Just curious is this code:
data Bla.SomeGreatNewDataset;
set WORK.InputTempDataset;
by SomeColumnName;
if first.SomeColumnName then output;
else delete;
run;
the same as:
data Bla.SomeGreatNewDataset;
set WORK.InputTempDataset;
by SomeColumnName;
if not missing(first.SomeColumnName) then output;
else delete;
run;
in other words does:
if first.SomeColumnName
just check if SomeColumnName does not contain a missing value?
Short answer, no.
BY Group processing with first.var and last.var operates on the distinct values of the variable. A missing value is a valid missing value.
first.var and last.var are Boolean values, either 1 or 0. You code outputs just the first record for each unique value of SomeColumnName.
Note, the data needs to either be sorted by SomeColumnName or have an index on that column.
Here is an example:
data have;
input x;
datalines;
1
2
2
.
3
3
3
;
run;
proc sort data=have;
by x;
run;
data want;
set have;
by x;
if first.x;
run;
proc print data=want;
run;
Produces:
Obs x
1 .
2 1
3 2
4 3
Related
I need some help in trying to execute a comparison of rows within different ID variable groups, all in a single dataset.
That is, if there is any duplicate observation within two or more ID groups, then I'd like to delete the observation entirely.
I want to identify any duplicates between rows of different groups and delete the observation entirely.
For example:
ID Value
1 A
1 B
1 C
1 D
1 D
2 A
2 C
3 A
3 Z
3 B
The output I desire is:
ID Value
1 D
3 Z
I have looked online extensively, and tried a few things. I thought I could mark the duplicates with a flag and then delete based off that flag.
The flagging code is:
data have;
set want;
flag = first.ID ne last.ID;
run;
This worked for some cases, but I also got duplicates within the same value group flagged.
Therefore the first observation got deleted:
ID Value
3 Z
I also tried:
data have;
set want;
flag = first.ID ne last.ID and first.value ne last.value;
run;
but that didn't mark any duplicates at all.
I would appreciate any help.
Please let me know if any other information is required.
Thanks.
Here's a fairly simple way to do it: sort and deduplicate by value + ID, then keep only rows with values that occur only for a single ID.
data have;
input ID Value $;
cards;
1 A
1 B
1 C
1 D
1 D
2 A
2 C
3 A
3 Z
3 B
;
run;
proc sort data = have nodupkey;
by value ID;
run;
data want;
set have;
by value;
if first.value and last.value;
run;
proc sql version:
proc sql;
create table want as
select distinct ID, value from have
group by value
having count(distinct id) =1
order by id
;
quit;
This is my interpretation of the requirements.
Find levels of value that occur in only 1 ID.
data have;
input ID Value:$1.;
cards;
1 A
1 B
1 C
1 D
1 D
2 A
2 C
3 A
3 Z
3 B
;;;;
proc print;
proc summary nway; /*Dedup*/
class id value;
output out=dedup(drop=_type_ rename=(_freq_=occr));
run;
proc print;
run;
proc summary nway;
class value;
output out=want(drop=_type_) idgroup(out[1](id)=) sum(occr)=;
run;
proc print;
where _freq_ eq 1;
run;
proc print;
run;
A slightly different approach can use a hash object to track the unique values belonging to a single group.
data have; input
ID Value:& $1.; datalines;
1 A
1 B
1 C
1 D
1 D
2 A
2 C
3 A
3 Z
3 B
run;
proc delete data=want;
proc ds2;
data _null_;
declare package hash values();
declare package hash discards();
declare double idhave;
method init();
values.keys([value]);
values.data([value ID]);
values.defineDone();
discards.keys([value]);
discards.defineDone();
end;
method run();
set have;
if discards.find() ne 0 then do;
idhave = id;
if values.find() eq 0 and id ne idhave then do;
values.remove();
discards.add();
end;
else
values.add();
end;
end;
method term();
values.output('want');
end;
enddata;
run;
quit;
%let syslast = want;
I think what you should do is:
data want;
set have;
by ID value;
if not first.value then flag = 1;
else flag = 0;
run;
This basically flags all occurrences of a value except the first for a given ID.
Also I changed want and have assuming you create what you want from what you have. Also I assume have is sorted by ID value order.
Also this will only flag 1 D above. Not 3 Z
Additional Inputs
Can't you just do a sort to get rid of the duplicates:
proc sort data = have out = want nodupkey dupout = not_wanted;
by ID value;
run;
So if you process the observations by VALUE levels (instead of by ID levels) then you just need keep track of whether any ID is ever different than the first one.
data want ;
do until (last.value);
set have ;
by value ;
if first.value then first_id=id;
else if id ne first_id then remapped=1;
end;
if not remapped;
keep value id;
run;
I have a question regarding recursive/cumulative addition of a particular column for example: Click on example
How do I write this in SAS code which generates cumalitive addition with respect to column. Please help me with this.
Thank you in Advance
Example
use sum statement
data have;
input val;
datalines;
1
2
3
;
data want;
set have;
newval+val;
run;
Using Retain functionality.
