You already asked these same questions: http://communities.sas.com/thread/30965?tstart=0 ... View more

I asked this question in the new SAS Deployment community here is the link: Paul Homes wrote: Hi, In terms of configuration and administration, I would start out by looking in the SAS/ACCESS(R) 9.2 Interface to PC Files: Reference, Second Edition under LIBNAME Statement and Pass-Through Facility on Linux, UNIX, and 64-Bit Microsoft Windows and then PC Files Server Administration. Cheers Paul Resa wrote: In addition to what Paul Homes indicated: From experience please take notice of the following Usage Notes: 35064 Network drives are not recognized by the SAS® PC File Server when the server is installed as a service 41060 The EXCELCS and PCFILES engines do not support the GETNAMES= and MIXED= options The syntax when using EXCELCS is basically as follows: PROC EXPORT         DATA = <SAS Dataset>         OUTFILE = <Excel file>         DBMS = EXCELCS         REPLACE ;     SERVER = <server name> ;     PORT = <portnumber> ;     SSPI = YES ; RUN ; PROC IMPORT         OUT = <SAS Dataset>         DATAFILE = <Excel file>         DBMS = EXCELCS         REPLACE ;     SERVER = <server name> ;     PORT = <portnumber> ;     SSPI = YES ; RUN ; We use SSPI=YES to allow Integrated Windows Authentication as described on this page. http://communities.sas.com/message/104758#104758 ... View more

If I understand this correctly what I have read, I will need to install the PC Files Server onto a machine running windows that has odbc drivers for excel and/or whatever other source I hope to utilize.  Since I have no machines that run windows I suppose I am out of luck on this one at the moment.  Fortuneatly though I was only asking for information purposes and have no need for the functionality at this point ... View more

Art already answered your question in the Stored Process Forum.  This is basically the exact same question... ... View more

I would look into proc template and ods tagsets to create an html document for excel to read. http://support.sas.com/rnd/base/ods/excel/index.html ... View more

Can you provide an example of your data?  What is the problem you are experiencing exactly?  In your code you call two macros: %dropout, %dropwgt, what is their purpose? ... View more

Your question is definitly highly complex.  I have worked at companies who spend hundred of thousands of dollars a year developing and maintaining name cleansing and matching algorithms.  There is nicknaming, abreviations, spelling mistakes, name reversal, gender qualifing, multiple variations of soundexing (just to name a few approaches to consider), not a simple task to accomplish and with only name you will never know that you are not going to merge different people with the same name anyway... ... View more

Are you using 32-bit or 64-bit version of AIX? ... View more

data have; format date eurdfde9.; input date eurdfde9. type $ value type2 name $; cards; 01-Jan-11 a1 10 1 ae 01-Feb-11 a1 10 1 ae 01-Mar-11 a1 10 2 ae 01-Apr-11 a1 10 2 ae 01-Jan-11 A2 5 1 at 01-Feb-11 A2 50 1 at 01-Mar-11 A2 5 2 at 01-Apr-11 A2 50 2 at 01-Jan-11 a3 20 1 au 01-Feb-11 a3 60 1 au 01-Mar-11 a3 20 2 au 01-Apr-11 a3 60 2 au ; run; proc sql; select type, type2, name, sum(value) as total_value    from have   group by type, type2, name; quit;                                              type         type2  name      total_value                                              -----------------------------------------                                              A2               1  at                 55                                              A2               2  at                 55                                              a1               1  ae                 20                                              a1               2  ae                 20                                              a3               1  au                 80                                              a3               2  au                 80 ... View more

Thanks Ksharp for the solution utilizing hash object.  It works well.  Here is another solution: %let v1=play; %let v2=table; data words(keep=word) word1(keep=word link) word2(keep=word link); infile '/usr/share/dict/words' truncover; input word : $45.; output words; array v[2] $ 45 _temporary_ ("&v1" "&v2"); do i=1 to dim(v);   if index(word,trim(v))>0 then    do;     link=tranwrd(word,trim(v),'');     if count(trim(link),' ')<2 then      do;       array l[2] $ 45 _temporary_;       do j=1 to dim(l);        l =scan(trim(link),j,' ');       end;       if length(l[1])>length(l[2]) then link=l[1]; else link=l[2];       if i=1 then output word1; else output word2;      end;           else delete;    end; end; run; proc sql; create table want as select a.link ,a.word as word1 ,b.word as word2    from ( select strip(link) as link ,word             from word1                        where link in ( select word from words ) ) a,         ( select strip(link) as link ,word                         from word2                        where link in ( select word from words ) ) b   where a.link=b.link; quit; My example will not produce the same results.  In my original examples of output I made it seem like the words should follow a pattern where a/b -> ac cb but it was unitentional and my solution above allows for more linkages to be found.  The hash can be modified to meet the same results, I will do it later if I find the time. ... View more

