data types from Stata automatically and correctly.
If you want to have information about which type of missing operator was recognized, you can set the argument missing.type=TRUE, by using:
myRFile <- read.dta(file="someStataFile.dta", missing.type=TRUE)
Then, according to the help file, the following will happen:
If missing.type is TRUE a separate list is created with the same
variable names as the loaded data. For string variables the list value
is NULL. For other variables the value is NA where the observation is
not missing and 0–26 when the observation is missing. This is attached
as the "missing" attribute of the returned value.
I am learning R and I have a R data table in which I want to remove unnecessary features (unnecessary table columns). For this I am using the ReliefexpRank algorithm from the CORElearn package, with table and originaltable being the R tables.
library(CORElearn)
estRelifF <-attrEval(FLAG_READMITIDO_MEAN ~.,table,estimator="ReliefFexpRank",ReliefIterations=30)
for( i in estRelifF ){
if(estReliefF[i]==0) {originaltable[i]<-NULL}
}
output <-data.frame (estReliefF)
I know that the estReliefF has the correct results, getting me results like this sample below for each feature
LOCAL
-4.428817e-01
HORA
0.000000e+00
And I want to remove the Hora one which is 0.
I don't know what the problem is though I suspect that's around the IF statement, since it's my first time using R I would appreciate some help since I can't seem to find the mistake.
The issue comes from you modifying your columns while running a loop on them. Let's say your vector and table are :
x<-c(1,1,0,1,0)
df<-data.frame(1:5,2:6,3:7,4:8,5:9)
If you run for(i in 1:5){if(x[i]==0){df[i]<-NULL}}, you'll see that the third column has been removed, but not the fifth. That's because after the third column has been removed, the fifth column is no longer the fifth but the fourth, and x[4]is not null.
You need to find all the unwanted columns before deleting them : one possible solution is :
df[-which(x==0)]
I have a data frame loaded using the CSV Library in R, like
mySheet <- read.csv("Table.csv", sep=";")
I now can print a summary on that mySheet object
summary(mySheet)
and it will show me a summary for each column, for example, one column named Diagnose has the unique values RCM, UCM, HCM and it shows the number of occurences of each of these values.
I now filter by a diagnose, like
subSheet <- mySheet[mySheet$Diagnose=='UCM',]
which seems to be working, when I just type subSheet in the console it will print only the rows where the value has been matched with 'UCM'
However, if I do a summary on that subSheet, like
summary(subSheet)
it still 'knows' about the other two possibilities RCM and HCM and prints those having a value of 0. However, I expected that the new created object will NOT know about the possible values of the original mySheet I initially loaded.
Is there any way to get rid of those other possible values after filtering? I also tried subset but this one just seems to be some kind of shortcut to '[' for the interactive mode... I also tried DROP=TRUE as option, but this one didn't change the game.
Totally mind squeezing :D Any help is highly appreciated!
What you are dealing with here are factors from reading the csv file. You can get subSheet to forget the missing factors with
subSheet$Diagnose <- droplevels(subSheet$Diagnose)
or
subSheet$Diagnose <- subSheet$Diagnose[ , drop=TRUE]
just before you do summary(subSheet).
Personally I dislike factors, as they cause me too many problems, and I only convert strings to factors when I really need to. So I would have started with something like
mySheet <- read.csv("Table.csv", sep=";", stringsAsFactors=FALSE)