I need to produce a report and used the PROC Tabulate in SAS.The Code I used produce the report with Sub_LOB, Group and Mat_Month and the totals column. With in the Mat_Month there are three sub-columns (Dec 16, Jan17 and Feb17).I wrote the code but it produce the columns in order like Dec 16,Feb17 and Jan17) which is not I wanted. Also, I need one empty row for the group named "CAROLINA GROUP" but the complete row disappears since there are now data in that row. Is there any way we can produce the sub columns in the same way I wanted. Also, is it possible to get the row though it has no values now but can have the values in the future.The code I used are as:
PROC Tabulate
DATA= T_Final_Summary Format=Comma12. ;
VAR Comm Net_Bal;
Class Mat_Month / ORDER=Unformatted MISSING;
Class Sub_LOB /ORDER=Unformatted MISSING;
Class Group /ORDER= Unformatted MISSING;
TABLE /*Row Dimension*/
Sub_LOB={LABEL= “ “} *
(Group={LABEL=” “}
ALL={LABEL=”Grand Total”})
ALL={LABEL=”Grand Total},
/*Column Dimension*/
Mat_Month *(
Comm={LABEL=”Count of Comm} *N={LABEL=” “}
Comm={LABEL=”Sum of Comm} *Sum={LABEL=” “}
Net_Bal={LABEL=”Count of Net Bal”}*N={LABEL=” “}
Net_Bal ={LABEL=”Sum of Net Bal”}*Sum={LABEL=”Sum of Net Bal”})
ALL={LABEL=”Grand Total}*(
Comm={LABEL=”Total Count of Comm} *N={LABEL=” “}
Comm={LABEL=”Total Sum of Comm} *Sum={LABEL=” “}
Net_Bal={LABEL=”Total Count of Net Bal”}*N={LABEL=” “}
Net_Bal ={LABEL=”Total Sum of Net Bal”}*Sum={LABEL=”Sum of Net Bal”})
/*Table Options*/
/BOX=(LABEL=”Sub Lob/Group”} Missing =”0”;
RUN;
Any help will be very much appreciated.
Regarding the order of the variable, it's sorting alphabetically. The variable in MAT_MONTH needs to be an actual SAS date to have it sort accordingly, which would mean numeric with a date format (MONYY5). You'll need to do the conversion before the PROC TABULATE step.
Then replace mat_month in your proc tabulate with the mat_month_date variable.
data want;
set have;
mat_month_date=input(have, anydtdte.);
format want monyy5.;
run;
Related
I have the following piece of result, which i need to add. Seems like a simple request, but i have spent a few days already trying to find the solution to this problem.
Data have:
Measure Jan_total Feb_total
Startup 100 200
Switcher 300 500
Data want:
Measure Jan_total Feb_total
Startup 100 200
Switcher 300 500
Total 400 700
I want individually placed vertical sum results of each column under the respective column please.
Can someone help me arrive at the solution for this request, please?
To do this in data step code, you would do something like:
data want;
set have end=end; * Var 'end' will be true when we get to the end of 'have'.;
jan_sum + jan_total; * These 'sum statements' accumulate the totals from each observation.;
feb_sum + feb_total;
output; * Output each of the original obbservations.;
if end then do; * When we reach the end of the input...;
measure = 'Total'; * ...update the value in Measure...;
jan_total = jan_sum; * ...move the accumulated totals to the original vars...;
feb_total = feb_sum;
output; * ...and output them in an additional observation.
end;
drop jan_sum feb_sum; * Get rid of the accumulator variables (this statement can go anywhere in the step).;
run;
You could do this many other ways. Assuming that you actually have columns for all the months, you might re-write the data step code to use arrays, or you might use PROC SUMMARY or PROC SQL to calculate the totals and add the resulting totals back using a much shorter data step, etc.
proc means noprint
data = have;
output out= want
class measure;
var Jan_total Feb_total;
run;
It depends on if this is for display or for a data set. It usually makes no sense to have a total in the data set and it's just used for reporting.
