Insert (internally existing) column headers as first row to a table - sas

Assume that we have a table INPUT_TABLE which has four columns name, lat, lon, and z, filled with many data sets. In the SAS Explorer it would e.g. look like this:
name lat lon z
1 Germany 49.420469 8.7269178 17
2 England 51.5540693 -0.8249039 16
...
I handover a PREPROCESSED_TABLE based on this INPUT_TABLE to a macro %tabl:
data V42.PREPROCESSED_TABLE;
set V21.INPUT_TABLE;
drop NAME;
run;
%tabl(libin=V42, file=PREPROCESSED_TABLE);
The macro itself I am not allowed to modify.
Among other things, %tabl also writes a plain text file PREPROCESSED_TABLE.txt:
49.420469|8.7269178|17
51.5540693|-0.8249039|16
I would like to have the header names written out as well, e.g.:
lat|lon|z
49.420469|8.7269178|17
51.5540693|-0.8249039|16
My idea is to expand the PREPROCESSED_TABLE somewhere in the data step - could somebody help me with that, please? How can I read out the header names which are internally stored?

If the goal is to make a file with one line with the variable names then just write the file yourself. First get the names into a dataset (in order) and then write them. For example you could use PROC TRANSPOSE with OBS=0 dataset option to generate a file with one observation per variable.
proc transpose data=V42.PREPROCESSED_TABLE(obs=0) out=NAMES ;
var _all_ ;
run;
Which you can then use to write to a file.
data _null_;
set names ;
file 'preprocessed.txt' dsd dlm='|';
put _name_ # ;
run;
If you also want to add the data to that same file just use a second data step. Make sure to use the MOD option on the FILE statement so that data lines are appended to the existing file.
data _null_;
set V42.PREPROCESSED_TABLE;
file 'preprocessed.txt' dsd dlm='|' mod;
put (_all_) (+0);
run;
If you need to call the existing macro for other reasons you could either ignore the file it creates. Or if for some reason the content is different than just the simple dump of the file then you could just concatenate the file with the the headers with the file the macro generates. Say the macro generated 'PREPROCESSED_TABLE.txt' and your code generated the one line file 'headers.txt'. Then this step will read both and write 'PREPROCESSED_TABLE_w_headers.txt';
data _null_;
file 'PREPROCESSED_TABLE_w_headers.txt';
if _n_=1 then do;
infile 'headers.txt';
input;
put _infile_;
end;
infile 'PREPROCESSED_TABLE.txt';
input;
put _infile_;
run;

Given Reeza's and Tom's hints, I figured out a workaround myself: We simple call out macro %tabl twice, once with a 1-row-table with column-names and once with the data. This approach essentially corresponds to attaching to the file first the headers and then then data to the file (except that I have to worry about additional things added by %tabl further down in the process chain).
The technical difficulty I had was how to extract this 1-row-table with column names from the meta-info of the table input table V21.INPUT_TABLE.
My team mate showed me how that is done. To make it testable for everybody, I will show this step for the test data table sashelp.class:
proc contents data=sashelp.class out=meta (keep=NAME VARNUM) noprint;
run;
proc sort data=meta out=meta2;
by VARNUM;
run;
proc transpose data=meta2 out=colheaders (drop=_NAME_ _LABEL_);
var name;
run;
As a result, we will have a table colheaders with exactly one line containing the table headers, sorted by VARNUM which is the order in which they appear in the original table:
COL1 COL2 COL3 COL4 COL5
1 NAME SEX AGE HEIGHT WEIGHT
Problem solved, at least theoretically.

Related

Manually Reading in Data in SAS from CSV

So I have a large dataset that is rather oddly formatted and I want to read it in based on the header. It only has unique columns for each unique participant and each participant participated in multiple rounds of the study. The data is from some experiments and is formatted as having variables for each participant (e.g. "participant.code") then some session variables which I can drop and then the actual variables from the experiment. These are formatted as "study.[round number].player.[variable]"
Rather then repeating the variable for every round, I want to just take out the round number as a separate variable and have an observation for every round for each participant.
