Unable to do homog.test in a loop - r

I have a problem looping through columns with this command. When printing "i", the variable name appears, but it does not substitute it in the formula. The error suggested that I can't use a variable. Any suggestions?
for (i in colnames(NMDStrokeHx)[3:14]){
print(i)
print(homog.test(i ~ AM25, data = NMDStrokeHx, method = "Levene"))
}
output:
[1] "ANCOWATO"
Error in homog.test(i ~ AM25, data = NMDStrokeHx, method = "Levene") :
The name of response variable does not match the variable names in the data.
these are the column names of the data:
> colnames(NMDStrokeHx)[3:14]
[1] "ANCOWATO" "ANMSETOT" "ANAFTOT" "ANBNTTOT" "ANDELCOR" "ANWM2TOT" "ANFULVR1" "ANVRTCOR" "ANTMASEC"
[10] "ANTMBSEC" "ANSDMTOT" "ADCDRSTG"

You can use reformulate/as.formula to create a formula object.
for (i in colnames(NMDStrokeHx)[3:14]){
print(i)
print(homog.test(reformulate('AM25', i), data = NMDStrokeHx,method = "Levene"))
}

Related

Using an R function to hash values produces a repeating value across rows

I'm using the following query:
let
Source = {1..5},
#"Converted to Table" = Table.FromList(Source, Splitter.SplitByNothing(), {"Numbers"}, null, ExtraValues.Error),
#"Added Custom" = Table.AddColumn(#"Converted to Table", "Letters", each Character.FromNumber([Numbers] + 64)),
#"Run R script" = R.Execute("# 'dataset' holds the input data for this script#(lf)#(lf)library(""digest"")#(lf)#(lf)dataset$SuffixedLetters <- paste(dataset$Letters, ""_suffix"")#(lf)dataset$HashedLetters <- digest(dataset$Letters, ""md5"", serialize = TRUE)#(lf)output<-dataset",[dataset=#"Added Custom"]),
output = #"Run R script"{[Name="output"]}[Value]
in
output
which leads to the resulting table:
And the here is the R script with better formatting:
# 'dataset' holds the input data for this script
library("digest")
dataset$SuffixedLetters <- paste(dataset$Letters, "_suffix")
dataset$HashedLetters <- digest(dataset$Letters, "md5", serialize = TRUE)
output<-dataset
The 'paste' function appears to iterate over rows and resolve on each row with the new input. But the 'digest' function only appears to return the first value in the table across all rows.
I don't know why the behavior of the two functions would seem to operate differently. Can anyone advise how to get the 'HashedLetters' column to resolve using the values from each row instead of just the initial one?
Use:
dataset$HashedLetters <- sapply(dataset$Letters, digest, algo = "md5", serialize = TRUE)
digest works on a whole object at a time, not individual elements of a vector.
vec <- letters[1:3]
digest::digest(vec, algo="md5", serialize=TRUE)
# [1] "38ce1fe9e19a222505e693e8bdd8aeec"
sapply(vec, digest::digest, algo="md5", serialize=TRUE)
# a b c
# "127a2ec00989b9f7faf671ed470be7f8" "ddf100612805359cd81fdc5ce3b9fbba" "6e7a8c1c098e8817e3df3fd1b21149d1"

