SAS Missing Values Findings
I am working on a SAS Dataset which has missing values.
I can identify whether a particular variable has missing values using IS NULL/IS MISSING operator.
Is there any alternative way, through which I can identify which variables have missing values in one shot.
Thanks in Advance
sas
edited Nov 24 '18 at 18:47
Jérôme Teisseire
1,0261919
asked Nov 24 '18 at 17:47
Atreyi DattaAtreyi Datta
1
add a comment |
I am working on a SAS Dataset which has missing values.
I can identify whether a particular variable has missing values using IS NULL/IS MISSING operator.
Is there any alternative way, through which I can identify which variables have missing values in one shot.
Thanks in Advance
sas
edited Nov 24 '18 at 18:47
Jérôme Teisseire
1,0261919
asked Nov 24 '18 at 17:47
Atreyi DattaAtreyi Datta
1
add a comment |
I am working on a SAS Dataset which has missing values.
I can identify whether a particular variable has missing values using IS NULL/IS MISSING operator.
Is there any alternative way, through which I can identify which variables have missing values in one shot.
Thanks in Advance
sas
edited Nov 24 '18 at 18:47
Jérôme Teisseire
1,0261919
asked Nov 24 '18 at 17:47
Atreyi DattaAtreyi Datta
1
I am working on a SAS Dataset which has missing values.
I can identify whether a particular variable has missing values using IS NULL/IS MISSING operator.
Is there any alternative way, through which I can identify which variables have missing values in one shot.
Thanks in Advance
sas
sas
edited Nov 24 '18 at 18:47
Jérôme Teisseire
1,0261919
asked Nov 24 '18 at 17:47
Atreyi DattaAtreyi Datta
1
edited Nov 24 '18 at 18:47
Jérôme Teisseire
1,0261919
asked Nov 24 '18 at 17:47
Atreyi DattaAtreyi Datta
1
edited Nov 24 '18 at 18:47
Jérôme Teisseire
1,0261919
edited Nov 24 '18 at 18:47
Jérôme Teisseire
1,0261919
edited Nov 24 '18 at 18:47
Jérôme Teisseire
1,0261919
1,0261919
asked Nov 24 '18 at 17:47
Atreyi DattaAtreyi Datta
1
asked Nov 24 '18 at 17:47
Atreyi DattaAtreyi Datta
1
asked Nov 24 '18 at 17:47
Atreyi DattaAtreyi Datta
1
1
add a comment |
add a comment |
4 Answers
4
active
oldest
votes
The syntax IS NULL or IS MISSING is limited to use in SQL code (also in WHERE statements or WHERE= dataset options since those essentially use the same parser.)
To test if a value is missing you can also use the MISSING() function. Or compare it to a missing value. So for character variables test if it is equal to all blanks: c=' '. For numeric you can test x=., but you also need to look out for special missing values. So you might test if x <= .z.
To get a quick summary of number of distinct missing values for each variable you could use the NLEVEL option on PROC FREQ. Note it might not work for a large dataset with too many distinct values as the procedure will run out of memory.
answered Nov 24 '18 at 19:13
TomTom
22.8k2718
add a comment |
use array and vname to find variable with missing values. If you want rows with missing values use cmiss function.
data have;
infile datalines missover;
input id num char $ var $;
datalines;
1 . A C
2 3 D
5 6 B D
;
/* gives variables with missing values*/
data want1(keep=miss);
set have;
array chars(*) _character_;
array nums(*) _numeric_;
do i=1 to dim(chars);
if chars(i)=' ' then
miss=vname(chars(i));
if nums(i)=. then
miss=vname(nums(i));
end;
if miss=' ' then
delete;
run;
/* gives rows with missing value*/
data want(drop=rows);
set have;
rows=cmiss(of id -- var);
if rows=1;
run;
answered Nov 24 '18 at 18:42
Kiran Kiran
2,6373819
add a comment |
You can use proc freq table statement with missing option. It includes missing category if missing values exist. Useful for categorical data.
data example;
input A Freq;
datalines;
1 2
2 2
. 2
;
*list variables in tables statement;
proc freq data=example;
tables A / missing;
run;
You can also use Proc Univariate it creates MissingValues table in ODS by default if any missing values exist. Useful for numeric data.
answered Nov 26 '18 at 20:21
Peter SlezákPeter Slezák
112
add a comment |
Two options (in addition to Peter Slezák's) I can suggest are :
- Use proc means with nmiss
proc means data = ___ n nmiss;
var _numeric_;
run;
- In SAS Enterprise Guide, there is a characterize data task - this helps profile character variables too. (Under the hood, it is a combination of various procs, but is an easy to use option).
Hope this helps,
regards,
Sundaresh
answered Nov 26 '18 at 21:56
SundareshSundaresh
213
add a comment |
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4 Answers
4
active
oldest
votes
4 Answers
4
active
oldest
votes
active
oldest
votes
active
oldest
votes
The syntax IS NULL or IS MISSING is limited to use in SQL code (also in WHERE statements or WHERE= dataset options since those essentially use the same parser.)
