I would like to create a table that lists the frequency of each variables frequencies. For example, a data set with 100 rows and 4 variables: ID, A, B, and C.
What I'm looking for would be like this:
Freqs| ID A B C
----------------------------
1 | 100 20 15 10
2 | 0 40 35 0
3 | 0 0 5 30
Since there are 100 unique IDs, there will be a frequency of 100 frequencies of 1 from the original data.
edit for clarification:
If you did a proc freq on the original data, you would get a frequency of 1 for every ID. Then if you did a proc freq on the count, you would have a frequency of 100 for counts of 1. I'm looking for that for every variable in a data set.
This should do what you want. You probably want to process the preds table since it contains "Table" in each table name, but this is a pretty simple way to do this.
ods output onewayfreqs=preds;
proc freq data=sashelp.class;
tables _all_;
run;
ods output close;
proc tabulate data=preds;
class table frequency;
tables frequency,table;
run;
Related
I have a dataframe
ID value1
1 12
2 345
3 342
i have a second dataframe
value2
3823
how do I get the following result?
ID value1 value2
1 12 3823
2 345 3823
3 342 3823
any joins I have done have given me
ID value1 value2
1 12 .
2 345 .
3 342 .
. . 3823
No need for joins or helper variables:
data have;
do i = 1 to 3;
output;
end;
run;
data lookup;
j = 1;
run;
data want;
set have;
if _n_ = 1 then set lookup;
run;
Without the if _n_ = 1, the data step stops after one iteration when it tries to read a second row from the lookup dataset and finds that there are no rows remaining.
N.B. this requires that the have dataset doesn't already contain a variable with the same name as the variable(s) attached from the lookup dataset.
By far the easiest way to do this is to utilize PROC SQL and defining the condition 1=1, which is always true for each comparison:
data first;
input ID value1 ##;
cards;
1 12 2 345 3 342
run;
data second;
input value2 ;
cards;
3823
run;
proc sql;
create table wanted as
select * from first
left join second
on 1 =1
;quit;
Edit: As far as I know, there isn't direct way to merge datasets by each row, but you can do the following trick:
Add variable Help:
data second_trick;
set second;
help=1;
run;
data first_trick;
set first;
help=1;
run;
Then we just perform the merge by the static variable:
data wanted_trick;
merge first_trick(in=a) second_trick;
by help;
if a; /*Left join, just to be sure.*/
run;
now this only works if you want to add single static value. Don't try to use it your Second set has more rows.
For more on Merges and joins see: https://support.sas.com/resources/papers/proceedings/proceedings/sugi30/249-30.pdf
I'm trying to create a new variable on SAS. There is a column called "Statefip" and a column called "countyfip". I need a four digit ID number that combines these two columns.
For example:
enter image description here
How do I tell SAS to follow this format when creating this new variable?
This is easy to do using put and input statements. The z3 format includes leading 0's in the output. || concatenates the put statements and then input converts the id field back to numeric.
data have;
input statefip countyfip;
datalines;
1 1
8 109
12 57
13 313
;
run;
data want;
set have;
id = input(put(statefip,2.) || put(countyfip,z3.),8.);
run;
proc print;
Output:
Obs statefip countyfip id
1 1 1 1001
2 8 109 8109
3 12 57 12057
4 13 313 13313
Suppose data set looks like:
A B C
1 2 0.2
2 7 0.3
3 10 0.7
and I want to multiply columns A and B by C and update the values? What is the most efficient way to do this?
Maybe I'm misunderstanding, but this is quite basic. Then again, basics are the most important bit.
data begin;
input A B C;
cards;
1 2 0.2
2 7 0.3
3 10 0.7
;
run;
data wanted;
set begin;
AC=A*C;
BC=B*C;
run;
/* Here is an easy example.*/
/*Your first data set*/
data fisrt;
input A B C;
datalines;
1 2 0.2
2 7 0.3
3 10 0.7
;
run;
/*The data you want to get*/
data product;
set first;
AC=A*C;
BC=B*C;
run;
Since you are just looking to update the values of a and b try this:
data product;
set first;
A=A*C;
B=B*C;
run;
alternatively, you could try:
proc sql noprint;
create table product as
select a*c as a,b*c as b,c from first;quit;
and then compare run times to see which one runs faster
I have two dataset data1 and data2
data data1;
input sn id $;
datalines;
1 a
2 a
3 a
;
run;
data data2;
input id $ sales x $;
datalines;
a 10 x
a 20 y
a 30 z
a 40 q
;
run;
I am merging them from below code:
data join;
merge data1(in=a) data2(in=b);
by id;
if a and b;
run;
Result: (I was expecting an Inner Join result which is not the case)
1 a 10 x
2 a 20 y
2 a 30 z
2 a 40 w
Result from proc sql inner join.
proc sql;
select data1.id,sn,sales,x from data2 inner join data1 on data1.hh_id;
quit;
Result: (As expected from an inner join)
a 1 10 x
a 1 20 y
a 1 30 z
a 1 40 w
a 2 10 x
a 2 20 y
a 2 30 z
a 2 40 w
b 3 10 x
b 3 20 y
b 3 30 z
b 3 40 w
I want to know the concept and STEP BY STEP working of merge statement in SAS with In= and proving the above result.