How to prevent coercion to list in R

I am trying to remove all NA values from two columns in a matrix and make sure that neither column has a value that the other doesn't.
code:
data <- dget(file)
dependent <- data[,"chroma"]
independent <- data[,"mass..Pantheria."]
names(independent) <- names(dependent) <- rownames(data)
for (name in rownames(data)) {
if(is.na(dependent[name])) {
independent$name <- NULL
dependent$name <- NULL
}
if(is.na(independent[name])) {
independent$name <- NULL
dependent$name <- NULL
}
}
print(dput(independent))
print(dput(dependent))
I am brand new to R and am trying to perform this task with a for loop. However, when I delete a section by assigning NULL I receive the following warning:
1: In independent$Aeretes_melanopterus <- NULL : Coercing LHS to a list
2: In dependent$name <- NULL : Coercing LHS to a list
No elements are deleted and independent and dependent retain all their original rows.
file (input):
structure(list(chroma = c(7.443501276, 10.96156313, 13.2987235,
17.58110922, 13.4991105), mass..Pantheria. = c(NA, 126.57, NA,
160.42, 250.57)), .Names = c("chroma", "mass..Pantheria."), class = "data.frame", row.names = c("Aeretes_melanopterus",
"Ammospermophilus_harrisii", "Ammospermophilus_insularis", "Ammospermophilus_nelsoni",
"Atlantoxerus_getulus"))
chroma mass..Pantheria.
Aeretes_melanopterus 7.443501 NA
Ammospermophilus_harrisii 10.961563 126.57
Ammospermophilus_insularis 13.298723 NA
Ammospermophilus_nelsoni 17.581109 160.42
Atlantoxerus_getulus 13.499111 250.57
desired output:
structure(list(chroma = c(10.96156313, 17.58110922, 13.4991105
), mass..Pantheria. = c(126.57, 160.42, 250.57)), .Names = c("chroma",
"mass..Pantheria."), class = "data.frame", row.names = c("Ammospermophilus_harrisii",
"Ammospermophilus_nelsoni", "Atlantoxerus_getulus"))
chroma mass..Pantheria.
Ammospermophilus_harrisii 10.96156 126.57
Ammospermophilus_nelsoni 17.58111 160.42
Atlantoxerus_getulus 13.49911 250.57
structure(c(126.57, 160.42, 250.57), .Names = c("Ammospermophilus_harrisii",
"Ammospermophilus_nelsoni", "Atlantoxerus_getulus"))
Ammospermophilus_harrisii Ammospermophilus_nelsoni Atlantoxerus_getulus
126.57 160.42 250.57
structure(c(10.96156313, 17.58110922, 13.4991105), .Names = c("Ammospermophilus_harrisii",
"Ammospermophilus_nelsoni", "Atlantoxerus_getulus"))
Ammospermophilus_harrisii Ammospermophilus_nelsoni Atlantoxerus_getulus
10.96156 17.58111 13.49911
Looks like you want to omit rows from your data where chroma or mass..Pantheria are NA. Here's a quick way to do it:
data = data[!is.na(data$chroma) & !is.na(data$mass..Pantheria.), ]
I'm not sure why you are breaking independent and dependent out separately, but after filtering out bad observations is a good time to do it.
Since those are your only two columns, this is equivalent to omitting rows from your data frame that have any NA values, so you can use a shortcut like this:
data = na.omit(data)
If you want to keep a "pristine" copy of your raw data, simply change the name of the result:
data_no_na = na.omit(data)
# or
data = data[!is.na(data$chroma) & !is.na(data$mass..Pantheria.), ]
As to what's wrong with your code, $ is used for extracting columns from a data frame, but you're trying to use it for a named vector (since you've already extracted the columns), which doesn't work. Even then, $ only works with a literal string, you can't use it with a variable. For data frames, you need to use brackets to extract columns stored in variables. For example, the built-in mtcars data has a column called "mpg":
# these work:
mtcars$mpg
mtcars[, "mpg"]
my_col = "mpg"
mtcars[, my_col]
mtcars$my_col ## does not work, need to use brackets!
You can never use $ with row names in a data frame, only column names.

How to structure output to write to csv within a for statement in R?

I'm running a conditional logistic regression analysis on different individuals using a for statement in R. The code for this is pretty straightforward:
for(ID in unique(Hour168Fin$BAND)){
modelone = clogit(Hour168Fin$OBSERVED ~ Hour168Fin$LNSTEPLENG + Hour168Fin$PowCross + Shrub +
strata(Hour168Fin$STEPID), data=Hour168Fin, subset = which(ID==Hour168Fin$BAND))
I'm interested in very specific parts of the output, so I've structured the output to give me exactly the coefficients I need using this:
x1beta = as.numeric(summary(modelone)$coef[1,1])
x2beta = as.numeric(summary(modelone)$coef[2,1])
x3beta = as.numeric(summary(modelone)$coef[3,1])
x1SE = as.numeric(summary(modelone)$coef[1,3])
x2SE = as.numeric(summary(modelone)$coef[2,3])
x3SE = as.numeric(summary(modelone)$coef[3,3])
x1pvalue = as.numeric(summary(modelone)$coef[1,5])
x2pvalue = as.numeric(summary(modelone)$coef[2,5])
x3pvalue = as.numeric(summary(modelone)$coef[3,5])
modelAIC = AIC(modelone)
results = table(x1beta, x1SE, x1pvalue, x2beta, x2SE, x2pvalue, x2beta, x2SE, x2pvalue, modelAIC, rownames = ID)}
In R, I can see all the results in the format I'm looking for, but when I use this to get these results into a csv:
write.csv = (results, file = "TrialOut.csv")
I'm only getting the results of 1 unique ID. I've tried embedding the write.csv statement in the for statement, and using it outside of it with the same results. Any suggestions? I'm really baffled because I can see the results in R but can't seem to get that to translate to a csv.
Thanks for your time!
Try including the write.csv call inside the loop, and use append = TRUE:
for (...) {
# ...
# ...
write.csv(results, file = "someFile.csv", append = TRUE)
}

