BookmarkSubscribeRSS Feed
jdveerapaneni
Calcite | Level 5

Hi

 

Need help to Highlight mismatched rows(compare 2-3 , 4-5,6-7 rows so on dynamically) data Using SAS while generating a multi sheet excel file .

SAS is on Unix server. I am using SAS EG 7.1

Below is the data I have to compare every two rows and highlight the mismatched data while generating the Excel and send it via email.

Note - there are multiple sheets and columns vary (sometimes there maybe 10 columns, sometimes it may be 18)

 

I have SAS code(used ODS) to generate excel with multiple sheets and send it via email and separate a VBA macro to highlight the mismatched data which I run manually. But I am unable to integrate both in to single code so that no manual work is needed, I really appreciate if anyone can suggest any way to do it in one single code.

 

Below is sample dataset , rows and column are dynamically created based on the project. Need to compare 2-3,4-5, 6-7..so-on rows and highlight(I have given blue to the font but i need whole box as yellow) only when they don’t match.

 

ssn

firstname

lastname

empid

address

city

state

zip

000-11-1234

abc

d

1001

plotno 123

abcd

rd

12345

000-11-1234

abc

e

1001

plotno 123

abcd

rd

12345

111-12-3456

efgh

f

2001

house 897

tyui

fg

23456-789

111-12-3456

efgh

f

2001

hs 897

tyui

fg

23456

444-56-7890

wrt

y

3001

 

 

xc

12345

444-56-7890

wert

y

3002

 

 

xc

12345

 

my VBA code:

 

Sub compare_Auto()

Dim LastColumn As Long

LastColumn = ActiveSheet.Range("A1").CurrentRegion.Columns.Count

Dim rng As Range, rngDiff As Range

Set rng = Range(Cells(2, 7), Cells(3, LastColumn))

Do While Application.CountA(rng) > 0  'loop while have content

        Set rngDiff = Nothing   'reset range

        On Error Resume Next    'ignore "No cells were found" error if no differences

        Set rngDiff = rng.ColumnDifferences(Comparison:=rng.Cells(1))

        On Error GoTo 0         'stop ignoring errors

        If Not rngDiff Is Nothing Then

            rngDiff.Interior.ColorIndex = 6 'color all differences

            rngDiff.Offset(-1).Interior.ColorIndex = 6

        End If

        Set rng = rng.Offset(2) 'two rows down

    Loop

End Sub

15 REPLIES 15
ChrisNZ
Tourmaline | Level 20

You could have an Excel file with no data that contains the VBA, and use SAS to add data to the file (or rather to a copy of the file as you want to keep the original file untouched, ready for the next run).

jdveerapaneni
Calcite | Level 5
I tried creating a blank xlsm file with the vba macro saved it , but unable to send multiple datasets and run vba macro for each sheet using ods.can you help me with the sample code. Appreciate your help.
Tom
Super User Tom
Super User

You should be able to use PROC REPORT to highlight the cells, so no need for any Excel code.

 

Can you explain the rule for highlighting a value? (and don't use cell numbers).

Are just just comparing to the first observation in the BY group? 

Or just to the previous observation?

jdveerapaneni
Calcite | Level 5
Yes I am comparing all the columns data based on 1 key column ssn .every 2 rows have same ssn, one row is coming from source A and other is coming from source B they both are getting appended in to 1 dataset, so need compare both rows and highlight the mismatched values.
jdveerapaneni
Calcite | Level 5
Thank you, I did try to proc compare but it didn't work for me because sometimes columns will be different in source A data compared to Source B, in that situation I only get compare dataset with the columns in source A(or which ever is the first dataset).
Can you share me a sample logic to compare 2 rows data and highlight using proc report? Appreciate your help.
Tom
Super User Tom
Super User

So if every SSN has two observations then it should be easy to make the FLAG variables using BY group processing an LAG() function.

