I have a variable with few values for that.
Example: Var1 A,B,C,D,E,F,G,H
How can i find the total 2 letter combinations possible? eg: AB, AC, AD etc.
Here the list i have mentioned is small but in general I have a huge list and need to find total two letter combinations possible with all the values present for the variable. Thanks
A Cartesian join will give you every combination against every combination, so a self join here will give you all possibilities. I usually use Proc SQL:
Proc sql;
create table cartesian1 as
select * from table1,table1;
Quit;
Does this give you the table you want? I'm assuming that you want all 2 letter combinations rather than permutations (i.e. order is not relevant).
data have;
input var1 $;
datalines;
A
B
C
D
E
F
G
H
;
run;
data want;
set have nobs=nobs;
length two_way $2;
do i=_n_+1 to nobs;
set have (rename=(var1=temp)) point=i;
two_way=cats(var1,temp);
keep two_way;
output;
end;
run;
Related
I have the following data:
data df;
input id $ d1 d2 d3;
datalines;
a . 2 3
b . . .
c 1 . 3
d . . .
;
run;
I want to apply some transformation/operation across a subset of columns. In this case, that means dropping all rows where columns prefixed with d are all missing/null.
Here's one way I accomplished this, taking heavy influence from this SO post.
First, sum all numeric columns, row-wise.
data df_total;
set df;
total = sum(of _numeric_);
run;
Next, drop all rows where total is missing/null.
data df_final;
set df_total;
where total is not missing;
run;
Which gives me the output I wanted:
a . 2 3
c 1 . 3
My issue, however, is that this approach assumes that there's only one "primary-key" column (id, in this case) and everything else is numeric and should be considered as a part of this sum(of _numeric_) is not missing logic.
In reality, I have a diverse array of other columns in the original dataset, df, and it's not feasible to simply drop all of them, writing all of that out. I know the columns for which I want to run this "test" all are prefixed with d (and more specifically, match the pattern d<mm><dd>).
How can I extend this approach to a particular subset of columns?
Use a different short cut reference, since you know it all starts with D,
total = sum( of D:);
if n(of D:) = 0 then delete;
Which will add variables that are numeric and start with D. If you have variables you want to exclude that start with D, that's problematic.
Since it's numeric, you can also use the N() function instead, which counts the non missing values in the row. In general though, SAS will do this automatically for most PROCS such as REG/GLM(not in a data step obviously).
If that doesn't work for some reason you can query the list of variables from the sashelp table.
proc sql noprint;
select name into :var_list separated by ", " from sashelp.vcolumn
where libname='WORK' and memname='DF' and name like 'D%';
quit;
data df;
set have;
if n(&var_list.)=0 then delete;
run;
I have a dataset with many columns like this:
ID Indicator Name C1 C2 C3....C90
A 0001 Black 0 1 1.....0
B 0001 Blue 1 0 0.....1
B 0002 Blue 1 0 0.....1
Some of the IDs are duplicates because the indicator is different, but they're essentially the same record. To find duplicates, I want to select distinct ID, Name and then C1 through C90 to check because some claims who have the same Id and indicator have different C1...C90 values.
Is there a way to select c1...c90 either through proc sql or a sas data step? It seems the only way I can think of is to set the dataset and then drop the non essential columns, but in the actual dataset, it's not only Indicator but at least 15 other columns.
It would be nice if PROC SQL used the : variable name wildcard like other Procs do. When no other alternative is reasonable, I usually use a macro to select bulk columns. This might work for you:
%macro sel_C(n);
%do i=1 %to %eval(&n.-1);
C&i.,
%end;
C&n.
%mend sel_C;
proc sql;
select ID,
Indicator,
Name,
%sel_C(90)
from have_data;
quit;
If I understand the question properly, the easiest way would be to concatenate the columns to one. RETAIN that value from row to row, and you can compare it across rows to see if it's the same or not.
data want;
set have;
by id indicator;
retain last_cols;
length last_cols $500;
cols = catx('|',of c1-c90);
if first.id then call missing(last_cols);
else do;
identical = (cols = last_cols); *or whatever check you need to perform;
end;
output;
last_cols = cols;
run;
There are a few different ways you can do this and it will be much easier if the actual column names are C1 - C90. If you're just looking to remove anything that you know is a duplicate you can use proc sort.
proc sort data=dups out=nodups nodupkey;
by ID Name C1-C90;
run;
The nodupkey option will automatically remove any duplicates in the by statement.
