I recently combined two datasets with a pretty straightforward Merge statement. I was using an ACS dataset and a Census population dataset. I needed a flag from the latter to be in the former. When I merged, the place variable (town/county, state) was not de-duplicated because one dataset used state abbreviations while the other used the full spelling:
Obs GeoID GeoName
1 . Abbeville County, SC
2 45001 Abbeville County, South Carolina
I need to change the GeoName for Obs1 so that it equals Obs2
Would an index function work? Or do I need the TRANWRD function? Thanks.
Solved:
data _null_;
length geoName $100;
GeoName_C = scan(GeoName,1,',');
GeoName_S = scan(GeoName,-1,','); *-1 scans from the right in case you could have commas in the city - check for this and adjust GeoName_C to include them if it is possible;
GeoName_S_F = stnamel(strip(GeoName_S));
GeoName = catx(',',GeoName_C,GeoName_S_F);
put _all_;
run;
What I would do is separate the city from the state and use SAS's inbuilt function stnamel to convert the abbreviation to the full name.
data _null_;
length geoName $100;
GeoName='Abbeville Road, SC';
GeoName_C = scan(GeoName,1,',');
GeoName_S = scan(GeoName,-1,','); *-1 scans from the right in case you could have commas in the city - check for this and adjust GeoName_C to include them if it is possible;
GeoName_S_F = stnamel(strip(GeoName_S));
GeoName = catx(',',GeoName_C,GeoName_S_F);
put _all_;
run;
Related
For context I'm a SAS programmer in clinical trials but I have this spec for variable ADTC.
If EC.ECDTC contains a full datetime, set ADTMC to the value of EC.ECDTC in "YYYY-MM-DD hh:mm" format. If EC.ECDTC contains a full or partial date but no time part then set ADTMC to the date part of EC.ECDTC in "YYYY-MM-DD" format. In both cases, replace any missing elements of the format with "XX", for example "2022-01-01 16:XX" or "2022-01-XX"
So currently I'm using this piece of code which is partially fine but not ideal
check=count(ecdtc,'-');
if check = 0 and ~missing(ecdtc) then adtc = cats(ecdtc,"-XX-XX");
else if check = 1 then adtc = cats(ecdtc,"-XX");
else if check = 2 then adtc = ecdtc;
Is there a way I could use perl-regular expressions to have like a template of the outline of the date/datetime and have it search through the values for that column and if they don't match to add -XX if missing day or -XX-XX if missing day and month etc. I was thinking of utilising prxchange but how do you incorporate the template so it knows to add -XX in the correct position where applicable.
SUBSTR on the left.
data want2;
set have;
length adtmc $16;
if length(ecdtc) le 10 then adtmc = 'xxxx-xx-xx';
else adtmc = 'xxxx-xx-xx xx:xx';
substr(adtmc,1,length(ecdtc))=ecdtc;
run;
Honestly, I wouldn't; regex are not faster for the most part than just straight-up checking with normal code, for simple things like this. If you have time pressure, or thousands or millions of rows... not a good idea, just use scan.
But that said, it's certainly possible, and somewhat interesting. We'll use PRXPOSN, which lets us iterate through the capture buffers, and "capture" each bit. This might need some tweaking, and you might need to capture/not capture the hyphens for example, but for my data this works - if your data is different, the regex will be different (and next time, post sample data!).
data have;
length ecdtc $16;
infile datalines truncover;
input #1 ecdtc $16.;
datalines;
2020-01-01 01:02
2020-01-02
2020-01
2020
junk
;;;;
run;
data want;
set have;
length adtmc $16;
array vals[3] $;
vals[1]='XXXX';
vals[2]='-XX';
vals[3]='-XX';
_rx = prxparse('/(\d{4})(-\d{2})?(-\d{2})?( \d{2}:\d{2})?/ios');
_rc = prxmatch(_rx,ecdtc); *this does the matching. Probably should check for value of _rc to make sure it matched before continuing.;
do _i = 1 to 4; *now iterate through the four capture buffers;
_rt = prxposn(_rx,_i,ecdtc);
if _i le 3 then vals[_i] = coalescec(_rt,vals[_i]);
else timepart = _rt; *we do the timepart outside the array since it needs to be catted with a space while the others do not, easier this way;
end;
adtmc = cats(of vals[*]); *cat them together now - if you do not capture the hyphen then use catx ('-',of vals[*]) instead;
if timepart ne ' ' then adtmc = catx(' ',adtmc,timepart); *and append the timepart after.;
run;
This might sound awkward but I do have a requirement to be able to concatenate all the values of a char column from a dataset, into one single string. For example:
data person;
input attribute_name $ dept $;
datalines;
John Sales
Mary Acctng
skrill Bish
;
run;
Result : test_conct = "JohnMarySkrill"
The column could vary in number of rows in the input dataset.