PROC PRINT has a SUM statement that will add the totals to the end of a report. PROC TABULATE also provides another mechanism for reporting like this.
example from here.
options obs=10 nobyline;
proc sort data=exprev;
by sale_type;
run;
proc print data=exprev noobs label sumlabel
n='Number of observations for the order type: '
'Number of observations for the data set: ';
var country order_date quantity price;
label sale_type='Sale Type'
price='Total Retail Price* in USD'
country='Country' order_date='Date' quantity='Quantity';
sum price quantity;
by sale_type;
format price dollar7.2;
title 'Retail and Quantity Totals for #byval(sale_type) Sales';
run;
options byline;
Results:
I have the following problem. I need to run PROC FREQ on multiple variables, but I want the output to all be on the same table. Currently, a PROC FREQ statement with something like TABLES ERstatus Age Race, InsuranceStatus; will calculate frequencies for each variable and print them all on separate tables. I just want the data on ONE table.
Any help would be appreciated. Thanks!
P.S. I tried using PROC TABULATE, but it didn't not calculate N correctly, so I'm not sure what I did wrong. Here is my code for PROC TABULATE. My variables are all categorical, so I just need to know N and percentages.
PROC TABULATE DATA = BCanalysis;
CLASS ERstatus PRstatus Race TumorStage InsuranceStatus;
TABLE (ERstatus PRstatus Race TumorStage) * (N COLPCTN), InsuranceStatus;
RUN;
The above code does not return the correct frequencies based on InsuranceStatus where 0 = insured and 1 = uninsured, but PROC FREQ does. Also doesn't calculate correctly with ROWPCTN. So any way that I can get PROC FREQ to calculate multiple variables on one table, or PROC TABULATE to return the correct frequencies, would be appreciated.
Here is a nice image of my output in a simplified analysis of only ERstatus and InsuranceStatus. You can see that PROC FREQ returns 204 people with an ERstatus of 1 and InsuranceStatus of 1. That's correct. The values in PROC TABULATE are not.
OUTPUT
I'll answer this separately as this is answering the other possible interpretation of the question; when it's clarified I'll delete one or the other.
If you want this in a single printed table, then you either need to use proc tabulate or you need to normalize your data - meaning put it in the form of variable | value. PROC FREQ is not capable of doing multiple one-way frequencies in a single table.
For PROC TABULATE, likely your issue is missing data. Any variable that is on the class statement will be checked for missingness, and if any rows are missing data for any of the class variables, those rows are entirely excluded from the tabulation for all variables.
You can override this by adding the missing option on the class statement, or in the table statement, or in the proc tabulate statement. So:
PROC TABULATE DATA = BCanalysis;
CLASS ERstatus PRstatus Race TumorStage InsuranceStatus/missing;
TABLE (ERstatus PRstatus Race TumorStage) * (N COLPCTN), InsuranceStatus;
RUN;
This will result in a slightly different appearance than on your table, though, as it will include the missing rows in places you probably do not want them, and they'll be factored against the colpctn when again you probably don't want them.
Typically some manipulation is then necessary; the easiest is to normalize your data and then run a tabulation (using PROC TABULATE or PROC FREQ, whichever is more appropriate; TABULATE has better percentaging options though) against that normalized dataset.
Let's say we have this:
data class;
set sashelp.class;
if _n_=5 then call missing(age);
if _n_=3 then call missing(sex);
run;
And we want these two tables in one table.
proc freq data=class;
tables age sex;
run;
If we do this:
proc tabulate data=class;
class age sex;
tables (age sex),(N colpctn);
run;
Then we get an N=17 total for both subtables - that's not what we want, we want N=18. Then we can do:
proc tabulate data=class;
class age sex/missing;
tables (age sex),(N colpctn);
run;
But that's not quite right either; I want F to have 8/18 = 44.44% and M 10/18 = 55.55%, not 42% and 53% with 5% allocated to the missing row.
The way I do this is to normalize the data. This means you get a dataset with 2 variables, varname and val, or whatever makes sense for your data, plus whatever identifier/demographic/whatnot variables you might have. val has to be character unless all of your values are numeric.