I want to read these in differently depending on the variable and pick it out. I would rather not have to manually mess with the source file since the experiment is going to be run multiple times.
If someone could just point me towards some relevant material or whatnot that would be great.
Thank you!
Edit: example of some of the raw data:
participant.id_in_session,participant.code,participant.label,participant._is_bot,participant._index_in_pages,participant._max_page_index,participant._current_app_name,participant._current_page_name,participant.time_started_utc,participant.visited,participant.mturk_worker_id,participant.mturk_assignment_id,participant.payoff,session.code,session.label,session.mturk_HITId,session.mturk_HITGroupId,session.comment,session.is_demo,session.config.real_world_currency_per_point,session.config.participation_fee,session.config.name,session.config.treatment,study.1.player.id_in_group,study.1.player.role,study.1.player.payoff,study.1.player.Seatfinal,study.1.player.finalpay,study.1.player.payroundpay,study.1.player.QCorrect,study.1.player.treatment,study.1.player.Q1a,study.1.player.Q1b,study.1.player.Q1c,study.1.player.Q2a,study.1.player.Q3,study.1.player.Q4,study.1.player.Q5,study.1.player.Q6,study.1.player.Q7,study.1.player.Q80,study.1.player.Q81,study.1.player.Q82,study.1.player.offer,study.1.player.OfferNum,study.1.player.OfferTaken,study.1.player.BuyerNumber,study.1.player.Seatnum2,study.1.player.Seatnum,study.1.player.pay,study.1.player.isoffertaken,study.1.player.hastakenoffer,study.1.player.consent,study.1.player.offerPrice,study.1.player.oprice,study.1.player.guess_num_seller,study.1.player.BoughtPrice,study.1.player.reward,study.1.player.guess_num_buyer,study.1.group.id_in_subsession,study.1.subsession.round_number,study.1.subsession.offersrem,study.1.subsession.game_finished,study.1.subsession.numbuyers,study.1.subsession.bnum,study.1.subsession.payround,study.2.player.id_in_group,study.2.player.role,study.2.player.payoff,study.2.player.Seatfinal,study.2.player.finalpay,study.2.player.payroundpay,study.2.player.QCorrect,study.2.player.treatment,study.2.player.Q1a,study.2.player.Q1b,study.2.player.Q1c,study.2.player.Q2a,study.2.player.Q3,study.2.player.Q4,study.2.player.Q5,study.2.player.Q6,study.2.player.Q7,study.2.player.Q80,study.2.player.Q81,study.2.player.Q82,study.2.player.offer,study.2.player.OfferNum,study.2.player.OfferTaken,study.2.player.BuyerNumber,study.2.player.Seatnum2,study.2.player.Seatnum,study.2.player.pay,study.2.player.isoffertaken,study.2.player.hastakenoffer,study.2.player.consent,study.2.player.offerPrice,study.2.player.oprice,study.2.player.guess_num_seller,study.2.player.BoughtPrice,study.2.player.reward,study.2.player.guess_num_buyer,study.2.group.id_in_subsession,study.2.subsession.round_number,study.2.subsession.offersrem,study.2.subsession.game_finished,study.2.subsession.numbuyers,study.2.subsession.bnum,study.2.subsession.payround,study.3.player.id_in_group,study.3.player.role,study.3.player.payoff,study.3.player.Seatfinal,study.3.player.finalpay,study.3.player.payroundpay,study.3.player.QCorrect,study.3.player.treatment,study