Avoiding for loop, Naming Example

I would like to avoid using for loop in following example. Goal is to repeat string vector multiple times with different second part which changes each repetition. Is that possible?
str2D = mtcars
Vector = c(10,20)
Dimen = dim( str2D )
nn = c()
for ( i in Dimen[2]*(1:length(Vector)) ){
nn[ (i+1-Dimen[2]): i ] = rep(paste("|d",Vector[i/Dimen[2]],sep=""), Dimen[2] )
}
Name = paste( rep(names(str2D) , length(Vector) ),nn,sep="")
Correct result for "Name" vector is following:
"mpg|d10" "cyl|d10" "disp|d10" "hp|d10" "drat|d10" "wt|d10" "qsec|d10" "vs|d10" "am|d10" "gear|d10" "carb|d10" "mpg|d20" "cyl|d20" "disp|d20" "hp|d20" "drat|d20" "wt|d20" "qsec|d20" "vs|d20" "am|d20" "gear|d20" "carb|d20"
Thank you
I don't quite understand the end goal here but at least this achieves your desired output without a loop:
Name <- paste0(paste(names(mtcars)), "|d", rep(1:2, each = length(names(mtcars))), "0")
> Name
[1] "mpg|d10" "cyl|d10" "disp|d10" "hp|d10" "drat|d10" "wt|d10" "qsec|d10"
[8] "vs|d10" "am|d10" "gear|d10" "carb|d10" "mpg|d20" "cyl|d20" "disp|d20"
[15] "hp|d20" "drat|d20" "wt|d20" "qsec|d20" "vs|d20" "am|d20" "gear|d20"
[22] "carb|d20"

How to access data saved in an assign construct?

I made a list, read the list into a for loop, do some calculations with it and export a modified dataframe to [1] "IAEA_C2_NoStdConditionResiduals1" [2] "IAEA_C2_EAstdResiduals2" ect. When I do View(IAEA_C2_NoStdConditionResiduals1) after the for loop then I get the following error message in the console: Error in print(IAEA_C2_NoStdConditionResiduals1) : object 'IAEA_C2_NoStdConditionResiduals1' not found, but I know it is there because RStudio tells me in its Environment view. So the question is: How can I access the saved data (in this assign construct) for further usage?
ResidualList = list(IAEA_C2_NoStdCondition = IAEA_C2_NoStdCondition,
IAEA_C2_EAstd = IAEA_C2_EAstd,
IAEA_C2_STstd = IAEA_C2_STstd,
IAEA_C2_Bothstd = IAEA_C2_Bothstd,
TIRI_I_NoStdCondition = TIRI_I_NoStdCondition,
TIRI_I_EAstd = TIRI_I_EAstd,
TIRI_I_STstd = TIRI_I_STstd,
TIRI_I_Bothstd = TIRI_I_Bothstd
)
C = 8
for(j in 1:C) {
#convert list Variable to string for later usage as Variable Name as unique identifier!!
SubNameString = names(ResidualList)[j]
SubNameString = paste0(SubNameString, "Residuals")
#print(SubNameString)
LoopVar = ResidualList[[j]]
LoopVar[ ,"F_corrected_normed"] = round(LoopVar[ ,"F_corrected_normed"] / mean(LoopVar[ ,"F_corrected_normed"]),
digit = 5
)
LoopVar[ ,"F_corrected_normed_error"] = round(LoopVar[ ,"F_corrected_normed_error"] / mean(LoopVar[ ,"F_corrected_normed_error"]),
digit = 5
)
assign(paste(SubNameString, j), LoopVar)
}
View(IAEA_C2_NoStdConditionResiduals1)
Not really a problem with assign and more with behavior of the paste function. This will build a variable name with a space in it:
assign(paste(SubNameString, j), LoopVar)
#simple example
> assign(paste("v", 1), "test")
> `v 1`
[1] "test"
,,,, so you need to get its value by putting backticks around its name so the space is not misinterpreted as a parse-able delimiter. See what happens when you type:
`IAEA_C2_NoStdCondition 1`
... and from here forward, use paste0 to avoid this problem.

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