So for example here I normalize class with age and sex variables. I don't keep any identifiers, but you certainly could in your data, I imagine InsuranceStatus would be kept there if I understand what you're doing in that table. Once I have the normalized table, I just use those two variables, and carefully construct a denominator definition in proc tabulate to have the right basis for my pctn value. It's not quite the same as the single table before - the variable name is in its own column, not on top of the list of values - but honestly that looks better in my opinion.
data class_norm;
set class;
length val $2;
varname='age';
val=put(age,2. -l);
if not missing(age) then output;
varname='sex';
val=sex;
if not missing(sex) then output;
keep varname val;
run;
proc tabulate data=class_norm;
class varname val;
tables varname=' '*val=' ',n pctn<val>;
run;
If you want something better than this, you'll probably have to construct it in proc report. That gives you the most flexibility, but is the most onerous to program in also.
You can use ODS OUTPUT to get all of the PROC FREQ output to one dataset.
ods output onewayfreqs=class_freqs;
proc freq data=sashelp.class;
tables age sex;
run;
ods output close;
or
ods output crosstabfreqs=class_tabs;
proc freq data=sashelp.class;
tables sex*(height weight);
run;
ods output close;
Crosstabfreqs is the name of the cross-tab output, while one-way frequencies are onewayfreqs. You can use ods trace to find out the name if you forget it.
You may (probably will) still need to manipulate this dataset some to get the structure you want ultimately.
I am trying to output a three way frequency table. I am able to do this (roughly) with proc freq, but would like the control for variable to be joined. I thought proc tabulate would be a good way to customize the output. Basically I want to fill in the cells with frequency, and then customize the percents at a later time. So, have count and column percent in each cell. Is that doable with proc tabulate?
Right now I have:
proc freq data=have;
table group*age*level / norow nopercent;
run;
that gives me e.g.:
What I want:
Here is the code I am using:
proc tabulate data=ex1;
class age level group;
var age;
table age='Age Category',
mean=' '*group=''*level=''*F=10./ RTS=13.;
run;
Thanks!
You can certainly get close to that. You can't really get in 'one' cell, it needs to write each thing out to a different cell, but theoretically with some complex formatting (probably using CSS) you could remove the borders.
You can't use VAR and CLASS together, but since you're just doing percents, you don't need to use MEAN - you should just use N and COLPCTN. If you're dealing with already summarized data, you may need to do this differently - if so then post an example of your dataset (but that wouldn't work in PROC FREQ either without a FREQ statement).
data have;
do _t = 1 to 100;
age = ceil(3*rand('Uniform'));
group = floor(2*rand('Uniform'));
level = floor(5*rand('Uniform'));
output;
end;
drop _t;
run;
proc tabulate data=have;
class age level group;
table age='Age Category',
group=''*level=''*(n='n' colpctn='p')*F=10./ RTS=13.;
run;
This puts N and P (n and column %) in separate adjacent cells inside a single level.
I've been trying to make my code more efficient and this is the original code, but I think it can be written in one step.
data TABLE;set ORIGINAL_DATA;
Multi=percent*total_units;
keep Multi Type;
proc sort; by Type;
proc means noprint data=TABLE1; by Type; var Multi;output out=Table2(drop= _type_ _freq_)sum=Multi;run;
proc means noprint data=Table1; var Multi;output out=Table3(drop= _type_ _freq_) sum=total ;run;
proc sql;
create table TABLE4as
select a.Type, a.Multi label="Multi", b.total label="total"
from TABLE2 a, TABLE3 b
order by Type;
quit;
data TABLE5;set TABLE4;
pct=(MULTI/total)*100;
run;
I am able to split up part of it, but I can't figure out how to get the PCT part in my code. This is what I have.
proc sql;
create table TABLE1 as
select distinct type, sum(percent*total_units) as MULTI label "MULTI",
MULTI/(percent*total_units)) as PCT
from ORIGINAL_DATA
group by type;
quit;
I had to edit some of the code but I think the general idea should make sense.
The main problem is I cannot call upon the MULTI column because it is just being created but I want to create a percentage of the total for each type.