.3.player.Q1a,study.3.player.Q1b,study.3.player.Q1c,study.3.player.Q2a,study.3.player.Q3,study.3.player.Q4,study.3.player.Q5,study.3.player.Q6,study.3.player.Q7,study.3.player.Q80,study.3.player.Q81,study.3.player.Q82,study.3.player.offer,study.3.player.OfferNum,study.3.player.OfferTaken,study.3.player.BuyerNumber,study.3.player.Seatnum2,study.3.player.Seatnum,study.3.player.pay,study.3.player.isoffertaken,study.3.player.hastakenoffer,study.3.player.consent,study.3.player.offerPrice,study.3.player.oprice,study.3.player.guess_num_seller,study.3.player.BoughtPrice,study.3.player.reward,study.3.player.guess_num_buyer,study.3.group.id_in_subsession,study.3.subsession.round_number,study.3.subsession.offersrem,study.3.subsession.game_finished,study.3.subsession.numbuyers,study.3.subsession.bnum,study.3.subsession.payround,study.4.player.id_in_group,study.4.player.role,study.4.player.payoff,study.4.player.Seatfinal,study.4.player.finalpay,study.4.player.payroundpay,study.4.player.QCorrect,study.4.player.treatment,study.4.player.Q1a,study.4.player.Q1b,study.4.player.Q1c,study.4.player.Q2a,study.4.player.Q3,study.4.player.Q4,study.4.player.Q5,study.4.player.Q6,study.4.player.Q7,study.4.player.Q80,study.4.player.Q81,study.4.player.Q82,study.4.player.offer,study.4.player.OfferNum,study.4.player.OfferTaken,study.4.player.BuyerNumber,study.4.player.Seatnum2,study.4.player.Seatnum,study.4.player.pay,study.4.player.isoffertaken,study.4.player.hastakenoffer,study.4.player.consent,study.4.player.offerPrice,study.4.player.oprice,study.4.player.guess_num_seller,study.4.player.BoughtPrice,study.4.player.reward,study.4.player.guess_num_buyer,study.4.group.id_in_subsession,study.4.subsession.round_number,study.4.subsession.offersrem,study.4.subsession.game_finished,study.4.subsession.numbuyers,study.4.subsession.bnum,study.4.subsession.payround,study.5.player.id_in_group,study.5.player.role,study.5.player.payoff,study.5.player.Seatfinal,study.5.player.finalpay,study.5.player.payroundpay,study.5.player.QCorrect,study.5.player.treatment,study.5.player.Q1a,study.5.player.Q1b,study.5.player.Q1c,study.5.player.Q2a,study.5.player.Q3,study.5.player.Q4,study.5.player.Q5,study.5.player.Q6,study.5.player.Q7,study.5.player.Q80,study.5.player.Q81,study.5.player.Q82,study.5.player.offer,study.5.player.OfferNum,study.5.player.OfferTaken,study.5.player.BuyerNumber,study.5.player.Seatnum2,study.5.player.Seatnum,study.5.player.pay,study.5.player.isoffertaken,study.5.player.hastakenoffer,study.5.player.consent,study.5.player.offerPrice,study.5.player.oprice,study.5.player.guess_num_seller,study.5.player.BoughtPrice,study.5.player.reward,study.5.player.guess_num_buyer,study.5.group.id_in_subsession,study.5.subsession.round_number,study.5.subsession.offersrem,study.5.subsession.game_finished,study.5.subsession.numbuyers,study.5.subsession.bnum,study.5.subsession.payround,study.6.player.id_in_group,study.6.player.role,study.6.player.payoff,study.6.player.Seatfinal,study.6.player.finalpay,study.6.player.payroundpay,study.6.player.QCorrect,study.6.player.treatment,study.6.player.Q1a,study.6.player.Q1b,study.6.player.Q1c,study.6.player