 

First let's convert your listing back into a dataset.

data have;
  infile cards dsd dlm='|' truncover;
  length ssn $11 firstname lastname $30 empid $10 address $80 city $30 state $2 zip $9;
  input ssn--zip;
cards;
000-11-1234|abc|d|1001|plotno 123|abcd|rd|12345
000-11-1234|abc|e|1001|plotno 123|abcd|rd|12345
111-12-3456|efgh|f|2001|house 897|tyui|fg|23456-789
111-12-3456|efgh|f|2001|hs 897|tyui|fg|23456
444-56-7890|wrt|y|3001|||xc|12345
444-56-7890|wert|y|3002|||xc|12345
;

Now we can make some flag variables and remerge it with the data.

data flags;
  set have;
  by ssn;
  keep ssn F_: ;
  F_firstname=firstname ne lag(firstname);
  F_lastname=lastname ne lag(lastname);
  F_empid=empid ne lag(empid);
  F_address=address ne lag(address);
  F_city=city ne lag(city);
  F_state=state ne lag(state);
  F_zip=zip ne lag(zip);
  if last.ssn;
run;

data want;
  merge have flags;
  by ssn;
run;

Now we can use compute blocks to set the text color based on the flag variable values.

proc report data=want;
  column ssn f_: firstname--zip;
  define f_: /  noprint display;
  compute firstname;
    if f_firstname then call define(_col_, "style", "style=[color=blue]");
  endcomp; 
  compute lastname;
    if f_lastname then call define(_col_, "style", "style=[color=blue]");
  endcomp; 
  compute empid;
    if f_empid then call define(_col_, "style", "style=[color=blue]");
  endcomp; 
  compute address;
    if f_address then call define(_col_, "style", "style=[color=blue]");
  endcomp; 
  compute city;
    if f_city then call define(_col_, "style", "style=[color=blue]");
  endcomp; 
  compute state;
    if f_state then call define(_col_, "style", "style=[color=blue]");
  endcomp; 
  compute zip;
    if f_zip then call define(_col_, "style", "style=[color=blue]");
  endcomp;
run;

Result

Tom_0-1719328597890.png

 

jdveerapaneni
Calcite | Level 5
Thanks so much . I will work on this , can you also let me know if there is way to do when we don't know the column names? I have more than 100 columns in 1 sheet and it will be varying based on the projects.
Quentin
Super User

100 columns is a pain to work with.  I would probably transpose the data to have one record per SSN-VariableName-Value.  That will make it easy to check for each SSN-VariableName whether the two values match or not.  Probably better to keep numeric and character values separate, so SSN-VariableName-NumericValue-CharacterValue.  

 

Then to make the wide report, you can either transpose back to wide format, or use some fancy PROC REPORT across variable or whatever.

 

The other option would be to do it with arrays or macros, but it gets loopy.

BASUG is hosting free webinars Next up: Mike Raithel presenting on validating data files on Wednesday July 17. Register now at the Boston Area SAS Users Group event page: https://www.basug.org/events.
Tom
Super User Tom
Super User

Just use code generation.

So get the list of variables:

proc contents data=have(drop=ssn) noprint out=contents; run;
proc sort data=contents; by varnum; run;

Then use it to write some code:

filename code temp;

data _null_;
  set contents end=eof;
  file code;
  if _n_=1 then put
 'data flags;'
/'  set ' libname +(-1) '.' memname ';'
/'  by ssn;'
  ;
  put 'F__' _n_ '=' name 'ne lag(' name ');';
  if eof then put
 '  if last.ssn;'
/'  keep ssn F__: ;'
/'run;'
/'data want;'
/'  merge ' libname +(-1) '.' memname 'flags;'
/'  by ssn;'
/'run;'
  ;
run;

data _null_;
  set contents end=eof;
  file code mod ;
  if _n_=1 then put
 'proc report data=want;'
/'  column ssn f__: ' @
  ;
  put name @ ;
  if eof then put
 ';'
/'  define f__: /  noprint display;'
  ;
run;

data _null_;
  set contents end=eof;
  file code mod;
  put 
 '  compute ' name ';'
/'    if f__' _n_ 'then call define(_col_, "style", "style=[color=blue]");'
/'  endcomp;'
  ;
  if eof then put
 'run;'
  ;
run;

