The examples I gave--Null, Empty string, white space, etc where just examples
based on SPSS Modeler's Data Audit node.
I just want something that both identifies the columns having missing values--
regardless of what they technically are stored as(NA or a field with space bar
hit a couple of times,etc) -- and tabulates based on what type of missing
value. This is a basic data exploration step that I thought just maybe comes
standard in R and that I just don't know of yet.
Hmisc::describe is good and may have to suffice. "Missing" for the example
below using Hmisc::describe was 0 although there was a "". And I know that's
because of the technical difference.
#EXAMPLE data - just one column in this case
> dput(sample(mydata$COMMUTE_BIN,100))
structure(c(2L, 5L, 3L, 2L, 6L, 3L, 2L, 3L, 4L, 2L, 2L, 4L, 3L,
4L, 3L, 3L, 3L, 6L, 2L, 2L, 2L, 4L, 6L, 4L, 2L, 3L, 2L, 2L, 6L,
3L, 2L, 6L, 3L, 2L, 3L, 4L, 4L, 4L, 5L, 7L, 3L, 5L, 2L, 3L, 2L,
2L, 6L, 7L, 7L, 4L, 3L, 3L, 2L, 2L, 2L, 5L, 2L, 2L, 2L, 2L, 2L,
2L, 5L, 2L, 3L, 3L, 6L, 4L, 6L, 2L, 7L, 4L, 6L, 2L, 3L, 2L, 2L,
2L, 3L, 2L, 3L, 4L, 3L, 5L, 3L, 4L, 2L, 3L, 3L, 3L, 3L, 3L, 2L,
4L, 5L, 3L, 2L, 2L, 3L, 1L), .Label = c("", "<15", "15 - 24",
"25 - 34", "35 - 44", "45 - 54", "55+"), class = "factor")
As David mentioned maybe I will have to create my own function. Maybe something
similar to what I got here for identifying a factor columns, column labels and
number of levels.
#EXAMPLE of formula I will probably need to create for identifying and listing
column names and counts of NA and "" and other "missing" in a dataframe or
table. In this case however I am listing factor columns and excluding columns
w/ >32 levels
set.seed(1)
dat1<-
data.frame(col1=factor(sample(1:25,10,replace=TRUE)),col2=sample(letters[1:10],10,replace=TRUE),col3=factor(rep(1:5,each=2)))
PrintLvls2 <- function(x) {print(data.frame(Lvls=sapply(x[sapply(x,function(x)
is.factor(x)&&length(levels(x))<=32)],nlevels),
Names=sapply(x[sapply(x, function(x) is.factor(x)&&length(levels(x))<=32)],
function(y) paste0(levels(y), collapse=", "))), right=FALSE)}
> PrintLvls2(dat1)
Lvls Names
col1 9 2, 6, 7, 10, 15, 16, 17, 23, 24
col2 7 b, c, d, e, g, h, j
col3 5 1, 2, 3, 4, 5
Thanks.
Dan
-----Original Message-----
From: Bert Gunter [mailto:gunter.ber...@gene.com]
Sent: Tuesday, October 23, 2012 3:15 PM
To: David Winsemius
Cc: Lopez, Dan; R help (r-help@r-project.org)
Subject: Re: [R] Summary of variables with NA, empty
To highlight:
"Basically all Null values" is a meaningless phrase in R. ?Null ?NA ?NaN have
**very specific meanings** in R and have nothing to do with the various sorts
of whitespace characters that David mentions (spaces, tabs...). If you wish to
use R, you **must** understand the distinctions (the Intro to R tutorial
discusses some of this -- have you read it?).
There is functionality to test for these sorts of things (is.na, is.null, etc).
You need to put in the effort to learn about this if you mean to use R in any
serious way, as these will occur in either data I/O (NA's) or data manipulation
(e.g. 0/0)
-- Bert
On Tue, Oct 23, 2012 at 2:44 PM, David Winsemius <dwinsem...@comcast.net> wrote:
>
> On Oct 23, 2012, at 11:17 AM, Lopez, Dan wrote:
>
>> Hi,
>>
>> Is there a function I can use on my dataframe to give me a concise summary
>> of variables that are NA,blank,etc? Basically all Null values, Empty
>> strings, white space, blank values. Ideally it would look something like the
>> below:
>>
>> # it should only includes the fields with NAs, blanks, etc. Added bonus
>> would be to include column Index.
>> #Valid Records = records that are not NA, blank,etc #ColIndex - what
>> place is column in the original dataframe...1,2,3, ...xth
>>
>> Valid Records Null (NA?) Empty String White
>> Space Blank Value ColIndex
>
> Would a "Valid Record" be defined by grep([^ ], column)? ... i.e. has
> a non-space character in it What is a "ColIndex"?
> How is an "Empty String" different than "White Space" or a "Blank Value"
>
>
>
>> Var1 52 8
>> 2
>> Var2 40 20
>> 10 10
>> 3
>> Var3 58
>> 2
>> 20
>> ..
>>
>
> I generally use describe from package:Hmisc. There are other versions of
> describe in other packages. It's not going to classify items composed
> entirely of a varying number of spaces and other non-character items like
> tabs as a single group. And it's unclear what you will use as an operational
> definition to separate blanks and white-space. You will probably need to code
> that yourself. You might want to look at the code for Hmisc::describe as a
> starting point.
>
>
>> I now there is summary() but I am not sure if that always displays NAs and
>> blanks especially with factor variables that have several levels (lumps them
>> in 'Other' when I run the entire dataframe).
>
>
>> In these instances I can run the individual field separately and see all
>> levels but that would be inefficient to do for a dataframe with over 50
>> variables.
>
> How were you going to "run the individual field"? If you show us code, there
> might be more rapid progress. It would probably be very easy to turn that
> into a function that could then be "run" with `lapply`.
>>
>>
> --
>
> David Winsemius, MD
> Alameda, CA, USA
>
> ______________________________________________
> R-help@r-project.org mailing list
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
--
Bert Gunter
Genentech Nonclinical Biostatistics
Internal Contact Info:
Phone: 467-7374
Website:
http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm
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