.Q2a,study.6.player.Q3,study.6.player.Q4,study.6.player.Q5,study.6.player.Q6,study.6.player.Q7,study.6.player.Q80,study.6.player.Q81,study.6.player.Q82,study.6.player.offer,study.6.player.OfferNum,study.6.player.OfferTaken,study.6.player.BuyerNumber,study.6.player.Seatnum2,study.6.player.Seatnum,study.6.player.pay,study.6.player.isoffertaken,study.6.player.hastakenoffer,study.6.player.consent,study.6.player.offerPrice,study.6.player.oprice,study.6.player.guess_num_seller,study.6.player.BoughtPrice,study.6.player.reward,study.6.player.guess_num_buyer,study.6.group.id_in_subsession,study.6.subsession.round_number,study.6.subsession.offersrem,study.6.subsession.game_finished,study.6.subsession.numbuyers,study.6.subsession.bnum,study.6.subsession.payround,study.7.player.id_in_group,study.7.player.role,study.7.player.payoff,study.7.player.Seatfinal,study.7.player.finalpay,study.7.player.payroundpay,study.7.player.QCorrect,study.7.player.treatment,study.7.player.Q1a,study.7.player.Q1b,study.7.player.Q1c,study.7.player.Q2a,study.7.player.Q3,study.7.player.Q4,study.7.player.Q5,study.7.player.Q6,study.7.player.Q7,study.7.player.Q80,study.7.player.Q81,study.7.player.Q82,study.7.player.offer,study.7.player.OfferNum,study.7.player.OfferTaken,study.7.player.BuyerNumber,study.7.player.Seatnum2,study.7.player.Seatnum,study.7.player.pay,study.7.player.isoffertaken,study.7.player.hastakenoffer,study.7.player.consent,study.7.player.offerPrice,study.7.player.oprice,study.7.player.guess_num_seller,study.7.player.BoughtPrice,study.7.player.reward,study.7.player.guess_num_buyer,study.7.group.id_in_subsession,study.7.subsession.round_number,study.7.subsession.offersrem,study.7.subsession.game_finished,study.7.subsession.numbuyers,study.7.subsession.bnum,study.7.subsession.payround,study.8.player.id_in_group,study.8.player.role,study.8.player.payoff,study.8.player.Seatfinal,study.8.player.finalpay,study.8.player.payroundpay,study.8.player.QCorrect,study.8.player.treatment,study.8.player.Q1a,study.8.player.Q1b,study.8.player.Q1c,study.8.player.Q2a,study.8.player.Q3,study.8.player.Q4,study.8.player.Q5,study.8.player.Q6,study.8.player.Q7,study.8.player.Q80,study.8.player.Q81,study.8.player.Q82,study.8.player.offer,study.8.player.OfferNum,study.8.player.OfferTaken,study.8.player.BuyerNumber,study.8.player.Seatnum2,study.8.player.Seatnum,study.8.player.pay,study.8.player.isoffertaken,study.8.player.hastakenoffer,study.8.player.consent,study.8.player.offerPrice,study.8.player.oprice,study.8.player.guess_num_seller,study.8.player.BoughtPrice,study.8.player.reward,study.8.player.guess_num_buyer,study.8.group.id_in_subsession,study.8.subsession.round_number,study.8.subsession.offersrem,study.8.subsession.game_finished,study.8.subsession.numbuyers,study.8.subsession.bnum,study.8.subsession.payround,study.9.player.id_in_group,study.9.player.role,study.9.player.payoff,study.9.player.Seatfinal,study.9.player.finalpay,study.9.player.payroundpay,study.9.player.QCorrect,study.9.player.treatment,study.9.player.Q1a,study.9.player.Q1b,study.9.player.Q1c,study.9.player.Q2a,study.9.player.Q3,study.9.player.Q4,study.9.player.Q5,study