Then run the code:

%include code / source2;

Result:

67  +data flags;
68  +  set WORK.HAVE ;
69  +  by ssn;
70  +F__1 =firstname ne lag(firstname );
71  +F__2 =lastname ne lag(lastname );
72  +F__3 =empid ne lag(empid );
73  +F__4 =address ne lag(address );
74  +F__5 =city ne lag(city );
75  +F__6 =state ne lag(state );
76  +F__7 =zip ne lag(zip );
77  +  if last.ssn;
78  +  keep ssn F__: ;
79  +run;

NOTE: There were 6 observations read from the data set WORK.HAVE.
NOTE: The data set WORK.FLAGS has 3 observations and 8 variables.
NOTE: DATA statement used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds


80  +data want;
81  +  merge WORK.HAVE flags;
82  +  by ssn;
83  +run;

NOTE: There were 6 observations read from the data set WORK.HAVE.
NOTE: There were 3 observations read from the data set WORK.FLAGS.
NOTE: The data set WORK.WANT has 6 observations and 15 variables.
NOTE: DATA statement used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds


84  +proc report data=want;
85  +  column ssn f__: firstname lastname empid address city state zip ;
86  +  define f__: /  noprint display;
87  +  compute firstname ;
88  +    if f__1 then call define(_col_, "style", "style=[color=blue]");
89  +  endcomp;
90  +  compute lastname ;
91  +    if f__2 then call define(_col_, "style", "style=[color=blue]");
92  +  endcomp;
93  +  compute empid ;
94  +    if f__3 then call define(_col_, "style", "style=[color=blue]");
95  +  endcomp;
96  +  compute address ;
97  +    if f__4 then call define(_col_, "style", "style=[color=blue]");
98  +  endcomp;
99  +  compute city ;
100 +    if f__5 then call define(_col_, "style", "style=[color=blue]");
101 +  endcomp;
102 +  compute state ;
103 +    if f__6 then call define(_col_, "style", "style=[color=blue]");
104 +  endcomp;
105 +  compute zip ;
106 +    if f__7 then call define(_col_, "style", "style=[color=blue]");
107 +  endcomp;
108 +run;

NOTE: There were 6 observations read from the data set WORK.WANT.
NOTE: PROCEDURE REPORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.00 seconds

jdveerapaneni
Calcite | Level 5

Thanks so much. It worked, i used macro to create multiple sheets with different columns with the above dynamic code .Only this is its taking so much time when there is more data.

 

ex- it took 25minutes to process 60k rows.

 

sorry for the delayed response, i was sick so unable to test the code earlier.

Quentin
Super User

Agree with others, I would do all the logic / crunching in SAS, and just right the report to Excel with traffic lighting.  I wouldn't use VBA, it only adds complexity.

 

What is the logic for the comparison, is it just to highlight any values that are not constant within a group of records with a single SSN? Or in other words, for every variable there should be only one distinct value within an SSN group?  Do you always have two records per SSN, or could there be more than two?

BASUG is hosting free webinars Next up: Mike Raithel presenting on validating data files on Wednesday July 17. Register now at the Boston Area SAS Users Group event page: https://www.basug.org/events.
jdveerapaneni
Calcite | Level 5
Yes It would make my life easy if I can do the highlight using proc report instead of vba macro.
Yes SSN is the key and will definitely have only 2 records per SSN, not more than that.other column names cannot be determined, because sometimes one project may have 3 address columns but other project have only 1 address columns(just an example). I used _all_ while generating exxel using proc report .
It would be very helpful if I get the compute logic to compare rows based on ssn.
Ksharp
Super User

The following code is I wrote before to compare two SAS database to check the difference of row between two tables (they have the same table name,but in different SAS database). 