You can reuse the code below as basis for any iterative/cumulative calculations.
data have;
input A;
datalines;
1
2
3
;
run;
data want;
set have;
Retain B;
/* If condition to initialize B only once, _N_ is the current row number */
if _N_= 1 then B=0;
B=B+A;
/* put statement will print the table in the log */
put _all_;
run;
Output:
A=1 B=1 _N_=1
A=2 B=3 _N_=2
A=3 B=6 _N_=3
In my sas data set there are groups, i.e. id and I want delete groups with missing values in a certain variable.
For example I have this sas data set:
data have;
input v1 v2 v3 id;
datalines;
9 7 210 1
0 6 . 1
9 3 320 2
6 1 . 1
9 4 432 2
;
run;
I tried this:
/*Order by id*/
proc sort data=have;
by id;
run;
/*Select no missing observations by id*/
data=want;
set=have;
if cmiss(of _all_) then delete;
run;
However this code does not exclude id's with missing values. It delete missing values.
Hmmm. You can use proc sql for this:
proc sql;
delete from have
where exists (select 1 from have have2 where have.id = have2.id and (have2.v1 is null or have2.v2 is null or have2.v3 is null);
One idea might be to use a double DOW loop. First to check for any missing values and then a second one to output the records for the ids with no missing values.
data have;
input v1 v2 v3 id;
datalines;
9 7 210 1
0 6 . 1
9 3 320 2
6 1 . 1
9 4 432 2
1 2 333 3
;
You will need to sort as in your example.
data want ;
do until (last.id);
set have;
by id;
anymissing=max(anymissing,cmiss(of v1-v3));
end;
do until (last.id);
set have;
by id;
if not anymissing then output;
end;
run;
You just dont want to have lines with missing Columns in your result dataset. So why delete, just exclude them when writing result-dataset or overwrite source-Dataset.:
data have;/*overwriting my have dataset instead of deleting lines*/
set have;
if not cmiss(of _ALL_);
run;
When you want to remove all lines for a group if only one line has a missing value you can do this, Store an ID if it has no value and then dont write any line with that id, and you just get ID lines you want as result. Important is that the ID with missing value is first in dataset, but that should be that way because of proc sort:
data want;
retain x;
set have;
if cmiss(of _ALL_) then
x= id;
if x ne id;
run;
I hope this is not a duplicate question. I've searched the forum and retain function seems to be choice of weapon but it copies down an observation, and I'm trying to do the following; for a given id, copy the second line to the first line for the x value. also first value of x is always 2.
Here's my data;
id x
3 2
3 1
3 1
2 2
2 1
2 1
6 2
6 0
6 0
and i want it to look like this;
id x
3 1
3 1
3 1
2 1
2 1
2 1
6 0
6 0
6 0
and here's the starter code;
data have;
input id x;
cards;
3 2
3 1
3 1
2 2
2 1
2 1
6 2
6 0
6 0
;
run;
Lead is tricky in SAS. You can sort in reverse and use a lag function to get around it though, and you are right: a retain statement will allow us to add an order variable so we can sort it back to its original format.
data have;
set have;
retain order;
lagid = lag(id);
if id ne lagid then order = 0;
order = order + 1;
drop lagid;
run;
proc sort data=have; by id descending order; run;
data have;
set have;
leadx = lag(x);
run;
proc sort data=have; by id order; run;
data have;
set have;
if order = 3 then x_fixed = x;
else x_fixed = leadx;
run;
If your data is exactly as you say, then you can use a lookahead merge. It literally takes the dataset and merges itself to a copy of the dataset that starts on row 2, side-to-side. You just have to check that you're still on the same ID. This does change the value of x for all records to the value one hence, not just the first; you could add additional code to pay attention to that (but can't use FIRST and LAST).
data want;
merge have have(firstobs=2 rename=(id=newid x=newx));
if newid=id then x=newx;
keep x id;
run;
If you don't have any additional variables of interest, then you can do something even more interesting: duplicate the second row in its entirety and delete the first row.
data want;
set have;
by id notsorted;
if first.id then do;
firstrow+1;
delete;
end;
if firstrow=1 then do;
firstrow=0;
output;
end;
output;
run;
However, the "safest" method (in terms of doing most likely what you want precisely) is the following, which is a DoW loop.
data want;
idcounter=0;
do _n_ = 1 by 1 until (last.id);
set have;
by id notsorted;
idcounter+1;
if idcounter=2 then second_x = x;
end;
do _n_=1 by 1 until (last.id);
set have;
by id notsorted;
if first.id then x=second_x;
output;
end;
run;
This identifies the second x in the first loop, for that BY group, then in the second loop sets it to the correct value for row 1 and outputs.
In both of the latter examples I assume your data is organized by ID but not truly sorted (like your initial example is). If it's not organized by ID, you need to perform a sort first (but then can remove the NOTSORTED).
I want to delete ALL blank observations from a data set.
I only know how to get rid of blanks from one variable:
data a;
set data(where=(var1 ne .)) ;
run;
Here I set a new data set without the blanks from var1.
But how to do it, when I want to get rid of ALL the blanks in the whole data set?
Thanks in advance for your answers.