The "SAS" way to do something like this is to use a CLASS statement with PROC MEANS. That will calculate statistics on all the interaction levels in the data (identified by the TYPE variable). The row where TYPE=0 will be the "total" value, representing the value of that statistic for the entire data set.
In your case, we can take advantage of the fact that PROC MEANS will create the output data set sorted by TYPE and by the variables listed in the CLASS statement. That means we can just read the first observation and save it's value for calculating percentages.
It's probably easier to just show some code:
data TABLE;
set ORIGINAL_DATA;
Multi = percent * total_units;
keep Multi Type;
run;
proc means noprint data=TABLE;
class Type;
var multi;
output out=next sum=;
run;
data want;
retain total;
set next;
if _n_ = 1 then do;
/* The first obs will be the _TYPE_=0 record */
total = multi;
delete;
end;
pct = (multi / total) * 100;
drop total _freq_ _type_;
run;
Notice that you do not need to sort the data before using PROC MEANS. That's because we are using a CLASS statement rather than a BY statement. The data step is using the first observation in the data set created by MEANS (the TYPE=0 record) to retain the total sum of your variable. The delete statement keeps it out of the result.
CLASS statements with PROC MEANS are very useful. Take a few minutes to read up on how the TYPE variable is calculated, especially if you try using more than one class variable.
You can skip the initial data step by using the WEIGHT option in VAR statement of PROC MEANS (this will effectively do the multiplication for you). You can also use PROC TABULATE instead of PROC MEANS, as tabulate can calculate the percentage. I believe the following code will produce your required output in one go.
ods noresults;
proc tabulate data=have out=want (drop=_: rename=(total_units_sum=total total_units_pctsum_0=pct));
class type;
var total_units / weight=percent;
table type, total_units*(sum pctsum);
run;
ods results;
If you need one step, maybe this will work, but it's not actually efficient, since it processes data twice, once for detail by TYPE, once for total.
proc sql;
create table TABLE1 as
select
d.type
, sum(d.percent*d.total_units) as MULTI label "MULTI"
, calculated MULTI/s.total as PCT
from ORIGINAL_DATA d,
( select sum(percent*total_units) as total
from ORIGINAL_DATA) s
group by type
;
quit;
For more efficiency, but in more than one steps you could simply replace tables withe views in your original code:
data TABLE; => data TABLE / view=TABLE;
create table TABLE4 => create view TABLE4
So I have multiple continuous variables that I have used proc rank to divide into 10 groups, ie for each observation there is now a "GPA" and a "GRP_GPA" value, ditto for Hmwrk_Hrs and GRP_Hmwrk_Hrs. But for each of the new group columns the values are between 1 - 10. Is there a way to change that value so that rather than 1 for instance it would be 1.2-2.8 if those were the min and max values within the group? I know I can do it by hand using proc format or if then or case in sql but since I have something like 40 different columns that would be very time intensive.
It's not clear from your question if you want to store the min-max values or just format the rank columns with them. My solution below formats the rank column and utilises the ability of SAS to create formats from a dataset. I've obviously only used 1 variable to rank, for your data it will be a simple matter to wrap a macro around the code and run for each of your 40 or so variables. Hope this helps.
/* create ranked dataset */
proc rank data=sashelp.steel groups=10 out=want;
var steel;
ranks steel_rank;
run;
/* calculate minimum and maximum values per rank */
proc summary data=want nway;
class steel_rank;
var steel;
output out=want_min_max (drop=_:) min= max= / autoname;
run;
/* create dataset with formatted values */
data steel_rank_fmt;
set want_min_max (rename=(steel_rank=start));
retain fmtname 'stl_fmt' type 'N';
label=catx('-',steel_min,steel_max);
run;
/* create format from previous dataset */
proc format cntlin=steel_rank_fmt;
run;
/* apply formatted value to rank column */
proc datasets lib=work nodetails nolist;
modify want;
format steel_rank stl_fmt10.;
quit;
In addition to Keith's good answer, you can also do the following:
proc rank data = sashelp.cars groups = 10 out = test;
var enginesize;
ranks es;
run;
proc sql ;
select *, catx('-',min(enginesize), max(enginesize)) as esrange, es from test
group by es
order by make, model
;
quit;