You need to transform my code to your case,since mine is coding for CDISC standard.

 

%let old_data=D:\XiaKeShan\listing编程需求\LKM-2023-BCG01_study_data_sas_20240117134719\dataset   ;   *the path for old database;
%let new_data=D:\XiaKeShan\listing编程需求\LKM-2023-BCG01_study_data_sas_20240129111311\dataset   ;   *the path for new database;

%let out= D:\XiaKeShan\MM listing编程需求 ;   /*the path of output excel file (want.xlsx)*/


%let subjid=subject_code;   *the subject id variable which is unique in all table. 注意:所有的数据集中是一样的,且值是唯一的;
%let drop= SITE_NAME VERSION_NAME PI_NAME USERNAME SUBMIT_TIME UPDATE_USER UPDATE_TIME ;   *the variables you need to drop from all tables  需要去掉的变量名;





















options validvarname=any validmemname=extend mrecall nofmterr nonumber nodate dkricond=nowarn dkrocond=nowarn;

/*******比较 前一次数据 和 新数据********/
libname old v9 "&old_data." access=readonly;
libname new v9 "&new_data." access=readonly;

%macro type_one(idx=,dsn=,title=);
proc datasets library=work kill nolist nodetails;quit;
proc sort data=old.&dsn.(drop=&drop.) out=old;by  &subjid.  ;run;
proc sort data=new.&dsn.(drop=&drop.) out=new;by  &subjid.  ;run;
proc compare data=old compare=new noprint out=diff_&dsn.;
id &subjid.;
run;
data call_define;
 set diff_&dsn.(drop=_TYPE_ _OBS_);
 retain _dummy_ .;
 array n{*} _numeric_;
 array c{*} _character_;
 length vname $ 40;
 do i=1 to dim(n);
   if n{i} not in (. 0) then do;vname=vname(n{i}); if upcase(vname) not in ("%upcase(&subjid.)") then output;end;
 end;
 do i=1 to dim(c);
   if findc(c{i},'X') then do;vname=vname(c{i}); if upcase(vname) not in ("%upcase(&subjid.)") then output;end;
 end;
keep &subjid. vname;
run;
filename t temp;
data _null_;
 set call_define;
 file t;
/* put 'if &subjid.="' &subjid. '" then call define("' vname '","style","style={background=yellow}");';*/
 put "if &subjid.='" &subjid. "' then call define('" vname "','style','style={background=yellow}');";
run;
data &dsn.;
if _n_=1 then do;
 length new_change $ 40;
 if 0 then set old.&dsn.;
 declare hash h(dataset:"old.&dsn.");
 h.definekey("&subjid.");
 h.definedone();

 declare hash h1(dataset:'call_define');
 h1.definekey("&subjid.");
 h1.definedone();
end;
 set new.&dsn.;
 new_change='old' ;
 if h.check() ne 0 then new_change='new' ;
 if h1.check() = 0 then new_change='change' ;
label new_change='数据状态';
run;
/*ods excel file="&out.\&idx..&dsn..xlsx" options(sheet_name="&dsn." autofilter='all' ) ;*/
ods excel options(sheet_name="&title."  Embedded_Titles='yes' autofilter='all' ) ;
title j=l link="#目录!A1"  "(*ESC*)S={textdecoration=underline color=blue }返回目录";
proc report data=&dsn. split='*'  nowd;
column _all_ dummy;
define _all_/display;
define dummy/computed noprint;
compute dummy;
%include t;
endcomp;
run;
/*ods excel close;*/
%mend;