.9.player.Q6,study.9.player.Q7,study.9.player.Q80,study.9.player.Q81,study.9.player.Q82,study.9.player.offer,study.9.player.OfferNum,study.9.player.OfferTaken,study.9.player.BuyerNumber,study.9.player.Seatnum2,study.9.player.Seatnum,study.9.player.pay,study.9.player.isoffertaken,study.9.player.hastakenoffer,study.9.player.consent,study.9.player.offerPrice,study.9.player.oprice,study.9.player.guess_num_seller,study.9.player.BoughtPrice,study.9.player.reward,study.9.player.guess_num_buyer,study.9.group.id_in_subsession,study.9.subsession.round_number,study.9.subsession.offersrem,study.9.subsession.game_finished,study.9.subsession.numbuyers,study.9.subsession.bnum,study.9.subsession.payround,study.10.player.id_in_group,study.10.player.role,study.10.player.payoff,study.10.player.Seatfinal,study.10.player.finalpay,study.10.player.payroundpay,study.10.player.QCorrect,study.10.player.treatment,study.10.player.Q1a,study.10.player.Q1b,study.10.player.Q1c,study.10.player.Q2a,study.10.player.Q3,study.10.player.Q4,study.10.player.Q5,study.10.player.Q6,study.10.player.Q7,study.10.player.Q80,study.10.player.Q81,study.10.player.Q82,study.10.player.offer,study.10.player.OfferNum,study.10.player.OfferTaken,study.10.player.BuyerNumber,study.10.player.Seatnum2,study.10.player.Seatnum,study.10.player.pay,study.10.player.isoffertaken,study.10.player.hastakenoffer,study.10.player.consent,study.10.player.offerPrice,study.10.player.oprice,study.10.player.guess_num_seller,study.10.player.BoughtPrice,study.10.player.reward,study.10.player.guess_num_buyer,study.10.group.id_in_subsession,study.10.subsession.round_number,study.10.subsession.offersrem,study.10.subsession.game_finished,study.10.subsession.numbuyers,study.10.subsession.bnum,study.10.subsession.payround,study.11.player.id_in_group,study.11.player.role,study.11.player.payoff,study.11.player.Seatfinal,study.11.player.finalpay,study.11.player.payroundpay,study.11.player.QCorrect,study.11.player.treatment,study.11.player.Q1a,study.11.player.Q1b,study.11.player.Q1c,study.11.player.Q2a,study.11.player.Q3,study.11.player.Q4,study.11.player.Q5,study.11.player.Q6,study.11.player.Q7,study.11.player.Q80,study.11.player.Q81,study.11.player.Q82,study.11.player.offer,study.11.player.OfferNum,study.11.player.OfferTaken,study.11.player.BuyerNumber,study.11.player.Seatnum2,study.11.player.Seatnum,study.11.player.pay,study.11.player.isoffertaken,study.11.player.hastakenoffer,study.11.player.consent,study.11.player.offerPrice,study.11.player.oprice,study.11.player.guess_num_seller,study.11.player.BoughtPrice,study.11.player.reward,study.11.player.guess_num_buyer,study.11.group.id_in_subsession,study.11.subsession.round_number,study.11.subsession.offersrem,study.11.subsession.game_finished,study.11.subsession.numbuyers,study.11.subsession.bnum,study.11.subsession.payround,study.12.player.id_in_group,study.12.player.role,study.12.player.payoff,study.12.player.Seatfinal,study.12.player.finalpay,study.12.player.payroundpay,study.12.player.QCorrect,study.12.player.treatment,study.12.player.Q1a,study.12.player.Q1b,study.12.player.Q1c,study.12.player.Q2a,study.12.player.Q3,study.