I am learning SAS at the moment and I wanted to know how do you join two tables without using any SQL where I need to get only the common values in two tables.
Both tables have a common unique id. Also the tables don't have common variables.
Please don't give any documentation links as I already have and I know merge. I am trying it with an IN operator.
Table 1 : Screenshot
Table 2 : Screenshot
Description: The first table has 157 records and the other has 161 records.
I tried searching a solution but didn't get any. Please refer a solution.
Thanks !
In DATA Step you will want to use the MERGE statement and the IN= option which sets up flags indicating 'contribution' to the current state of the program data vector (PDV)
data want;
merge
have1 (in=_from1)
have2 (in=_from2)
;
by uniqueid; * variable of same name, type and length should be in have1 and have2;
if _from1 and _from2; * subsetting if;
run;
DATA Step is an implicit loop. The MERGE automatically advances reads through the contributing data, synchronizing about the BY variables.
When a DATA Step has no explicit OUTPUT statement, there will be an implicit OUPUT of the values in the PDV when control reaches the bottom of the step. Thus, the if without a then is called subsetting because control only goes past the if (and reaches the bottom for implicit output) when both flags are true (or when data is coming from both tables at a common key value)
Related
In SAS, I have a table that have 1000 rows. I am trying to separate that table into two tables. Row1-500 to Table A and row501-100 to table B. What is the code that can do this function. Thank you all for helping!
I am searching the code online and cannot get anything on google, help is appreciated.
The DATA statement lists the output tables of the step. An OUTPUT statement explicitly sends a row to each of the output tables. An explicit OUTPUT <target> ... <target-k> statement sends records to the specified tables only. The automatic implicit loop index variable _n_ can act as a row counter when a single data set is being read with SET.
Try
data want1 want2;
set have;
if _n_ <= 500 then output want1; else output want2;
run;
However, you may be better served by creating a categorical variable that can be used later in WHERE or BY statements.
Maybe the set options will help.Try firstobs= and obs= to choose the rows you want.
Here is how to use them:
data want1;
set have(obs=500);
run;
data want2;
set have(firstobs=501 obs=1000);
run;
I have a table in SAS which contains the format information I want. I want to bin this data into the categories given.
What I don't know how to do is create either an xform or a format file from the data.
An example table looks like this:
TxtLabel Type FmtName label Hlo count
. I FAC1f 0 O 1
1996 I FAC1f 1 2
1997 I FAC1f 2 3
I want to date all years in a different data set as after 1997 OR before 1996.
The problem is that I know how to do this by hard coding it, but these files changes the numbers each time so I'm hoping to use the information in the table to generate the bins rather than hard code them.
How do I go about binning by data using a column from another dataset for my categorization?
Edit
I have two data sets, one which looks like the one I have included and one which has a column titled "YEAR". I want to bin the second data set using the categories from the first. In this case there are two available years in TxtLabel. There are multiple tables like this, I'm looking at how to generate PROC Format code from the table, rather than hard coding the values.
This should run to create the desired format
Proc FORMAT CNTLIN=MyCustomFormatControlData;
run;
You can then use it in a DATA Step, or apply it to a column in a data set.
Binning the data might be construed as 'data set splitting' but your question does not make it clear if that is so. Generic arbitrary splitting is often done with one of these techniques:
wall paper source code resolved from macro variables populated from information garnered in a Proc SQL or Proc FREQ step
dynamic data splitting using hash object for grouping records in memory, and saved to a data set with an .output() call.
Sample code for explicit binning
data want0 want1 want2 want3 want4 want5 wantOther;
set have;
* explicit wall paper;
select (put(year,FAC1f.));
when ('0') output want0;
when ('1') output want1;
when ('2') output want2;
when ('3') output want3;
when ('4') output want4;
when ('5') output want5;
otherwise output wantOther;
run;
This is the construct that source code generated by macro can produce, and requires
one pass to determine the when/output lines that are to be generated
a second pass to apply the lines of code that were generated.
If this is the data processing that you are attempting:
do some research (plenty of info out there)
write some code
make a new question if you get errors you can't resolve
Proc FORMAT
Proc FORMAT has a CNTLIN option for specifying a data set containing the format information. The structure and values expected of the Input Control Data Set (that CNTLIN) is described in the Output Control Data Set documentation. Some of the important control data columns are:
FMTNAME
specifies a character variable whose value is the format or informat name.