data have; format hold_date date date9.; input date mmddyy10. v_bought; retain hold_date rownum;   if _n_=1 then do; hold_date=date; rownum=1; end;   if hold_date ne date and hold_date ne date+1 then do;    output;      rownum=rownum+1; date=hold_date+1; v_bought=0;    output;   end;   else output;   rownum=rownum+1;   hold_date=date; keep date v_bought rownum; cards; 05/01/2005          7 05/01/2005          2 05/01/2005          8 05/01/2005          1 05/01/2005          7 05/03/2005          6 05/03/2005          2 05/03/2005          4 05/03/2005          1 05/05/2005          4 05/05/2005          8 05/05/2005          8 05/05/2005          8 05/07/2005          8 05/07/2005          7 05/07/2005          5 05/07/2005          7 05/09/2005          9 05/09/2005          2 05/09/2005          2 05/09/2005          3 05/11/2005          4 05/11/2005          8 05/11/2005          1 05/11/2005          6 ; run; proc sql; create table want as select date, sum(v_bought) as v_total    from have   group by date   order by date; quit; proc reg data=have(where=(10<=rownum<=25)); model date=v_bought; run; data have_more; format hold_date date date9.; input date mmddyy10. v_bought; retain hold_date rownum;   if _n_=1 then do; hold_date=date; rownum=1; end;   if hold_date ne date and hold_date ne date+1 then do;    output;      rownum=rownum+1; date=hold_date+1; v_bought=0;    output;   end;   else output;   rownum=rownum+1;   hold_date=date; keep date v_bought rownum; cards; 05/12/2005          7 05/12/2005          5 05/12/2005          8 05/12/2005          6 05/12/2005          5 05/12/2005          9 05/12/2005          7 05/13/2005          5 05/13/2005          1 05/13/2005          6 05/13/2005          6 05/13/2005          5 05/13/2005          7 05/13/2005          4 05/15/2005          8 05/15/2005          5 05/15/2005          3 ; run; proc sql; create table want_more as select date, sum(v_bought) as v_total    from ( select date, v_bought             from have                        where 1<=rownum<=35                        union                       select date, v_bought                         from have_more            where 1<=rownum<=20 )   group by date   order by date; quit; ... View more

The following definitly doesn't work but it may give you or others some ideas.  I am not good with hash objects but I assume my example could be duplicated using one instead of my proc sql to explode the inputed records.  Name matching algorithms are extremly complex and this is just a very dirty, low-quality match assurance test...  In the output of the linkage set you can clearly see some matches are definitly not desireable, but I consider the results good for a few minutes work... data have; input id (namep1-namep2) (:$20.); retain yes 1; cards; 1 Alex Smith 2 Alexander Smith 3 Smith Alex 4 Smith Alexander 5 Matt Roberts 6 Matthew Robertson 7 Robert Matthews 8 Robert Mattherson 9 Matt Thompson 10 Tom Matterhorn 11 Alexis Smith 12 John Smith 13 Smith Alexis ; run; proc sql; create table want as select a.id, compress(a.namep1,,'kw') as namep1, compress(a.namep2,,'kw') as namep2, compress(b.namep1,,'kw') as namep1x, compress(b.namep2,,'kw') as namep2x, b.id as idx    from have a    join have b on a.id lt b.id; quit; data linkage; set want; /*----------------------------------------------*   |  i = ignore case                             |   |  l = remove leading blanks                   |   |  : = truncate to shortest length and compare |   *----------------------------------------------*/   /* get complev of a:a */   complev1=complev(namep1,namep1x,'il');   complev2=complev(namep2,namep2x,'il');   complev1t=complev(namep1,namep1x,'il:');   complev2t=complev(namep2,namep2x,'il:');   avgcomplev_aa=mean(of complev1,complev2,complev1t,complev2t);   if avgcomlev_aa<3 then    do;     complev=avgcomplev_aa;           aa=1;    end;   /* get complev of a:b */   complev1x=complev(namep1,namep2x,'il');   complev2x=complev(namep2,namep1x,'il');   _complev1xt=complev(namep1,namep2x,'il:');   _complev2xt=complev(namep2,namep1x,'il:');   avgcomplev_ab=mean(of complev1x,complev2x,complev1xt,complev2xt);   if avgcomplev_ab<3 then    do;           complev=avgcomplev_ab;           _namep2x=namep2x;           namep2x=namep1x;           namep1x=_namep2x;           aa=0;    end;   if complev<3; keep id idx namep1 namep2 namep1x namep2x complev aa; run; proc print data=linkage; run;                        Obs    id    namep1       namep2       namep1x      namep2x       idx    complev    aa                          1     1    Alex         Smith        Alexander    Smith           2      2.5       1                          2     1    Alex         Smith        Alex         Smith           3      0.0       0                          3     1    Alex         Smith        Alexander    Smith           4      2.5       0                          4     1    Alex         Smith        Alexis       Smith          11      1.0       1                          5     1    Alex         Smith        John         Smith          12      2.0       1                          6     1    Alex         Smith        Alexis       Smith          13      1.0       0                          7     2    Alexander    Smith        Alex         Smith           3      2.5       0                          8     2    Alexander    Smith        Alexander    Smith           4      0.0       0                          9     2    Alexander    Smith        Alexis       Smith          11      2.5       1                         10     2    Alexander    Smith        Alexis       Smith          13      2.5       0                         11     3    Smith        Alex         Smith        Alexander       4      2.5       1                         12     3    Smith        Alex         Smith        Alexis         11      1.0       0                         13     3    Smith        Alex         Smith        John           12      2.0       0                         14     3    Smith        Alex         Smith        Alexis         13      1.0       1                         15     4    Smith        Alexander    Smith        Alexis         11      2.5       0                         16     4    Smith        Alexander    Smith        Alexis         13      2.5       1                         17     5    Matt         Roberts      Matthew      Robertson       6      2.5       1                         18     5    Matt         Roberts      Matthews     Robert          7      2.5       0                         19     6    Matthew      Robertson    Matthews     Robert          7      2.0       0                         20     7    Robert       Matthews     Robert       Mattherson      8      1.5       1                         21    11    Alexis       Smith        Alexis       Smith          13      0.0       0 ... View more