I am trying to create computed variables in SAS EG.
data data1;
input ID Type Payment_Amt;
cards;
1 Voucher $50
1 Cash $50
1 Cash $20
1 Card $20
1 Card $50
;
Data want:
ID TotalAmtVoucher TotalAmtCash TotalAmtCard
1 $50 $70 $70
Is this possible?
Please let me know if I am lacking any details needed.
Thank you very much!
Your input data for Payment_Amt is going to be a character variable with a $ on the front. which is going to be really awkward to work with. I suggest using the numeric amount and using the dollarformat to display them as monetary values.
However, if you're data is already in a character format, you can convert them to numeric with:
data data1;
set data1;
Payment_Amt2 = input(substr(Payment_Amt,2),best.);
format Payment_Amt2 dollar3.;
drop Payment_Amt;
rename Payment_Amt2 = Payment_Amt;
run;
This takes only the values after the $ in the string using substr()and then converts them to numeric values with the input() function.
To get your totals you can use proc sql and then transpose the data:
proc sql;
create table want0 as
select distinct id, type, sum(payment_amt) as total
from data1
group by type;
quit;
proc transpose data = want0 out = want(drop = _name_) prefix = TotalAmt;
by id;
id type;
run;
The proc sql step will sum all the values of a particular type via the group by statement. You can then get the data into the format you want with proc transpose. The use of the prefix= option allows you to specify the "TotalAmt" prefix in you variable name.
If the values for Types are known, static, and few you could do the following:
data data1;
input ID : 8. Type : $char10. Payment_Amt : dollar4.;
cards;
1 Voucher $50
1 Cash $50
1 Cash $20
1 Card $20
1 Card $50
2 Voucher $90
2 Cash $30
;
run;
proc sql;
create table data_want as
select ID,
sum(ifn(Type="Voucher",Payment_Amt,0)) as TotalAmtVoucher format=dollar4.,
sum(ifn(Type="Cash",Payment_Amt,0)) as TotalAmtCash format=dollar4.,
sum(ifn(Type="Card",Payment_Amt,0)) as TotalAmtCard format=dollar4.
from data1
group ID;
quit;
Related
I have a sas datebase with something like this:
id birthday Date1 Date2
1 12/4/01 12/4/13 12/3/14
2 12/3/01 12/6/13 12/2/14
3 12/9/01 12/4/03 12/9/14
4 12/8/13 12/3/14 12/10/16
And I want the data in this form:
id Date Datetype
1 12/4/01 birthday
1 12/4/13 1
1 12/3/14 2
2 12/3/01 birthday
2 12/6/13 1
2 12/2/14 2
3 12/9/01 birthday
3 12/4/03 1
3 12/9/14 2
4 12/8/13 birthday
4 12/3/14 1
4 12/10/16 2
Thanks by ur help, i'm on my second week using sas <3
Edit: thanks by remain me that i was not finding a sorting method.
Good day. The following should be what you are after. I did not come up with an easy way to rename the columns as they are not in beginning data.
/*Data generation for ease of testing*/
data begin;
input id birthday $ Date1 $ Date2 $;
cards;
1 12/4/01 12/4/13 12/3/14
2 12/3/01 12/6/13 12/2/14
3 12/9/01 12/4/03 12/9/14
4 12/8/13 12/3/14 12/10/16
; run;
/*The trick here is to use date: The colon means everything beginning with date, comparae with sql 'date%'*/
proc transpose data= begin out=trans;
by id;
var birthday date: ;
run;
/*Cleanup. Renaming the columns as you wanted.*/
data trans;
set trans;
rename _NAME_= Datetype COL1= Date;
run;
See more from Kent University site
Two steps
Pivot the data using Proc TRANSPOSE.
Change the names of the output columns and their labels with PROC DATASETS
Sample code
proc transpose
data=have
out=want
( keep=id _label_ col1)
;
by id;
var birthday date1 date2;
label birthday='birthday' date1='1' date2='2' ; * Trick to force values seen in pivot;
run;
proc datasets noprint lib=work;
modify want;
rename
_label_ = Datetype
col1 = Date
;
label
Datetype = 'Datetype'
;
run;
The column order in the TRANSPOSE output table is:
id variables
copy variables
_name_ and _label_
data based column names
The sample 'want' shows the data named columns before the _label_ / _name_ columns. The only way to change the underlying column order is to rewrite the data set. You can change how that order is perceived when viewed is by using an additional data view, or an output Proc that allows you to specify the specific order desired.
I have a dataset as following
AGE GENDER
11 F
12 M
13
15
now I want to create a dataset as following
Basically I want to have the variable names in another column.
or may be in one column like
VAR Value
AGE 11
AGE 12
AGE 13
AGE 15
GENDER F
GENDER M
I have tried normal proc transpose, but looks like it doesnt give the desired result.
This is not a strictly speaking a transpose. Transpose implies that you want to transform some columns into rows or vice-versa, which is not the case here. That sample data transposed would look like:
VAR VALUE1 VALUE2 VALUE3 VALUE4
----------------------------------
AGE 11 12 13 14
GENDER F M
What you're trying to do here instead is have all your variables in the same column and add a 'label' column.
You could have your desired result with a data step:
data have;
infile datalines missover
;
input age $ gender $;
datalines;
11 F
12 M
13
15
;
run;
data want;
length var $6;
set have(keep=age rename=(age=value) in=a)
have(keep=gender rename=(gender=value) where=(value is not missing) in=b);
if b then var='GENDER';
else if a then var='AGE';
run;
Note the where= dataset option on the second part of the set statement since your desired result does not include the missing values that you have for gender in your sample data.
