[R] Help with factor column replacement value issue

[Bill Poling]

Hello:

I am running windows 10 -- R3.5.1 -- RStudio Version 1.1.456

I would like to know why when I replace a column value it still appears in subsequent routines:

My example:

r1$B1 is a Factor: It is created from the first character of a list of CPT codes, r1$CPT.

head(r1$CPT, N= 25)
[1] A4649 A4649 C9359 C1713 A0394 A0398
903 Levels: 00000 00001 00140 00160 00670 00810 00940 01400 01470 01961 01968 10160 11000 11012 11042 11043 11044 11045 11100 11101 11200 11201 11401 11402 ... l8699

str(r1$CPT)
 Factor w/ 903 levels "00000","00001",..: 773 773 816 783 739 741 743 739 739 741 ...


And I want only those CPT's with leading alpha char in this column so I set the numeric leading char to Z

r1$B1 <- str_sub(r1$CPT,1,1)

r1$B1 <- as.factor(r1$B1) #Redundant
levels(r1$B1)[levels(r1$B1) %in%  c('1','2','3','4','5','6','7','8','9','0')] <- 'Z'

When I check what I have done I find l & L

unique(r1$B1)
#[1] A C Z L G Q U J V E S l D P
#Levels: Z A C D E G J l L P Q S U V

So I change l to L
r1$B1[r1$B1 == 'l'] <- 'L'

When I check again I have l & L but l = 0
table(r1$B1)
#   Z          A          C      D     E     G      J           l     L         P     Q     S     U     V
#19639  1673   546     2     8   147   281     0    664     1    64    36   114    14

When I go to find those rows as if they existed, they are not accounted for?

tmp <- subset(r1, B1 == "l")
print(tmp)
Empty data.table (0 rows) of 9 cols: SavingsReversed,productID,ProviderID,PatientGender,ModCnt,Editnumber2...

And I have actually visually inspected the whole darn column, sheesh!

So I ignore it temporarily.

Now later on it resurfaces in a tutorial I am following for caret pkg.

preProcess(r1b, method = c("center", "scale"),
           thresh = 0.95, pcaComp = NULL, na.remove = TRUE, k = 5,
           knnSummary = mean, outcome = NULL, fudge = 0.2, numUnique = 3,
           verbose = FALSE, freqCut = 95/5, uniqueCut = 10, cutoff = 0.9,
           rangeBounds = c(0, 1))
# Warning in preProcess.default(r1b, method = c("center", "scale"), thresh = 0.95,  :
#                                 These variables have zero variances: B1l  <-------------yes this is a remnant of the r1$B1 clean-up
#                               Created from 23141 samples and 22 variables
#
#                               Pre-processing:
#                                 - centered (22)
#                                 - ignored (0)
#                                 - scaled (22)


So my questions are, in consideration of regression modelling accuracy:

Why is this happening?
How do I remove it?
Or is it irrelevant and leave it be?

As always, thank you for you support.

WHP












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