%macro type_two(idx=,dsn=,key=,title=);
proc datasets library=work kill nolist nodetails;quit;
proc sort data=old.&dsn.(drop=&drop.) out=old;by  &subjid. &key. ;run;
proc sort data=new.&dsn.(drop=&drop.) out=new;by  &subjid. &key. ;run;
proc compare data=old compare=new noprint out=diff_&dsn.;
id &subjid. &key. ;
run;
data call_define;
 set diff_&dsn.(drop=_TYPE_ _OBS_);
 retain _dummy_ .;
 array n{*} _numeric_;
 array c{*} _character_;
 length vname $ 40;
 do i=1 to dim(n);
   if n{i} not in (. 0) then do;vname=vname(n{i});if upcase(vname) not in ("%upcase(&subjid.)" "%upcase(&key.)") then output;end;
 end;
 do i=1 to dim(c);
   if findc(c{i},'X') then do;vname=vname(c{i});if upcase(vname) not in ("%upcase(&subjid.)" "%upcase(&key.)") then output;end;
 end;
keep &subjid. &key. vname;
run;
filename t temp;
data _null_;
 set call_define;
 file t;
 put "if &subjid.='" &subjid. "' and &key.='" &key. "' then call define('" vname "','style','style={background=yellow}');";
run;
data &dsn.;
if _n_=1 then do;
 length new_change $ 40;
 if 0 then set new.&dsn.;
 if 0 then set old.&dsn.;
 declare hash h(dataset:"old.&dsn.");
 h.definekey("&subjid.","&key.");
 h.definedone();

 declare hash h1(dataset:'call_define');
 h1.definekey("&subjid.","&key.");
 h1.definedone();
end;
 set new.&dsn.;
 new_change='old' ;
 if h.check() ne 0 then new_change='new' ;
 if h1.check() = 0 then new_change='change' ;
label new_change='数据状态';
run;
/*ods excel file="&out.\&idx..&dsn..xlsx" options(sheet_name="&dsn." autofilter='all' ) ;*/
ods excel options(sheet_name="&title."  Embedded_Titles='yes' autofilter='all' ) ;
title j=l link="#目录!A1"  "(*ESC*)S={textdecoration=underline color=blue }返回目录";
proc report data=&dsn. split='*'  nowd;
column _all_ dummy;
define _all_/display;
define dummy/computed noprint;
compute dummy;
%include t;
endcomp;
run;
/*ods excel close;*/
%mend;


%macro type_three(idx=,dsn=,key=,key2=,title=);
%local  value lower  upper ;
%if %upcase(%substr(&dsn.,1,2))=LB %then %do;
proc sql noprint;
select name into :value trimmed from dictionary.columns where libname='OLD' and memname="%upcase(&dsn.)" and label='检查结果';
select name into :lower trimmed from dictionary.columns where libname='OLD' and memname="%upcase(&dsn.)" and label='正常值下限';
select name into :upper trimmed from dictionary.columns where libname='OLD' and memname="%upcase(&dsn.)" and label='正常值上限';
quit;
%put &=value.  &=lower. &=upper.;
%end;

proc datasets library=work kill nolist nodetails;quit;
proc sort data=old.&dsn.(drop=&drop.) out=old;by  &subjid. &key.  &key2.;run;
proc sort data=new.&dsn.(drop=&drop.) out=new;by  &subjid. &key.  &key2.;run;
proc compare data=old compare=new noprint out=diff_&dsn.;
id &subjid. &key.  &key2.;
run;
data call_define;
 set diff_&dsn.(drop=_TYPE_ _OBS_);
 retain _dummy_ .;
 array n{*} _numeric_;
 array c{*} _character_;
 length vname $ 40;
 do i=1 to dim(n);
   if n{i} not in (. 0) then do;vname=vname(n{i});if upcase(vname) not in ("%upcase(&subjid.)" "%upcase(&key.)" "%upcase(&key2.)") then output;end;
 end;
 do i=1 to dim(c);
   if findc(c{i},'X') then do;vname=vname(c{i});if upcase(vname) not in ("%upcase(&subjid.)" "%upcase(&key.)" "%upcase(&key2.)") then  output;end;
 end;
keep &subjid. &key. &key2. vname;
run;
filename t temp;
data _null_;
 set call_define;
 file t;
 put "if &subjid.='" &subjid. "' and &key.='" &key. "' and  &key2.='" &key2. "' then call define('" vname "','style','style={background=yellow}');";
run;
data &dsn.;
if _n_=1 then do;
 length new_change $ 40;
 if 0 then set old.&dsn.;
 declare hash h(dataset:"old.&dsn.");
 h.definekey("&subjid.","&key.","&key2.");
 h.definedone();