So, I tried the code below but it errors out when the length of the combined string (samplkey) exceeds 32K in length.
DATA RECKEYS(KEEP=test_conct);
length samplkey $32767;
do until(eod);
SET person END=EOD;
if lengthn(attribute_name) > 0 then do;
test_conct = catt(test_conct, strip(attribute_name));
end;
end;
output; stop;
run;
Can anyone suggest a better way to do this, may be break down a column into chunks of 32k length macro vars?
Regards
It would very much help if you indicated what you're trying to do but a quick method is to use SQL
proc sql NOPRINT;
select name into :name_list separated by ""
from sashelp.class;
quit;
%put &name_list.;
As you've indicated macro variables do have a size limit (64k characters) in most installations now. Depending on what you're doing, a better method may be to build a macro that puts the entire list as needed into where ever it needs to go dynamically but you would need to explain the usage for anyone to suggest that option. This answers your question as posted.
Try this, using the VARCHAR() option. If you're on an older version of SAS this may not work.
data _null_;
set sashelp.class(keep = name) end=eof;
length long_var varchar(1000000);
length want $256.;
retain long_var;
long_var = catt(long_var, name);
if eof then do;
want = md5(long_var);
put want;
end;
run;
I need help reading the code below. I am not sure what specific parts in this code are doing. For example, what does ( firstobs = 2 keep = column3 rename = (column3 = column4) ) do?
Also, what does ( obs = 1 drop = _all_ ); do?
I have also not used column5 = ifn( first.column1, (.), lag(column3) ); before. What does this do?
I am reading someone else's code. I wish I could provide more detail. If I find a solution, I will post it. Thanks for your help.
data out.dataset1;
set out.dataset2;
by column1;
WHERE column2 = 'N';
set out.dataset1 ( firstobs = 2 keep = column3 rename = (column3 = column4) )
out.dataset1 ( obs = 1 drop = _all_ );
FORMAT column5 DATETIME20.;
FORMAT column4 DATETIME20.;
column5 = ifn( first.column1, (.), lag(column3) );
column4 = ifn( last.column1, (.), column4 );
IF first.column1 then DIF=intck('dtday',column4,column3);
ELSE DIF= intck('dtday',column5,column3);
format column6 $6.;
IF first.column1
OR intck('dtday',column5,column3) GT 20 THEN column6= 'HARM';
ELSE column6= 'REPEAT';
run;
Seems like you need to learn about SAS datastep languange!
This series of things happening in the parenthesis are datastep options
You can use those options when ever you are referencing a table, even in a proc sql
The options you have:
firstobs : This starts the datafeed on the record enter in your case 2 it means SAS will start on the table on the 2nd record.
keep : This will only use the fields in list rather than using all the field in the table
rename = rename will rename field, so it works like an alias in SQL
OBS = will limit the amount of record you pull out of a table like top or limit in SQL
DROP = would remove the fields selected from the table in your case all is used wich means he's dropping all the fields.
as for the functions:
LAG is keeping the value from the previous record for the field you put in parenthesis so DPD_CLOSE_OF_BUSINESS_DT
INF = Works like a case or if. Basically you create a condition in the 1st argument and then the 2nd argument is applied when your condition in the 1st argument is true, the 3rd argument get done in the event that your condition on the 1st argument is false.
So to answer that question if it's the first record for the variable SOR_LEASE_NBR then the field Prev_COB_DT will be . otherwise it will be a previous value of DPD_CLOSE_OF_BUSINESS_DT.
The best advise I can give you is to start googling SAS and the function name you are wondering what it does, then it's a matter of encapsulation!
Hope this helps!
Basically your data step is using the LAG() function to look back one observation and the extra SET statement to look ahead one observation.
The IFN() function calls are then being used to make sure that missing values are assigned when at the boundary of a group.
You then use these calculated PREV and NEXT dates to calculate the DIF variable.
Note for this to work you need to be referencing the same input dataset in the two different SET statements (the dataset used in the last with the obs=1 and drop=_all_ dataset options
doesn't really need to be the same since it is not reading any of the actual data, it just has to have at least one observation).
( firstobs = 2 keep = DPD_CLOSE_OF_BUSINESS_DT rename =
(DPD_CLOSE_OF_BUSINESS_DT = Next_COB_DT) ) do?