PS: I have read this, and it says
An obvious use for these variables is to control what kind of 'merge'
will occur, using if statements. For example, if
ThisRecordIsFromYourData and ThisRecordIsFromOtherData; will make SAS
only include rows that match on the by variables from both input data
sets (like an inner join).
which I guess, (like an Inner Join) is not always the case.
Basically, this is a result of the difference in how the SAS data step and SQL process their respective join/merges.
SQL creates a separate record for each possible combination of keys. This is a Cartesian Product (at the key level).
SAS data step, however, process merges very differently. MERGE is really nothing more than a special case of SET. It still processes rows iteratively, one at a time - it never goes back, and never has more than one row from any dataset in the PDV at once. Thus, it cannot create a Cartesian product in its normal process - that would require random access, which the SAS datastep doesn't do normally.
What it does:
For each unique BY value
Take the next record from the left side dataset, if one exists with that BY value
Take the next record from the right side dataset, if one exists with that BY value
Output a row
Continue until both datasets are exhausted for that BY value
With BY values that yield unique records per value on either side (or both), it is effectively identical to SQL. However, with BY values that yield duplicates on BOTH sides, you get what you have there: a side-by-side merge, and if one runs out before the other, the values from the last row of the shorter dataset (for that by value) are more-or-less copied down. (They're actually RETAINED, so if you overwrite them with changes, they will not reset on new records from the longer dataset).
So, if left has 3 records and right has 4 records for key value a, like in your example, then you get data from the following records (assuming you don't alter the data after):
left right
1 1
2 2
3 3
3 4
This is my current issue:
I have 53 variable headers in a SAS data set that need to be changed, for example:
Current_Week_0 TS | Current_Week_1 TS | Current_Week_2 TS -- etc.
I need it to change such that Current_Week_# TS = Current_Week_# -- dropping the TS
Is there a way to automate this such as looping it like:
i = 0,53
Current_week_i TS = Current_Week_i ?
I just don't understand the proper syntax.
Edit: Thank you for editing my formats Sergiu, appreciate it! :)
Edit:
I used the following code, but I get the following error:
Missing numeric suffix on a numbered variable list (TS-Current_Week_53)
DATA True_Start_8;
SET True_Start_7;
ARRAY oldnames (53) Current_Week_1 TS-Current_Week_53 TS;
ARRAY newnames (53) Current_Week_1-Current_Week_53;
DO i = 1 TO 53;
newnames(i) = oldnames(i) ;
END;
RUN;
#Joe EDIT
Here's what the data looks like before and after the "denorm" / transpose
BEFORE
Product ID CurrentWeek Market TS
X 75av2kz Current_Week_0 Z 1
Y 7sav2kz Current_Week_0 Z 1
X 752v2kz Current_Week_1 Z 1
Y 255v2kz Current_Week_1 Z 1
Product ID Market Current_Week_0_TS Current_Week_1_TS
X 75av2kz Z 1 0
Y 7sav2kz Z 1 1
X 752v2kz Z 1 1
Y 255v2kz Z 1 0
This isn't too hard. I assume these are variable labels.
proc sql;
select cats('%relabel_nots(',name,')') into :relabellist separated by ' '
from dictionary.columns
where libname='WORK' and memname='True_Start_7'
and name like '%TS'; *you may need to upper case the dataset name (memname) depending on your OS;
quit;
%macro relabel_nots(name);
label &name.= substr(vlabel(&name.),1,length(vlabel(&name.))-3);
%mend relabel_nots;
data want;
set True_Start_7;
&relabellist.;
run;
Basically the PROC SQL grabs the different names that qualify for the relabelling, and generates a large macro variable with all of the rename macro calls. The relabel_nots macro generates the new labels. You may need to change the logic behind the WHERE in the PROC SQL if the variable names don't also contain the TS.
Another option is to do this in the transpose. Your example data either doesn't match the example desired output, or there is something in logic not explained, but this does the simple transpose; if there is a logical reason that the current_week_0/1 are different in yours than in the below, explain why.
data have;
format currentWeek $20.;
input Product $ ID $ CurrentWeek $ Market $ TS;
datalines;
X 75av2kz Current_Week_0 Z 1
Y 7sav2kz Current_Week_0 Z 1
X 752v2kz Current_Week_1 Z 1
Y 255v2kz Current_Week_1 Z 1
;;;;
run;
proc sort data=have;
by market id product;
run;
proc transpose data=have out=want;
by market id product ;
id currentWeek;
var TS;
run;