 declare hash h1(dataset:'call_define');
 h1.definekey("&subjid.","&key.","&key2.");
 h1.definedone();
end;
 set new.&dsn.;
 new_change='old' ;
 if h.check() ne 0 then new_change='new' ;
 if h1.check() = 0 then new_change='change' ;
label new_change='数据状态';


%if %upcase(%substr(&dsn.,1,2))=LB %then %do;
_value=input(&value.,?? best.);
_lower=input(&lower.,?? best.);
_upper=input(&upper.,?? best.);
if not missing(_value) and not missing(_lower) then do; if _value<_lower then &value.=catx(' ',&value.,'-');  end;
if not missing(_value) and not missing(_upper) then do; if _value>_upper then &value.=catx(' ',&value.,'+');  end;
drop _value _lower _upper;
%end;
run;
/*ods excel file="&out.\&idx..&dsn..xlsx" options(sheet_name="&dsn." autofilter='all' ) ;*/
ods excel options(sheet_name="&title."  Embedded_Titles='yes' autofilter='all' ) ;
title j=l link="#目录!A1"  "(*ESC*)S={textdecoration=underline color=blue }返回目录";
proc report data=&dsn. split='*'  nowd;
column _all_ dummy;
define _all_/display;
define dummy/computed noprint;
compute dummy;
%include t;
endcomp;
run;
/*ods excel close;*/
%mend;


 




/********  
注意: 
1)目录的值和宏参数(title=)的值保持一致 。
2)目录的值不能包括 /\*~ 等非法字符,因为Sheet名无法显示这些字符。
********/
data 目录;
infile cards truncover expandtabs;
input 序号	目录 $80.;
cards;
1	标题
2	签署知情同意书
3	访视日期
4	人口学资料
5	非膀胱癌既往病史-手术史问询
6	非膀胱癌既往病史-手术史
7	过敏史
8	一般问询
9	膀胱癌病史
10	膀胱癌既往治疗史问询
11	膀胱癌既往治疗史
12	体格检查
13	生命体征问询
14	生命体征
15	ECOG评分
16	胸部X线片
17	超声心动图
18	十二导联心电图
19	C-TST试验
20	血妊娠试验
21	血常规
22	尿常规
23	血生化
24	肌酐
25	凝血功能
26	传染病筛查
27	泌尿系统彩超
28	影像学检查
29	入选排除标准问询
30	入选排除标准
31	筛选结果
32	给药记录表(1周1次)
33	PK采血
34	细胞因子血样采集
35	细胞因子尿样采集
36	药物脱落情况尿样采集
37	不良事件问询
38	不良事件
39	既往或合并用药问询
40	既往或合并用药
41	既往或合并非药物治疗问询
;

ods noresults;
ods _all_ close;
ods excel file="&out.\want.xlsx" ;
ods excel options(sheet_name="目录"  Embedded_Titles='yes' ) ;
title "医学监查数据审核表";
proc report data=目录 split='*' nowd;
compute 目录;
 call define(_col_,'url',cats('#''',目录,'''!A1') );
 call define(_col_,'style','style={textdecoration=underline color=blue}');
endcomp;
run;