12.player.Q4,study.12.player.Q5,study.12.player.Q6,study.12.player.Q7,study.12.player.Q80,study.12.player.Q81,study.12.player.Q82,study.12.player.offer,study.12.player.OfferNum,study.12.player.OfferTaken,study.12.player.BuyerNumber,study.12.player.Seatnum2,study.12.player.Seatnum,study.12.player.pay,study.12.player.isoffertaken,study.12.player.hastakenoffer,study.12.player.consent,study.12.player.offerPrice,study.12.player.oprice,study.12.player.guess_num_seller,study.12.player.BoughtPrice,study.12.player.reward,study.12.player.guess_num_buyer,study.12.group.id_in_subsession,study.12.subsession.round_number,study.12.subsession.offersrem,study.12.subsession.game_finished,study.12.subsession.numbuyers,study.12.subsession.bnum,study.12.subsession.payround,study.13.player.id_in_group,study.13.player.role,study.13.player.payoff,study.13.player.Seatfinal,study.13.player.finalpay,study.13.player.payroundpay,study.13.player.QCorrect,study.13.player.treatment,study.13.player.Q1a,study.13.player.Q1b,study.13.player.Q1c,study.13.player.Q2a,study.13.player.Q3,study.13.player.Q4,study.13.player.Q5,study.13.player.Q6,study.13.player.Q7,study.13.player.Q80,study.13.player.Q81,study.13.player.Q82,study.13.player.offer,study.13.player.OfferNum,study.13.player.OfferTaken,study.13.player.BuyerNumber,study.13.player.Seatnum2,study.13.player.Seatnum,study.13.player.pay,study.13.player.isoffertaken,study.13.player.hastakenoffer,study.13.player.consent,study.13.player.offerPrice,study.13.player.oprice,study.13.player.guess_num_seller,study.13.player.BoughtPrice,study.13.player.reward,study.13.player.guess_num_buyer,study.13.group.id_in_subsession,study.13.subsession.round_number,study.13.subsession.offersrem,study.13.subsession.game_finished,study.13.subsession.numbuyers,study.13.subsession.bnum,study.13.subsession.payround
1,kppf7hjb,,0,221,221,study,FinalPay,2022-04-16 22:08:18.471115,1,,,0.0,lew8kph3,,,,,0,1.0,0.0,externality_control,0,2,Seller,0.0,1,0,0,10,0,125,125,50,100,50,0,0,0,1,1,,,1,3,,0,1,1,100,0,0,,50.0,,,,,,1,1,6,1,5,6,4,2,Seller,0.0,,0,0,0,0,,,,,,,,,,,,,1,1,,0,,,100,0,0,,45.0,,,,,,1,2,6,1,5,6,13,2,Seller,0.0,,0,0,0,0,,,,,,,,,,,,,0,0,,0,,,100,0,0,,,,,,,,1,3,5,1,5,6,6,2,Seller,0.0,,0,0,0,0,,,,,,,,,,,,,1,6,,0,,,138,1,0,,38.0,,,,,,1,4,6,1,5,6,3,2,Seller,0.0,,0,0,0,0,,,,,,,,,,,,,1,2,,0,,,135,1,0,,35.0,,,,,,1,5,6,1,5,6,11,2,Seller,0.0,,0,0,0,0,,,,,,,,,,,,,0,0,,0,,,100,0,0,,,,,,,,1,6,5,1,5,6,6,2,Seller,0.0,,0,0,0,0,,,,,,,,,,,,,1,6,,0,,,132,1,0,,32.0,,,,,,1,7,6,1,5,6,4,2,Seller,0.0,,0,0,0,0,,,,,,,,,,,,,1,5,,0,,,150,1,0,,50.0,,,,,,1,8,6,1,5,6,9,2,Seller,0.0,,0,0,0,0,,,,,,,,,,,,,1,2,,0,,,100,0,0,,49.0,,,,,,1,9,6,1,5,6,10,2,Seller,0.0,,0,0,0,0,,,,,,,,,,,,,1,5,,0,,,100,0,0,,39.0,,,,,,1,10,6,1,5,6,3,2,Seller,0.0,,0,0,0,0,,,,,,,,,,,,,1,1,,0,,,132,1,0,,32.0,,,,,,1,11,6,1,5,6,10,2,Seller,0.0,,0,0,0,0,,,,,,,,,,,,,1,1,,0,,,130,1,0,,30.0,,,,,,1,12,6,1,5,6,8,2,Seller,0.0,1,192,132,10,0,,,,,,,,,,,,,1,2,,0,,,128,1,0,,28.0,,,,,,1,13,6,1,5,6,11
Your file is not really as complicated as it first seems. For example the bulk of the data is just 43 columns that repeat 13 times. The STUDY.1 columns, then STUDY.2 columns etc.
