Hi I am trying to merge two tables the FormA scores table that I made that is now CalculatingScores with the domain number found in DomainsFormA. I need to merge them by QuestionNum. Here is my code.
proc sql;
create table combined as
select *
from CalculatingScores inner join DomainsFormA
on CalculatingScores.Scores=DomainsFormA.QuestionNum;
quit;
proc print data=combined (obs=15);
run;
This table is what I am trying to get my merged tables to look like but for 15 observations.
Form
Student
QuestionNum
Scores
DomainNum
A
1
1
0
5
A
1
2
1
4
A
1
3
0
5
But My tables look more like this
Form
Student
QuestionNum
Scores
DomainNum
A
1
2
1
5
A
1
4
1
5
A
1
5
1
5
My entire Scores column for these 15 observations have a value of 1. Also my DomainNum column only has values of 5. My Student and Form columns are correct but I need to have varied scores and varied domain numbers. Any ideas for how to solve my problem? Maybe I need a order by statement?
You appear to be joining on the incorrect columns
You coded
on CalculatingScores.Scores=DomainsFormA.QuestionNum
which is joining a score to a question number
perhaps you should be coding
on CalculatingScores.QuestionNum=DomainsFormA.QuestionNum
^^^^^^^^^^^ ^^^^^^^^^^^
Related
Let's say I have four samples: id=1, 2, 3, and 4, with one or more measurements on each of those samples:
Table
ID Value
1 1
1 2
2 3
2 -4
3 -5
4 6
I want to remove duplicates, keeping only one entry per ID - the one having the largest absolute value of the "value" column. I.e., this is what I want:
Result
ID Value
1 2
2 -4
3 -5
4 6
How might I do this in SAS?
I didn't find a solution to do this with SAS, so I tried to export it to Excel and use pivot table and "Value Field max" -setting, but that only gave me highest value, and and I need highest difference from zero.
SQL with a having clause will solve this quickly.
proc sql;
create table want as
select id, value
from have
group by id
having abs(value) = max(abs(value))
;
quit;
Output:
ID Value
1 2
2 -4
3 -5
4 6
If I understand your question correctly,there are a few ways to do this.
I would create a new variable with your absolute value, sort the dataset by id and descending absolute value and then keep the top record.
The code would look like:
data tmp1;
set data1;
absvalue = abs(value);
proc sort data=tmp1;
by id descending absvalue ;
data tmp2;
set tmp1;
by id;
if first.id then output tmp2;
run;
You could also use Proc Sql.
I'm trying to set up an array formula in a google sheet to save filling in a simple formula for ID#s.
The sheet is populated by a google form, so it receives a timestamp. Let's say these are orders.
If the month of the order matches that of the previous I want to increase the ID# by one, essentially counting this months orders. The complete ID# is actually made up of several factors, the order count being just one of them (so that they are unique), but for the sake of this exercise, I'll keep it simple.
If the month of the order does not match the previous, then safe to say we've entered the new month and the ID should restart at 01.
I have a column that has the extracted month from the timestamp. So the data looks like this:
A B
ID# MONTH
1 1
2 1
3 1
4 1
5 1
6 1
1 2
2 2
3 2
1 3
2 3
3 3
4 3
I can't get the arrayformula to work! I've tried numerous countIfs and Ifs, something like
=ARRAYFORMULA(if(len(B2:B),if(B3:B<>B2:B,1,A2:A+1),""))
Does anyone have any suggestions for this?
I found it hard to Google for and have tried a few search terms!
try:
=ARRAYFORMULA(IF(B1:B<>"", COUNTIFS(B1:B, B1:B, ROW(B1:B), "<="&ROW(B1:B)), ))
Say we are confined to using SAS and have a panel/longitudinal dataset. We have indicators for cohort and time, as well as some measured variable y.
data in;
input cohort time y;
datalines;
1 1 100
1 2 101
1 3 102
1 4 103
1 5 104
1 6 105
2 2 .
2 3 .
2 4 .
2 5 .
2 6 .
3 3 .
3 4 .
3 5 .
3 6 .
4 4 108
4 5 110
4 6 112
run;
Note that units of cohort and time are the same so that if the dataset goes out to time unit 6, each successive panel unit will be one period shorter than the one before it in time.
We have a gap of two panel units between actual data. The goal is to linearly interpolate the two missing panel units (values for cohort 2 and 3) from the two that "sandwich" them. For cohort 2 at time 5 the interpolated value should be 0.67*104 + 0.33*110, while for cohort 3 at time 5 it would be 0.33*104 + 0.67*110. Basically you just weight 2/3 for the closer panel unit with actuals, and 1/3 for the further panel unit. You'll of course have missing values, but for this toy example that's not a problem.
I'm imagining the solution involves lagging and using the first. operator and loops but my SAS is so poor I hesitate to provide even my broken code example.