%type_one(idx=1,dsn=PRIMARY,title=标题)
%type_one(idx=2,dsn=DS,title=签署知情同意书)
%type_two(idx=3,dsn=SV1,key=folder_name,title=访视日期)
%type_one(idx=4,dsn=DM,title=人口学资料)
%type_one(idx=5,dsn=MH1CO ,title=非膀胱癌既往病史-手术史问询)
%type_two(idx=6,dsn=MH1,key=spid,title=非膀胱癌既往病史-手术史)
%type_one(idx=7,dsn=MH2,title=过敏史)
%type_one(idx=8,dsn=SU,title=一般问询)
%type_one(idx=9,dsn=MH3,title=膀胱癌病史)
%type_one(idx=10,dsn=MH4CO,title=膀胱癌既往治疗史问询)
%type_two(idx=11,dsn=MH4,key=spid,title=膀胱癌既往治疗史)
%type_three(idx=12,dsn=PE,key=folder_name,key2=OID,title=体格检查)
%type_two(idx=13,dsn=VSCO,key=folder_name ,title=生命体征问询)
%type_three(idx=14,dsn=VS,key=spid,key2=OID,title=生命体征)
%type_two(idx=15,dsn=QS,key=folder_name,title=ECOG评分)
%type_two(idx=16,dsn=FA1,key=folder_name,title= 胸部X线片)
%type_two(idx=17,dsn=FA2,key=folder_name,title=超声心动图)
%type_two(idx=18,dsn=EG,key=folder_name,title=十二导联心电图)
%type_two(idx=19,dsn=TST,key=folder_name,title=C-TST试验)
%type_three(idx=20,dsn=LBHCG,key=folder_name,key2=OID ,title=血妊娠试验)
%type_three(idx=21,dsn=LBBR,key=folder_name,key2=OID,title=血常规)
%type_three(idx=22,dsn=LBUR,key=folder_name,key2=OID,title=尿常规)
%type_three(idx=23,dsn=LBBB,key=folder_name,key2=OID,title=血生化)
%type_three(idx=24,dsn=LBSCR,key=folder_name,key2=OID,title=肌酐)
%type_three(idx=25,dsn=LBCG,key=folder_name,key2=OID,title=凝血功能)
%type_two(idx=26,dsn=IFD,key=folder_name,title=传染病筛查)
%type_three(idx=27,dsn=FA3,key=folder_name,key2=OID,title=泌尿系统彩超)
%type_two(idx=28,dsn=FA4,key=folder_name,title=影像学检查)
%type_two(idx=29,dsn=IECO,key=folder_name,title=入选排除标准问询)
%type_two(idx=30,dsn=IE,key=spid,title=入选排除标准)
%type_one(idx=31,dsn=DS1 ,title=筛选结果)
%type_two(idx=32,dsn=EX1,key=OID,title=给药记录表(1周1次))
%type_two(idx=33,dsn=PC,key=OID ,title=PK采血)
%type_two(idx=34,dsn=CB,key=OID,title=细胞因子血样采集)
%type_two(idx=35,dsn=CU,key=OID,title=细胞因子尿样采集)
%type_two(idx=36,dsn=MU,key=OID,title=药物脱落情况尿样采集)
%type_one(idx=37,dsn=AECO,title=不良事件问询)
%type_two(idx=38,dsn=AE,key=spid,title=不良事件)
%type_one(idx=39,dsn=CMCO,title=既往或合并用药问询)
%type_two(idx=40,dsn=CM,key=spid,title=既往或合并用药)
%type_one(idx=41,dsn=CM1CO,title=既往或合并非药物治疗问询)

ods excel close;


 

 

Ready to join fellow brilliant minds for the SAS Hackathon?

Build your skills. Make connections. Enjoy creative freedom. Maybe change the world. Registration is now open through August 30th. Visit the SAS Hackathon homepage.

Register today!
How to Concatenate Values

Learn how use the CAT functions in SAS to join values from multiple variables into a single value.

Find more tutorials on the SAS Users YouTube channel.

Click image to register for webinarClick image to register for webinar

Classroom Training Available!

Select SAS Training centers are offering in-person courses. View upcoming courses for:

View all other training opportunities.

Discussion stats
  • 15 replies
  • 758 views
  • 5 likes
  • 6 in conversation