To test if a value is missing you can also use the MISSING() function. Or compare it to a missing value. So for character variables test if it is equal to all blanks: c=' '. For numeric you can test x=., but you also need to look out for special missing values. So you might test if x <= .z.
To get a quick summary of number of distinct missing values for each variable you could use the NLEVEL option on PROC FREQ. Note it might not work for a large dataset with too many distinct values as the procedure will run out of memory.
answered Nov 24 '18 at 19:13
TomTom
22.8k2718
add a comment |
The syntax IS NULL or IS MISSING is limited to use in SQL code (also in WHERE statements or WHERE= dataset options since those essentially use the same parser.)
To test if a value is missing you can also use the MISSING() function. Or compare it to a missing value. So for character variables test if it is equal to all blanks: c=' '. For numeric you can test x=., but you also need to look out for special missing values. So you might test if x <= .z.
To get a quick summary of number of distinct missing values for each variable you could use the NLEVEL option on PROC FREQ. Note it might not work for a large dataset with too many distinct values as the procedure will run out of memory.
answered Nov 24 '18 at 19:13
TomTom
22.8k2718
add a comment |
The syntax IS NULL or IS MISSING is limited to use in SQL code (also in WHERE statements or WHERE= dataset options since those essentially use the same parser.)
To test if a value is missing you can also use the MISSING() function. Or compare it to a missing value. So for character variables test if it is equal to all blanks: c=' '. For numeric you can test x=., but you also need to look out for special missing values. So you might test if x <= .z.
To get a quick summary of number of distinct missing values for each variable you could use the NLEVEL option on PROC FREQ. Note it might not work for a large dataset with too many distinct values as the procedure will run out of memory.
answered Nov 24 '18 at 19:13
TomTom
22.8k2718
The syntax IS NULL or IS MISSING is limited to use in SQL code (also in WHERE statements or WHERE= dataset options since those essentially use the same parser.)
To test if a value is missing you can also use the MISSING() function. Or compare it to a missing value. So for character variables test if it is equal to all blanks: c=' '. For numeric you can test x=., but you also need to look out for special missing values. So you might test if x <= .z.
To get a quick summary of number of distinct missing values for each variable you could use the NLEVEL option on PROC FREQ. Note it might not work for a large dataset with too many distinct values as the procedure will run out of memory.
answered Nov 24 '18 at 19:13
TomTom
22.8k2718
answered Nov 24 '18 at 19:13
TomTom
22.8k2718
answered Nov 24 '18 at 19:13
TomTom
22.8k2718
answered Nov 24 '18 at 19:13
TomTom
22.8k2718
22.8k2718
add a comment |
add a comment |
use array and vname to find variable with missing values. If you want rows with missing values use cmiss function.
data have;
infile datalines missover;
input id num char $ var $;
datalines;
1 . A C
2 3 D
5 6 B D
;
/* gives variables with missing values*/
data want1(keep=miss);
set have;
array chars(*) _character_;
array nums(*) _numeric_;
do i=1 to dim(chars);
if chars(i)=' ' then
miss=vname(chars(i));
if nums(i)=. then
miss=vname(nums(i));
end;
if miss=' ' then
delete;
run;
/* gives rows with missing value*/
data want(drop=rows);
set have;
rows=cmiss(of id -- var);
if rows=1;
run;
answered Nov 24 '18 at 18:42
Kiran Kiran
2,6373819
add a comment |
use array and vname to find variable with missing values. If you want rows with missing values use cmiss function.
data have;
infile datalines missover;
input id num char $ var $;
datalines;
1 . A C
2 3 D
5 6 B D
;
/* gives variables with missing values*/
data want1(keep=miss);
set have;
array chars(*) _character_;
array nums(*) _numeric_;
do i=1 to dim(chars);
if chars(i)=' ' then
miss=vname(chars(i));
if nums(i)=. then
miss=vname(nums(i));
end;
if miss=' ' then
delete;
run;
/* gives rows with missing value*/
data want(drop=rows);
set have;
rows=cmiss(of id -- var);
if rows=1;
run;
answered Nov 24 '18 at 18:42
Kiran Kiran
2,6373819
add a comment |
use array and vname to find variable with missing values. If you want rows with missing values use cmiss function.
data have;
infile datalines missover;
input id num char $ var $;
datalines;
1 . A C
2 3 D
5 6 B D
;
/* gives variables with missing values*/
data want1(keep=miss);
set have;
array chars(*) _character_;
array nums(*) _numeric_;
do i=1 to dim(chars);
if chars(i)=' ' then
miss=vname(chars(i));
if nums(i)=. then
miss=vname(nums(i));
end;
if miss=' ' then
delete;
run;
/* gives rows with missing value*/
data want(drop=rows);
set have;
rows=cmiss(of id -- var);
if rows=1;
run;
answered Nov 24 '18 at 18:42
Kiran Kiran
2,6373819
use array and vname to find variable with missing values. If you want rows with missing values use cmiss function.