LABEL
specifies a character variable whose value is associated with a format or an informat.
START
specifies a character variable that gives the range's starting value.
END
specifies a character variable that gives the range's ending value.
As the requirements of the custom format to be created get more sophisticated you will need to have more information variables in the input control data set.
I was using the following code to analyze data:
set taq.cq_&yyyymmdd:;
by symbol date time NOTSORTED ex;
There are are thousands of datasets I am running the code on in the unit of days. When &yyyymmdd only specifies one dataset (for one day. for example, 20130102), it works. However, when I try to run it for multiple datasets (for example, 201301:), SAS returns the following errors:
BY NOTSORTED/NOBYSORTED cannot be used with SET statement when
more than one data set is specified.
If I cannot use NOTSORTED here, what is an equivalent statement that I could use?
My understanding of the keyword NOTSORTED is that you use it when the data is not sorted yet. Therefore, do I need to sort it first? How to do it?
I am also confused by the number of variables that NOTSORTED is referencing. Does it only have an effect on "time", or it has effect on "symbol, data, time"?
Many thanks!
UPDATE#2:
The rest of the process immediately following the set statement is: (pseudo code as i don't have the permission to post the original code)
Data _quotes;
SET STATEMENT HERE
Change the name of a variable in the dataset (Variable name is EXN).
last.EXN in a if statement. If the condition is satisfied, label EXN.
Drop some variables.
Run;
DATA NEWDATASET (sortedby= SYMBOL DATE TIME index=(SYMBOL)
label="WRDS-TAQ NBBO Data");
SET _quotes;
by symbol date time;
....
Run;
NOTSORTED means that SAS can assume the sort order in the data is correct, so it may not have explicitly gone through a PROC SORT but it is in logical order as listed in the BY statement.
All variables in the BY statement are included in the NOTSORTED option. Given that I suspect you fully don't understand BY group processing.
It's usually a bit dangerous to use, especially if you don't understand BY group processing. If your data is in the same group but not adjacent it won't work properly and will not produce an error. The correct workaround depends on your processes to be honest.
I would suggest reviewing the documentation regarding BY group processing. It's quite in depth and has lots of samples to illustrate the different type of calculations.
http://support.sas.com/documentation/cdl/en/lrcon/69852/HTML/default/viewer.htm#n138da4gme3zb7n1nifpfhqv7clq.htm
NOTSORTED is often used in example posts to either avoid a sort or when using a custom sort that's difficult to implement in other ways. Explicitly sorting will remove this issue but you may also be misunderstanding how SAS processes data when you have a SET statement with a BY statement. I believe this is called interleaving.
http://support.sas.com/documentation/cdl/en/lrcon/69852/HTML/default/viewer.htm#n1tgk0uanvisvon1r26lc036k0w7.htm
I suspect that the NOTSORTED keyword is being using to find groups for observations with the same value for the EX variable within the same symbol,date,time. If you only need to find the FIRST then you can use the LAG() function to calculate the FIRST.EX flag.
data want;
set taq.cq_&yyyymmdd:;
by symbol date time;
first_ex = first.time or ex ne lag(ex);
Otherwise then perhaps you want to convert the process to data step views and then set the views together.
data work.view_cq_20130102 / view=work.view_cq_20130102;
set taq.cq_20130102;
by symbol date time ex NOTSORTED;
...
run;
...
data want ;
set work.view_cq_201301: ;
by symbol date time;
...
I am using SAS for a large dataset (>20gb). When I run a DATA step, I received the "BY variables are not properly sorted ......" although I sorted the dataset by the same variables. When I ran the PROC SORT again, SAS even said "Input dataset is already sorted, No sorting done"
My code is:
proc sort data=output.TAQ;
by market ric date miliseconds descending type order;
run;
options nomprint;
data markers (keep=market ric date miliseconds type order);
set output.TAQ;
by market ric date;
if first.date;
* ie do the following once per stock-day;
* Make 1-second markers;
/*Type="AMARK"; Order=0; * Set order to zero to ensure that markers get placed before trades and quotes that occur at the same milisecond;
do i=((9*60*60)+(30*60)) to (16*60*60); miliseconds=i*1000; output; end;*/
run;
And the error message was:
ERROR: BY variables are not properly sorted on data set OUTPUT.TAQ.