Alternatively, if you want to know which records contain duplicates, you could use proc summary.
proc summary data=dups nway missing;
class ID Name C1-C90;
output out=onlydups(where=(_freq_ > 1));
run;
proc summary creates two new variables, _type_ and _freq_. If you specify _freq_ > 1 you will only output the duplicate records. Also, note that this will remove the Indicator variable.
Hell everyone --
I have some sales data which looks like this:
data have;
input order_id item $;
cards;
1 A
1 B
2 A
2 C
3 B
4 A
4 B
;
run;
What I'm trying to find out is what are the most popular combinations of items ordered. For example in the above case, there were 2 orders that contained items A&B, 1 order of A&C, and 1 order of B. What would be the best way to output the different combinations along with the numbers of orders placed?
It seems there is no permutation issue, you could try this:
proc sort data=have;
by order_id item;
run;
data temp;
set have;
by order_id;
retain comb;
length comb $4;
comb=cats(comb,item);
if last.order_id then do;
output;
call missing(comb);
end;
run;
proc freq data=temp;
table comb/norow nopercent nocol nocum;
run;
There are many possible approaches to this problem, and I would not presume to say which is the best. Here's a fairly simple method you could use:
Transpose your data so that you only have 1 row for each order, with an indicator variable for each product.
Feed the transposed dataset into proc corr to produce a correlation matrix for the indicator variables, and look for the strongest correlations.
original output
Count
AAB BB
01NOV2014 5 4
02NOV2014 4 3
But ideal output is
Count
BB AAB
01NOV2014 4 5
02NOV2014 4 4
Is there a way to change a n by k tables from proc tabulate to list it as requested?
Since k is not small, I'm looking for an efficient way to achieve this. Maybe store the requested order in a macro variable?
The easiest answer depends on how the order is derived.
You have some ordering options on the class variable, such as order=data, which may give you the desired result if the data is stored in that order. This can be tricky, but sometimes is a simple method to get to that result.
Second, you have a couple of options related to formats.
If the data can be stored as a formatted numeric, where BB=1, AAB=2, etc., then use order=unformatted to achieve that.
Create a format that lists the values in order, just formatting them to themselves, with notsorted in the options of the value statement, and then use order=data on the class statement and preloadfmt.
Example of the second option:
data have;
input var $ count;
datalines;
AAA 1
AAB 2
BBA 3
BBB 4
;;;;
run;
proc format;
value $myformatf (notsorted)
BBB=BBB
AAB=AAB
BBA=BBA
AAA=AAA
other=' ';
quit;
proc tabulate data=have;
class var/order=data preloadfmt;
format var $myformatf.;
var count;
tables var,count*sum;
run;
I have two datasets in SAS that I would like to merge, but they have no common variables. One dataset has a "subject_id" variable, while the other has a "mom_subject_id" variable. Both of these variables are 9-digit codes that have just 3 digits in the middle of the code with common meaning, and that's what I need to match the two datasets on when I merge them.
What I'd like to do is create a new common variable in each dataset that is just the 3 digits from within the subject ID. Those 3 digits will always be in the same location within the 9-digit subject ID, so I'm wondering if there's a way to extract those 3 digits from the variable to make a new variable.
Thanks!
SQL(using sample data from Data Step code):
proc sql;
create table want2 as
select a.subject_id, a.other, b.mom_subject_id, b.misc
from have1 a JOIN have2 b
on(substr(a.subject_id,4,3)=substr(b.mom_subject_id,4,3));
quit;
Data Step:
data have1;
length subject_id $9;
input subject_id $ other $;
datalines;
abc001def other1
abc002def other2
abc003def other3
abc004def other4
abc005def other5
;
data have2;
length mom_subject_id $9;
input mom_subject_id $ misc $;
datalines;
ghi001jkl misc1
ghi003jkl misc3
ghi005jkl misc5
;
data have1;
length id $3;
set have1;
id=substr(subject_id,4,3);
run;
data have2;
length id $3;
set have2;
id=substr(mom_subject_id,4,3);
run;
Proc sort data=have1;
by id;
run;
Proc sort data=have2;
by id;
run;
data work.want;
merge have1(in=a) have2(in=b);
by id;
run;
an alternative would be to use
proc sql
and then use a join and the substr() just as explained above, if you are comfortable with sql
Assuming that your "subject_id" variable is a number then the substr function wont work as sas will try convert the number to a string. But by default it pads some paces on the left of the number.
You can use the modulus function mod(input, base) which returns the remainder when input is divided by base.
/*First get rid of the last 3 digits*/
temp_var = floor( subject_id / 1000);
/* then get the next three digits that we want*/
id = mod(temp_var ,1000);
Or in one line:
id = mod(floor(subject_id / 1000), 1000);
Then you can continue with sorting the new data sets by id and then merging.