If you are attempting to get rid of rows where ALL variables are missing, it's quite easy:
/* Create an example with some or all columns missing */
data have;
set sashelp.class;
if _N_ in (2,5,8,13) then do;
call missing(of _numeric_);
end;
if _N_ in (5,6,8,12) then do;
call missing(of _character_);
end;
run;
/* This is the answer */
data want;
set have;
if compress(cats(of _all_),'.')=' ' then delete;
run;
Instead of the compress you could also use OPTIONS MISSING=' '; beforehand.
If you want to remove ALL Rows with ANY missing values, then you can use NMISS/CMISS functions.
data want;
set have;
if nmiss(of _numeric_) > 0 then delete;
run;
or
data want;
set have;
if nmiss(of _numeric_) + cmiss(of _character_) > 0 then delete;
run;
for all char+numeric variables.
You can do something like this:
data myData;
set myData;
array a(*) _numeric_;
do i=1 to dim(a);
if a(i) = . then delete;
end;
drop i;
This will scan trough all the numeric variables and will delete the observation where it finds a missing value
Here you go. This will work irrespective of the variable being character or numeric.
data withBlanks;
input a$ x y z;
datalines;
a 1 2 3
b 1 . 3
c . . 3
. . .
d . 2 3
e 1 . 3
f 1 2 3
;
run;
%macro removeRowsWithMissingVals(inDsn, outDsn, Exclusion);
/*Inputs:
inDsn: Input dataset with some or all columns missing for some or all rows
outDsn: Output dataset with some or all columns NOT missing for some or all rows
Exclusion: Should be one of {AND, OR}. AND will only exclude rows if any columns have missing values, OR will exclude only rows where all columns have missing values
*/
/*get a list of variables in the input dataset along with their types (i.e., whether they are numericor character type)*/
PROC CONTENTS DATA = &inDsn OUT = CONTENTS(keep = name type varnum);
RUN;
/*put each variable with its own comparison string in a seperate macro variable*/
data _null_;
set CONTENTS nobs = num_of_vars end = lastObs;
/*use NE. for numeric cols (type=1) and NE '' for char types*/
if type = 1 then call symputx(compress("var"!!varnum), compbl(name!!" NE . "));
else call symputx(compress("var"!!varnum), compbl(name!!" NE '' "));
/*make a note of no. of variables to check in the dataset*/
if lastObs then call symputx("no_of_obs", _n_);
run;
DATA &outDsn;
set &inDsn;
where
%do i =1 %to &no_of_obs.;
&&var&i.
%if &i < &no_of_obs. %then &Exclusion;
%end;
;
run;
%mend removeRowsWithMissingVals;
%removeRowsWithMissingVals(withBlanks, withOutBlanksAND, AND);
%removeRowsWithMissingVals(withBlanks, withOutBlanksOR, OR);
Outout of withOutBlanksAND:
a x y z
a 1 2 3
f 1 2 3
Output of withOutBlanksOR:
a x y z
a 1 2 3
b 1 . 3
c . . 3
e 1 . 3
f 1 2 3
Really weird nobody provided this elegant answer:
if missing(cats(of _all_)) then delete;
Edit: indeed, I didn't realized the cats(of _all_) returns a dot '.' for missing numeric value.
As a fix, I suggest this, which seems to be more reliable:
*-- Building a sample dataset with test cases --*;
data test;
attrib a format=8.;
attrib b format=$8.;
a=.; b='a'; output;
a=1; b=''; output;
a=.; b=''; output; * should be deleted;
a=.a; b=''; output; * should be deleted;
a=.a; b='.'; output;
a=1; b='b'; output;
run;
*-- Apply the logic to delete blank records --*;
data test2;
set test;
*-- Build arrays of numeric and characters --*;
*-- Note: array can only contains variables of the same type, thus we must create 2 different arrays --*;
array nvars(*) _numeric_;
array cvars(*) _character_;
*-- Delete blank records --*;
*-- Blank record: # of missing num variables + # of missing char variables = # of numeric variables + # of char variables --*;
if nmiss(of _numeric_) + cmiss(of _character_) = dim(nvars) + dim(cvars) then delete;
run;
The main issue being if there is no numeric at all (or not char at all), the creation of an empty array will generate a WARNING and the call to nmiss/cmiss an ERROR.
So, I think so far there is not other option than building a SAS statement outside the data step to identify empty records:
*-- Building a sample dataset with test cases --*;
data test;
attrib a format=8.;
attrib b format=$8.;
a=.; b='a'; output;
a=1; b=''; output;
a=.; b=''; output; * should be deleted;
a=.a; b=''; output; * should be deleted;
a=.a; b='.'; output;
a=1; b='b'; output;
run;
*-- Create a SAS statement which test any missing variable, regardless of its type --*;
proc sql noprint;
select distinct 'missing(' || strip(name) || ')'
into :miss_stmt separated by ' and '
from dictionary.columns
where libname = 'WORK'
and memname = 'TEST'
;
quit;
/*
miss_stmt looks like missing(a) and missing(b)
*/
*-- Delete blank records --*;
data test2;
set test;
if &miss_stmt. then delete;
run;