I've got a solution, it is however tortured. There must be a better way to do it, this takes one line in Stata.
First we use proc SQL to make a table of the two populated panel units, the "bread of the sandwich"
proc sql;
create table haveY as
select time, cohort, y
from startingData
where y is not missing
order by time, cohort;
quit;
Next we loop over the rows of this reduced dataset to produce interpolated values, I don't completely follow the operations here, I modified a related example I found.
data wantY;
set haveY(rename=(y=thisY cohort=thisCohort));
by time;
retain lastCohort lastY;
lastcohort = lag(thisCohort);
lastY = lag(thisY);
if not first.time then do;
do cohort = lastCohort +1 to thisCohort-1;
y = ((thisCohort-cohort)*lastY + (cohort-lastCohort)*thisY)/(thisCohort-lastCohort);
output;
end;
end;
cohort=thisCohort;
y=thisY;
drop this: last:;
run;
proc sort data=work.wantY;
by cohort time;
run;
This does produce what is needed, it can be joined using proc sql into the starting table: startingData. Not a completely satisfying solution due to the verbosity but it does work.
I am wanting to count the number of time a certain value appears in a particular column in sas. For example in the following dataset the value 1 appears 3 times
value 2 appears twice, value 3 appears once, value 4 appears 4 times and value 5 appears four times.
Game_ball
1
1
1
2
2
3
4
4
4
5
5
5
5
5
I want the dataset to represented like the following:
Game_ball Count
1 3
2 2
3 1
4 4
5 4
. .
. .
. .
Thanks in advance
As per #Dwal, proc freq is the easiest solution.
Using your sample data,
proc freq data=sample;
table game_ball/out=output;
run;
Or do it in one-pass data step
proc sort data = sample;by game_ball;run;
data output;
set sample;
retain count;
if first.game_ball then count = 0;
count + 1;
if last.game_ball then output;
by game_ball;
run;
Or in SQL
proc sql;
create table output as
select game_ball, count(*) as count
from sample
group by game_ball;
quit;
I have three different questions about modifying a dataset in SAS. My data contains: the day and the specific number belonging to the tag which was registred by an antenna on a specific day.
I have three separate questions:
1) The tag numbers are continuous and range from 1 to 560. Can I easily add numbers within this range which have not been registred on a specific day. So, if 160-280 is not registered for 23-May and 40-190 for 24-May to add these non-registered numbers only for that specific day? (The non registered numbers are much more scattered and for a dataset encompassing a few weeks to much to do by hand).
2) Furthermore, I want to make a new variable saying a tag has been registered (1) or not (0). Would it work to make this variable and set it to 1, then add the missing variables and (assuming the new variable is not set for the new number) set the missing values to 0.
3) the last question would be in regard to the format of the registered numbers which is along the line of 528 000000000400 and 000 000000000054. I am only interested in the last three digits of the number and want to remove the others. If I could add the missing numbers I could make a new variable after the data has been sorted by date and the original transponder code but otherwise what would you suggest?
I would love some suggestions and thank you in advance.
I am inventing some data here, I hope I got your questions right.
data chickens;
do tag=1 to 560;
output;
end;
run;
data registered;
input date mmddyy8. antenna tag;
format date date7.;
datalines;
01012014 1 1
01012014 1 2
01012014 1 6
01012014 1 8
01022014 1 1
01022014 1 2
01022014 1 7
01022014 1 9
01012014 2 2
01012014 2 3
01012014 2 4
01012014 2 7
01022014 2 4
01022014 2 5
01022014 2 8
01022014 2 9
;
run;
proc sql;
create table dates as
select distinct date, antenna
from registered;
create table DatesChickens as
select date, antenna, tag
from dates, chickens
order by date, antenna, tag;
quit;
proc sort data=registered;
by date antenna tag;
run;
data registered;
merge registered(in=INR) DatesChickens;
by date antenna tag;
Registered=INR;
run;
data registeredNumbers;
input Numbers $16.;
datalines;
528 000000000400
000 000000000054
;
run;
data registeredNumbers;
set registeredNumbers;
NewNumbers=substr(Numbers,14);
run;
I do not know SAS, but here is how I would do it in SQL - may give you an idea of how to start.
1 - Birds that have not registered through pophole that day
SELECT b.BirdId
FROM Birds b
WHERE NOT EXISTS
(SELECT 1 FROM Pophole_Visits p WHERE b.BirdId = p.BirdId AND p.date = ????)
2 - Birds registered through pophole
If you have a dataset with pophole data you can query that to find if a bird has been through. What would you flag be doing - finding a bird that has never been through any popholes? Looking for dodgy sensor tags or dead birds?
3 - Data code
You might have more joy with the SUBSTRING function
Good luck