RIC=CXR.CCP Date=20160914 Time=13:47:18.125 Type=Quote Price=. Volume=. BidPrice=9.03 BidSize=400
AskPrice=9.04 AskSize=100 Qualifiers= order=116458952 Miliseconds=49638125 exchange=CCP market=1
FIRST.market=0 LAST.market=0 FIRST.RIC=0 LAST.RIC=0 FIRST.Date=0 LAST.Date=1 i=. _ERROR_=1
_N_=43297873
NOTE: The SAS System stopped processing this step because of errors.
NOTE: There were 43297874 observations read from the data set OUTPUT.TAQ.
WARNING: The data set WORK.MARKERS may be incomplete. When this step was stopped there were
56770826 observations and 6 variables.
WARNING: Data set WORK.MARKERS was not replaced because this step was stopped.
NOTE: DATA statement used (Total process time):
real time 1:14.21
cpu time 26.71 seconds
The error is occurring deep into your data step, at _N_=43297873. That suggests to me that the PROC SORT is working up to a point, but then fails. It is hard to know what the reason is without knowing your SAS environment or how OUTPUT.TAQ is stored.
Some people have reported resource problems or file system limitations when sorting large data sets.
From SAS FAQ: Sorting Very Large Datasets with SAS (not an official source):
When sorting in a WORK folder, you must have free storage equal to 4x the size of the data set (or 5x if under Unix)
You may be running out of RAM
You may be able to use options MSGLEVEL=i and FULLSTIMER to get a fuller picture
Also using options sastraceloc=saslog; can produce helpful messages.
Maybe instead of sorting it, you could break it up into a few steps, something like:
/* Get your market ~ ric ~ date pairs */
proc sql;
create table market_ric_date as
select distinct market, ric, date
from output.TAQ
/* Possibly an order by clause here on market, ric, date */
; quit;
data millisecond_stuff;
set market_ric_date;
*Possibly add type/order in this step as well?;
do i=((9*60*60)+(30*60)) to (16*60*60); miliseconds=i*1000; output; end;
run;
/* Possibly a third step here to add type / order if you need to get from original data source */
If your source dataset is in a database, it may be sorted in a different collation.
Try the following before your sort:
options sortpgm=sas;
I had the same error, and the solution was to make a copy of the original table in the work directory, do the sort, and then the "by" was working.
In your case something like below:
data tmp_TAQ;
set output.TAQ;
run;
proc sort data=tmp_TAQ;
by market ric date miliseconds descending type order;
run;
data markers (keep=market ric date miliseconds type order);
set tmp_TAQ;
by market ric date;
if first.date;
* ie do the following once per stock-day;
* Make 1-second markers;
/*Type="AMARK"; Order=0; * Set order to zero to ensure that markers get placed before trades and quotes that occur at the same milisecond;
do i=((9*60*60)+(30*60)) to (16*60*60); miliseconds=i*1000; output; end;*/
run;
I am working in SAS Enterprise guide and have a one column SAS table that contains unique identifiers (id_list).
I want to filter another SAS table to contain only observations that can be found in id_list.
My code so far is:
proc sql noprint;
CREATE TABLE test AS
SELECT *
FROM data_sample
WHERE id IN id_list
quit;
This code gives me the following errors:
Error 22-322: Syntax error, expecting on of the following: (, SELECT.
What am I doing wrong?
Thanks up front for the help.
You can't just give it the table name. You need to make a subquery that includes what variable you want it to read from ID_LIST.
CREATE TABLE test AS
SELECT *
FROM data_sample
WHERE id IN (select id from id_list)
;
You could use a join in proc sql but probably simpler to use a merge in a data step with an in= statement.
data want;
merge oneColData(in = A) otherData(in = B);
by id_list;
if A;
run;
You merge the two datasets together, and then using if A you only take the ID's that appear in the single column dataset. For this to work you have to merge on id_list which must be in both datasets, and both datasets must be sorted by id_list.
The problem with using a Data Step instead of a PROC SQL is that for the Data step the Data-set must be sorted on the variable used for the merge. If this is not yet the case, the complete Data-set must be sorted first.
If I have a very large SAS Data-set, which is not sorted on the variable to be merged, I have to sort it first (which can take quite some time). If I use the subquery in PROC SQL, I can read the Data-set selectively, so no sort is needed.
My bet is that PROC SQL is much faster for large Data-sets from which you want only a small subset.