Here the code firstobs=2 says SAS to read the data from 2nd observation in the dataset.
and also by using rename option trying to change the name of the variable.
(obs = 1 drop = _all_);
obs=1 is reading only the 1st obs in the dataset. If you specify obs=2 then up to 2nd obs will be read.
drop = _all_ , is dropping all of your variables.
Firstobs:
Can read part of the data. If you specify Firstobs= 10, it starts reading the data from 10th observation.
Obs :
If specify obs=15, up to 15th obs the data will be readed.
If you run the below table, it gives you 3 observations ( from 2nd to 4th ) in the output result.
Example;
DATA INSURANCE;
INFILE CARDS FIRSTOBS=2 OBS=4;
INPUT NAME$ GENDER$ AGE INSURANCE $;
CARDS;
SOWMYA FEMALE 20 MEDICAL
SUNDAR MALE 25 MEDICAL
DIANA FEMALE 67 MEDICARE
NINA FEMALE 56 MEDICAL
RUN;
Probably a simple question. I have a simple dataset with scheduled payment dates in it.
DATA INFORM2;
INFORMAT previous_pmt_date scheduled_pmt_date MMDDYY10.;
INPUT previous_pmt_date scheduled_pmt_date;
FORMAT previous_pmt_date scheduled_pmt_date MMDDYYS10.;
DATALINES;
11/16/2015 12/16/2015
12/17/2015 01/16/2016
01/17/2016 02/16/2016
;
What I'm trying to do is to create a binary latest row indicator. For example, If I wanted to know the latest row as of 1/31/2016 I'd want row 2 to be flagged as the latest row. What I had been doing before is finding out where 1/31/2016 is between the previous_pmt_date and the scheduled_pmt_date, but that isn't correct for my purposes. I'd like to do this in an data step as opposed to SQL subqueries. Any ideas?
Want:
previous_pmt_date scheduled_pmt_date latest_row_ind
11/16/2015 12/16/2015 0
12/17/2015 01/16/2016 1
01/17/2016 02/16/2016 0
Here's a solution that does it all in the single existing datastep without any additional sorting. First I'm going to modify your data slightly to include account as the solution really should take that into account as well:
DATA INFORM2;
INFORMAT previous_pmt_date scheduled_pmt_date MMDDYY10.;
INPUT account previous_pmt_date scheduled_pmt_date;
FORMAT previous_pmt_date scheduled_pmt_date MMDDYYS10.;
DATALINES;
1 11/16/2015 12/16/2015
1 12/17/2015 01/16/2016
1 01/17/2016 02/16/2016
2 11/16/2015 12/16/2015
2 12/17/2015 01/16/2016
2 01/17/2016 02/16/2016
;
run;
Specify a cutoff date:
%let cutoff_date = %sysfunc(mdy(1,31,2016));
This solution uses the approach from this question to save the variables in the next row of data, into the current row. You can drop the vars at the end if desired (I've commented out for the purposes of testing).
data want;
set inform2 end=eof;
by account scheduled_pmt_date;
recno = _n_ + 1;
if not eof then do;
set inform2 (keep=account previous_pmt_date scheduled_pmt_date
rename=(account = next_account
previous_pmt_date = next_previous_pmt_date
scheduled_pmt_date = next_scheduled_pmt_date)
) point=recno;
end;
else do;
call missing(next_account, next_previous_pmt_date, next_scheduled_pmt_date);
end;
select;
when ( next_account eq account and next_scheduled_pmt_date gt &cutoff_date ) flag='a';
when ( next_account ne account ) flag='b';
otherwise flag = 'z';
end;
*drop next:;
run;
This approach works by using the current observation in the dataset (obtained via _n_) and adding 1 to it to get the next observation. We then use a second set statement with the point= option to load in that next observation and rename the variables at the same time so that they don't overwrite the current variables.
We then use some logic to flag the necessary records. I'm not 100% of the logic you require for your purposes, so I've provided some sample logic and used different flags to show which logic is being triggered.
Some notes...
The by statement isn't strictly necessary but I'm including it to (a) ensure that the data is sorted correctly, and (b) help future readers understand the intent of the datastep as some of the logic requires this sort order.
The call missing statement is simply there to clean up the log. SAS doesn't like it when you have variables that don't get assigned values, and this will happen on the very last observation so this is why we include this. Comment it out to see what happens.
The end=eof syntax basically creates a temporary variable called eof that has a value of 1 when we get to the last observation on that set statement. We simply use this to determine if we're at the last row or not.
Finally but very importantly, be sure to make sure you are keeping only the variables required when you load in the second dataset otherwise you will overwrite existing vars in the original data.
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.