data have;
infile datalines missover;
input id num char $ var $;
datalines;
1 . A C
2 3 D
5 6 B D
;
/* gives variables with missing values*/
data want1(keep=miss);
set have;
array chars(*) _character_;
array nums(*) _numeric_;
do i=1 to dim(chars);
if chars(i)=' ' then
miss=vname(chars(i));
if nums(i)=. then
miss=vname(nums(i));
end;
if miss=' ' then
delete;
run;
/* gives rows with missing value*/
data want(drop=rows);
set have;
rows=cmiss(of id -- var);
if rows=1;
run;
answered Nov 24 '18 at 18:42
Kiran Kiran
2,6373819
edited Nov 24 '18 at 18:54
answered Nov 24 '18 at 18:42
Kiran Kiran
2,6373819
answered Nov 24 '18 at 18:42
Kiran Kiran
2,6373819
answered Nov 24 '18 at 18:42
Kiran Kiran
2,6373819
2,6373819
add a comment |
add a comment |
You can use proc freq table statement with missing option. It includes missing category if missing values exist. Useful for categorical data.
data example;
input A Freq;
datalines;
1 2
2 2
. 2
;
*list variables in tables statement;
proc freq data=example;
tables A / missing;
run;
You can also use Proc Univariate it creates MissingValues table in ODS by default if any missing values exist. Useful for numeric data.
answered Nov 26 '18 at 20:21
Peter SlezákPeter Slezák
112
add a comment |
You can use proc freq table statement with missing option. It includes missing category if missing values exist. Useful for categorical data.
data example;
input A Freq;
datalines;
1 2
2 2
. 2
;
*list variables in tables statement;
proc freq data=example;
tables A / missing;
run;
You can also use Proc Univariate it creates MissingValues table in ODS by default if any missing values exist. Useful for numeric data.
answered Nov 26 '18 at 20:21
Peter SlezákPeter Slezák
112
add a comment |
You can use proc freq table statement with missing option. It includes missing category if missing values exist. Useful for categorical data.
data example;
input A Freq;
datalines;
1 2
2 2
. 2
;
*list variables in tables statement;
proc freq data=example;
tables A / missing;
run;
You can also use Proc Univariate it creates MissingValues table in ODS by default if any missing values exist. Useful for numeric data.
answered Nov 26 '18 at 20:21
Peter SlezákPeter Slezák
112
You can use proc freq table statement with missing option. It includes missing category if missing values exist. Useful for categorical data.
data example;
input A Freq;
datalines;
1 2
2 2
. 2
;
*list variables in tables statement;
proc freq data=example;
tables A / missing;
run;
You can also use Proc Univariate it creates MissingValues table in ODS by default if any missing values exist. Useful for numeric data.
answered Nov 26 '18 at 20:21
Peter SlezákPeter Slezák
112
answered Nov 26 '18 at 20:21
Peter SlezákPeter Slezák
112
answered Nov 26 '18 at 20:21
Peter SlezákPeter Slezák
112
answered Nov 26 '18 at 20:21
Peter SlezákPeter Slezák
112
112
add a comment |
add a comment |
Two options (in addition to Peter Slezák's) I can suggest are :
- Use proc means with nmiss
proc means data = ___ n nmiss;
var _numeric_;
run;
- In SAS Enterprise Guide, there is a characterize data task - this helps profile character variables too. (Under the hood, it is a combination of various procs, but is an easy to use option).
Hope this helps,
regards,
Sundaresh
answered Nov 26 '18 at 21:56
SundareshSundaresh
213
add a comment |
Two options (in addition to Peter Slezák's) I can suggest are :
- Use proc means with nmiss
proc means data = ___ n nmiss;
var _numeric_;
run;
- In SAS Enterprise Guide, there is a characterize data task - this helps profile character variables too. (Under the hood, it is a combination of various procs, but is an easy to use option).
Hope this helps,
regards,
Sundaresh
answered Nov 26 '18 at 21:56
SundareshSundaresh
213
add a comment |
Two options (in addition to Peter Slezák's) I can suggest are :
- Use proc means with nmiss
proc means data = ___ n nmiss;
var _numeric_;
run;
- In SAS Enterprise Guide, there is a characterize data task - this helps profile character variables too. (Under the hood, it is a combination of various procs, but is an easy to use option).
Hope this helps,
regards,
Sundaresh
answered Nov 26 '18 at 21:56
SundareshSundaresh
213
Two options (in addition to Peter Slezák's) I can suggest are :
- Use proc means with nmiss
proc means data = ___ n nmiss;
var _numeric_;
run;
- In SAS Enterprise Guide, there is a characterize data task - this helps profile character variables too. (Under the hood, it is a combination of various procs, but is an easy to use option).
Hope this helps,
regards,
Sundaresh
answered Nov 26 '18 at 21:56
SundareshSundaresh
213
answered Nov 26 '18 at 21:56
SundareshSundaresh
213
answered Nov 26 '18 at 21:56
SundareshSundaresh
213
answered Nov 26 '18 at 21:56
SundareshSundaresh
213
213
add a comment |
add a comment |
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