Obtaining cum. freqs for all possible outcomes in TABLES variable for PROC FREQ

[AvocadoRivalry]

I am trying to build a dataset that shows the cumulative % of "bads" across 10 different buckets using PROC FREQ.  I'm running into a problem for the buckets where there are zero "bads."  SAS outputs what I've labeled below as "Table 1" where what I need is "Table 2."  Basically, the difference that I'm trying to solve is to have SAS output that 80% - 90% bucked and output the same Cumulative Bad % from the bucket above it.  Are there any options in PROC FREQ to do this?  If not, what is the best alternative approach?  Thanks!

TABLE 1:

Percentile	Bads	Cum. Bad %
0 - 10%	5	20.8%
10% - 20%	6	45.8%
20% - 30%	2	54.2%
30% - 40%	1	58.3%
40% - 50%	3	70.8%
50% - 60%	1	75.0%
60% - 70%	2	83.3%
70% - 80%	2	91.7%
90% - 100%	2	100.0%

TABLE 2:

Percentile	Bads	Cum. Bad %
0 - 10%	5	20.8%
10% - 20%	6	45.8%
20% - 30%	2	54.2%
30% - 40%	1	58.3%
40% - 50%	3	70.8%
50% - 60%	1	75.0%
60% - 70%	2	83.3%
70% - 80%	2	91.7%
80% - 90%	0	91.7%
90% - 100%	2	100.0%

[art297]

Take a look at the following SAS-L thread: http://listserv.uga.edu/cgi-bin/wa?A2=ind1107e&L=sas-l&D=0&P=3180

[data_null__]

Another complete example with data.  Uses CLASSDATA option. 

proc rank data=sashelp.heart groups=10 out=smoke;
   var Smoking;
   run;
data class;
   if 0 then set smoke;
   do smoking=0 to 9;
      output;
      end;
   stop;
   run;
proc summary data=smoke nway classdata=class;
   class smoking;
   output out=summary;
   run;
proc freq;
   tables smoking;
   weight _freq_ / zeros;
   run;

          Values of Smoking Were Replaced by Ranks
                                    Cumulative    Cumulative
Smoking    Frequency     Percent     Frequency      Percent
ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ
      0           0        0.00             0         0.00
      1           0        0.00             0         0.00
      2        2501       48.35          2501        48.35
      3           0        0.00          2501        48.35
      4         113        2.18          2614        50.53
      5         466        9.01          3080        59.54
      6         576       11.13          3656        70.67
      7         921       17.80          4577        88.48
      8         125        2.42          4702        90.90
      9         471        9.10          5173       100.00

[AvocadoRivalry]

Easy enough.  Using the preloadfmt / completetypes options in PROC Summary and then running that dataset through PROC Freq seems to get me exactly where I need.  Thanks for the link!