Alternatively, you could do it with two proc transpose:
proc transpose data=have out=temp name=VAR;
var age gender;
run;
proc transpose data=temp out=want(drop=_name_ rename=(col1=VALUE) where=(VALUE is not missing));
var col1 col2 col3 col4;
by var;
run;
One solution is to introduce a new unique row identifier and use that in a BY statement. This will let TRANSPOSE pivot the data values in each row.
data have;
rownum + 1; * new variable for pivoting by row via BY statement;
input AGE GENDER $;
datalines;
11 F
12 M
13 .
15 .
run;
proc transpose data=have out=want(drop=_name_ rename=(col1=value) where=(value ne ''));
by rownum;
var age gender;
run;
In Proc TRANPOSE the default new column names are prefixed with COL and indexed by the number of occurrences of a value 1..n in the incoming rows. The artificial rownum and BY statement ensure the pivoted data has only one data column. Note: the prefix can be specified with option PREFIX=, and additionally the pivoted data column names can come from the data itself if you use the ID statement.
Mixed data types can be a problem because the new column will use character representation of underlying data values. So dates will come out as numbers and numeric that were initially formatted will lose their format.
If you are trying to make a JSON transmission I would recommend researching the JSON library engine or the JSON package of Proc DS2.
If you are looking to create a report with the data in this transposed shape I would recommend Proc TABULATE.
I have a list of financial advisors and I need to pull 4 samples per advisor but catch is in those 4 samples I need to force 2 mortgages, 1 loan, 1 credit card lets say.
Is there a way in the Survey select statement to set the specific number of samples to pull per stratum? I know you can stratify on 1 category and set it as a equal number. I was hoping I could use a mapping of employee names + the number of samples left to pull for each category and have survey select utilize that to pull in a dynamic way.
I'm using this as an example but this only stratifies on employee first and gives me 4 per employee. I would need to further stratify on Product type and set that to a specific sample size per product.
proc surveyselect data=work.Emp_Table_Final
method=srs n=4 out=work.testsample SELECTALL;
strata Employee_No;
run;
Thanks i know it might sound complicated, but if i know its possible then i can google the rest
Yes, you can have a dataset be the target of the n option. That dataset must:
Contain the strata variables as well as a variable SAMPSIZE or _NSIZE_ with the number to select
Have the same type and length as the strata variables
Be sorted by the strata variables
Have an entry for every strata variable value
See the documentation for more details.
data sample_counts;
length sex $1;
input sex $ _NSIZE_;
datalines;
F 5
M 3
;;;;
run;
proc sort data=sashelp.class out=class;
by sex;
run;
proc surveyselect n=sample_counts method=srs out=samples data=class;
strata sex;
run;
For two variables it's the same, you just need two variables in the sample_counts. Of course it makes it a lot more complicated, and you may want to produce this in an automated fashion.
proc sort data=sashelp.class out=class;
by sex age;
run;
data sample_counts;
length sex $1;
input sex $ age _NSIZE_;
datalines;
F 11 1
F 12 1
F 13 1
F 14 1
F 15 1
M 11 1
M 12 1
M 13 1
M 14 1
M 15 1
M 16 0
;;;;
run;
/* or do it in an automated way*/
data sample_counts;
set class;
by sex age; *your strata;
if first.age then do; *do this once per stratum level;
if age le 15 then _NSIZE_ = 1; *whatever your logic is for defining _NSIZE_;
else _NSIZE_=0;
output;
end;
run;
proc surveyselect n=sample_counts method=srs out=samples data=class;
strata sex age;
run;
Here is my data :
data example;
input id sports_name;
datalines;
1 baseball
1 basketball
1 cricket
1 soccer
2 golf
2 fencing
This is just a sample. The variable sports_name is categorical with 56 types.
I am trying to transpose the data to wide form where each row would have a user_id and the names of sports as the variables with values being 1/0 indicating Presence or absence.
So far, I used proc freq procedure to get the cross tabulated frequency table and put that in a different data set and then transposed that data. Now i have missing values in some cases and count of the sports in rest of the cases.
Is there any better way to do this?
Thanks!!
You need a way to create something from nothing. You could have also used the SPARSE option in PROC FREQ. SAS names cannot have length greater than 32.
data example;
input id sports_name :$16.;
retain y 1;
datalines;
1 baseball
1 basketball
1 cricket
1 soccer
2 golf
2 fencing
;;;;
run;
proc print;
run;
proc summary data=example nway completetypes;
class id sports_name;
output out=freq(drop=_type_);
run;
proc print;
run;
proc transpose data=freq out=wide(drop=_name_);
by id;
var _freq_;
id sports_name;
run;
proc print;
run;
Same theory here, generate a list of all possible combinations using SQL instead of Proc Summary and then transposing the results.
data example;
informat sports_name $20.;
input id sports_name $;
datalines;
1 baseball
1 basketball
1 cricket
1 soccer
2 golf
2 fencing
;
run;
proc sql;
create table complete as
select a.id, a_x.sports_name, case when not missing(e.sports_name) then 1 else 0 end as Present
from (select distinct ID from example) a
cross join (select distinct sports_name from example) a_x
full join example as e
on e.id=a.id
and e.sports_name=a_x.sports_name;
quit;
proc transpose data=complete out=want;
by id;
id sports_name;
var Present;
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.