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    <title>topic How to create a table of nested values and percentages in SAS Procedures</title>
    <link>https://communities.sas.com/t5/SAS-Procedures/How-to-create-a-table-of-nested-values-and-percentages/m-p/167947#M43505</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi, I hope I am submitting this correctly and I have tried to format it to be clear and concise. I am trying to create a table using proc tabulate that will contain the counts and percentages of (for example) job applicants, interviewees, and hires. My knowledge of SAS, on a scale of 1 = newbie to 10 = expert, probably about a 3 or 4. I use Base SAS and although I am very open to learning about new things (e.g. sql, proc report, etc), I really would prefer to solve this problem using only Base SAS if possible. I'm totally open to data restructuring ideas. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Say I have the following data: &lt;/P&gt;&lt;P&gt;data job_apps; &lt;/P&gt;&lt;P&gt;input year applied interviewed hired sex $ race $ fem_count min_count; &lt;/P&gt;&lt;P&gt;datalines; &lt;/P&gt;&lt;P&gt;2012&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; M&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; maj&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&lt;/P&gt;&lt;P&gt;2013&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; F&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; maj&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&lt;/P&gt;&lt;P&gt;2014&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; M&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; min&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&lt;/P&gt;&lt;P&gt;2012&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; F&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; maj&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&lt;/P&gt;&lt;P&gt;2013&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; M&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; maj&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&lt;/P&gt;&lt;P&gt;2014&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; F&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; min&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&lt;/P&gt;&lt;P&gt;2012&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; M&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; maj&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&lt;/P&gt;&lt;P&gt;2013&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; F&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; maj&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&lt;/P&gt;&lt;P&gt;2014&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; M&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; min&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&lt;/P&gt;&lt;P&gt;2012&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; F&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; maj&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&lt;/P&gt;&lt;P&gt;; &lt;/P&gt;&lt;P&gt;run; &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;The following table gives me exactly what I want: the counts for applied, interviewed, and hired by year. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Title "All Applied Interviewed Hired."; &lt;/P&gt;&lt;P&gt;proc tabulate data = job_apps format = comma10. out = job_app._counts; &lt;/P&gt;&lt;P&gt;&amp;nbsp; class year&amp;nbsp; / missing; &lt;/P&gt;&lt;P&gt;&amp;nbsp; var&amp;nbsp; applied interviewed hired; &lt;/P&gt;&lt;P&gt;&amp;nbsp; tables (&lt;SPAN style="font-size: 13.3333330154419px;"&gt;applied interviewed hired) * sum, year / row=float misstext = "0" printmiss; &lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp; keylabel n=' ';&lt;/P&gt;&lt;P&gt;run; &lt;/P&gt;&lt;P&gt;Title; &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I would be very happy to have a new dataset (job_app_counts) that looks somewhat like this table, but the output dataset has 9 different values for year, and I can't figure out why. putting "year" in the rows of the table (instead of the columns) seemed to fix this, but when I tried to transpose the resulting dataset, it gave me something where year was now a value of the variables "COL1 COL2 COL3 COL4", which I don't understand. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Next, I want a table for the percentages of all who were interviewed (out of who applied), and all who were hired (out of who was interviewed). I have been trying to follow these instructions (&lt;A href="http://www.pharmasug.org/proceedings/2011/PO/PharmaSUG-2011-PO16.pdf" title="http://www.pharmasug.org/proceedings/2011/PO/PharmaSUG-2011-PO16.pdf"&gt;http://www.pharmasug.org/proceedings/2011/PO/PharmaSUG-2011-PO16.pdf&lt;/A&gt;) but without much luck. I think part of it is that I have the variables in the var statement. This was the only way I could figure out how to get tabulate to compute the counts without deleting the missing values. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN style="font-size: 13.3333330154419px;"&gt;Finally, I want a table for women and minorities who applied interviewed or hired, without showing the men or majority applicants. I can't use a WHERE statement because some women are not minorities, etc. The following table gives me the format I'm looking for except that it shows the missing values. I can't suppress the missing values because then it only gives me the cases where fem_count AND min_count = 1. &lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN style="font-size: 13.3333330154419px;"&gt;&lt;BR /&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;Title "Female &amp;amp; Minority Applied Interviewed Hired"; &lt;/P&gt;&lt;P&gt;proc tabulate data = job_apps format = comma10.; &lt;/P&gt;&lt;P&gt;&amp;nbsp; class fem_count min_count year / missing; &lt;/P&gt;&lt;P&gt;&amp;nbsp; var&amp;nbsp; applied interviewed hired; &lt;/P&gt;&lt;P&gt;&amp;nbsp; tables (fem_count min_count)* ((applied interviewed hired) * sum = "") all = "Total", year all = "Total" / row=float misstext = "0" printmiss; &lt;/P&gt;&lt;P&gt;&amp;nbsp; keylabel n=' ';&lt;/P&gt;&lt;P&gt;run; &lt;/P&gt;&lt;P&gt;Title; &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Thank you for reading. &lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Fri, 13 Feb 2015 15:35:33 GMT</pubDate>
    <dc:creator>shailey</dc:creator>
    <dc:date>2015-02-13T15:35:33Z</dc:date>
    <item>
      <title>How to create a table of nested values and percentages</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/How-to-create-a-table-of-nested-values-and-percentages/m-p/167947#M43505</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi, I hope I am submitting this correctly and I have tried to format it to be clear and concise. I am trying to create a table using proc tabulate that will contain the counts and percentages of (for example) job applicants, interviewees, and hires. My knowledge of SAS, on a scale of 1 = newbie to 10 = expert, probably about a 3 or 4. I use Base SAS and although I am very open to learning about new things (e.g. sql, proc report, etc), I really would prefer to solve this problem using only Base SAS if possible. I'm totally open to data restructuring ideas. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Say I have the following data: &lt;/P&gt;&lt;P&gt;data job_apps; &lt;/P&gt;&lt;P&gt;input year applied interviewed hired sex $ race $ fem_count min_count; &lt;/P&gt;&lt;P&gt;datalines; &lt;/P&gt;&lt;P&gt;2012&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; M&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; maj&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&lt;/P&gt;&lt;P&gt;2013&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; F&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; maj&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&lt;/P&gt;&lt;P&gt;2014&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; M&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; min&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&lt;/P&gt;&lt;P&gt;2012&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; F&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; maj&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&lt;/P&gt;&lt;P&gt;2013&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; M&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; maj&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&lt;/P&gt;&lt;P&gt;2014&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; F&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; min&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&lt;/P&gt;&lt;P&gt;2012&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; M&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; maj&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&lt;/P&gt;&lt;P&gt;2013&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; F&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; maj&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&lt;/P&gt;&lt;P&gt;2014&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; M&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; min&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&lt;/P&gt;&lt;P&gt;2012&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; F&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; maj&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; .&lt;/P&gt;&lt;P&gt;; &lt;/P&gt;&lt;P&gt;run; &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;The following table gives me exactly what I want: the counts for applied, interviewed, and hired by year. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Title "All Applied Interviewed Hired."; &lt;/P&gt;&lt;P&gt;proc tabulate data = job_apps format = comma10. out = job_app._counts; &lt;/P&gt;&lt;P&gt;&amp;nbsp; class year&amp;nbsp; / missing; &lt;/P&gt;&lt;P&gt;&amp;nbsp; var&amp;nbsp; applied interviewed hired; &lt;/P&gt;&lt;P&gt;&amp;nbsp; tables (&lt;SPAN style="font-size: 13.3333330154419px;"&gt;applied interviewed hired) * sum, year / row=float misstext = "0" printmiss; &lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp; keylabel n=' ';&lt;/P&gt;&lt;P&gt;run; &lt;/P&gt;&lt;P&gt;Title; &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I would be very happy to have a new dataset (job_app_counts) that looks somewhat like this table, but the output dataset has 9 different values for year, and I can't figure out why. putting "year" in the rows of the table (instead of the columns) seemed to fix this, but when I tried to transpose the resulting dataset, it gave me something where year was now a value of the variables "COL1 COL2 COL3 COL4", which I don't understand. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Next, I want a table for the percentages of all who were interviewed (out of who applied), and all who were hired (out of who was interviewed). I have been trying to follow these instructions (&lt;A href="http://www.pharmasug.org/proceedings/2011/PO/PharmaSUG-2011-PO16.pdf" title="http://www.pharmasug.org/proceedings/2011/PO/PharmaSUG-2011-PO16.pdf"&gt;http://www.pharmasug.org/proceedings/2011/PO/PharmaSUG-2011-PO16.pdf&lt;/A&gt;) but without much luck. I think part of it is that I have the variables in the var statement. This was the only way I could figure out how to get tabulate to compute the counts without deleting the missing values. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN style="font-size: 13.3333330154419px;"&gt;Finally, I want a table for women and minorities who applied interviewed or hired, without showing the men or majority applicants. I can't use a WHERE statement because some women are not minorities, etc. The following table gives me the format I'm looking for except that it shows the missing values. I can't suppress the missing values because then it only gives me the cases where fem_count AND min_count = 1. &lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN style="font-size: 13.3333330154419px;"&gt;&lt;BR /&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;Title "Female &amp;amp; Minority Applied Interviewed Hired"; &lt;/P&gt;&lt;P&gt;proc tabulate data = job_apps format = comma10.; &lt;/P&gt;&lt;P&gt;&amp;nbsp; class fem_count min_count year / missing; &lt;/P&gt;&lt;P&gt;&amp;nbsp; var&amp;nbsp; applied interviewed hired; &lt;/P&gt;&lt;P&gt;&amp;nbsp; tables (fem_count min_count)* ((applied interviewed hired) * sum = "") all = "Total", year all = "Total" / row=float misstext = "0" printmiss; &lt;/P&gt;&lt;P&gt;&amp;nbsp; keylabel n=' ';&lt;/P&gt;&lt;P&gt;run; &lt;/P&gt;&lt;P&gt;Title; &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Thank you for reading. &lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Fri, 13 Feb 2015 15:35:33 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/How-to-create-a-table-of-nested-values-and-percentages/m-p/167947#M43505</guid>
      <dc:creator>shailey</dc:creator>
      <dc:date>2015-02-13T15:35:33Z</dc:date>
    </item>
    <item>
      <title>Re: How to create a table of nested values and percentages</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/How-to-create-a-table-of-nested-values-and-percentages/m-p/167948#M43506</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Do you want data set's or output to the Result window?&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Using proc tabulate to generate datasets in the format it gets displayed is cumbersome. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;For the first one here's a way to do it, assuming you want a data set. It is a two step process because it requires a transpose. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;proc means data=job_apps noprint nway;&lt;/P&gt;&lt;P&gt;var applied interviewed hired;&lt;/P&gt;&lt;P&gt;class year;&lt;/P&gt;&lt;P&gt;output out=_counts sum= ;&lt;/P&gt;&lt;P&gt;label applied = 'Applied' interviewed='Interviewed' hired='Hired';&lt;/P&gt;&lt;P&gt;run;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;proc transpose data=_counts(drop=_:) out=want1 prefix=Year;&lt;/P&gt;&lt;P&gt;ID year;&lt;/P&gt;&lt;P&gt;run;&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Fri, 13 Feb 2015 17:04:37 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/How-to-create-a-table-of-nested-values-and-percentages/m-p/167948#M43506</guid>
      <dc:creator>Reeza</dc:creator>
      <dc:date>2015-02-13T17:04:37Z</dc:date>
    </item>
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