For this one just write a program to read it. There are 22 columns that are not "study" columns. Then 13 copies of the 43 study columns.
data want;
infile csv dsd truncover firstobs=2;
input var1 ..... var22 #;
do study=1 to 13;
input svar1 .... svar43 # ;
output;
end;
run;
So you turn each line into 13 observations (study=1 to study=13).
To complete the sketch of a data step above you just need figure out want names you want to use for the 65 (22 + 43) variables other than STUDY. And for each variable what type of variable it is, numeric or character, and when character what length it needs to store the longest possible value.
If you need to work with a lot of different variations of files in this style then it might be worth working on a program to analyze the headers and determine the role of the columns based on the pattern of the header name and perhaps generate the code to read the file.
You might start by building a dataset with just the header names.
data headers;
infile csv dsd obs=1 ;
length col 8 words 8 ;
col+1;
array header [4] $50 ;
input header1 :$50. ## ;
words=countw(header1,'.');
do _n_=words to 1 by -1;
header[_n_] = scan(header1,_n_,'.');
end;
run;
You can use that list of the headers to help you figure out what would be useful names for the variables.
If you want to let SAS guess how to define and name the variables you could try splitting the CSV file into two separate CSV files. One with the first 22 columns and one with the other 43. So first split the headers (perhaps removing the STUDY.N. prefix while you are at it). Then split the data. Add an ROW number to make it easy to join them later.
filename single temp;
filename multiple temp;
data _null_;
infile csv dsd obs=1 ;
input header :$50. ## ;
file single dsd ;
if _n_=1 then put 'ROW,' #;
if _n_<= 22 then put header #;
else do;
file multiple dsd;
if _n_=23 then put 'ROW,STUDY,'# ;
call scan(header,3,pos,len,'.');
header = substr(header,pos);
put header #;
end;
if _n_=22+43 then stop;
run;
data _null_;
infile csv dsd firstobs=2 truncover ;
row+1;
length s1-s43 $200 ;
input s1-s22 #;
file single dsd mod;
put row s1-s22 ;
file multiple dsd mod;
do study=1 to 13 ;
input s1-s43 # ;
put row study s1-s43 ;
end;
run;
Now you can use PROC IMPORT to GUESS how to read SINGLE and MULTIPLE and then you can join them back together.
proc import file=single dbms=csv out=single replace;
run;
proc import file=multiple dbms=csv out=multiple replace;
run;
data want;
merge single multiple;
by row;
run;

How can I make the first row of a SAS dataset the variable names?

I have an already imported dataset where the first row contains the variable names. I know that typically when importing a dataset you use getnames = yes. However, if the data is already imported how can I make the first row the variable names using a data step?
Data looks like:
A B C
1 Name 1 Name 2 Name 3
2 2 4 66
3 3 5 6
Since reading the names as data probably made all of your variables character you can try just transposing the data twice to fix it. That will work well for small datasets.
So the first transpose will place the current name into the _NAME_ variable and convert each row into a column. The second proc transpose can drop the original name and use the first row (new COL1 variable) as the names.
proc transpose data=have out=wide ;
var _all_;
run;
proc transpose data=wide(drop=_name_ rename=(col1=_name_)) out=want(drop=_name_ _label_);
var col:;
id _name_;
run;
The problem with the already imported data is that all the numeric data was likely placed in a character variables because the 'first row' of data seen by the import process contained some character data, and drove the inference for automatic column construction.
Regardless, you will need to construct renaming pairs old-name=new-name for each variables that has to be renamed. The new-name being in row 1 makes it possible to transpose that row to arrange those name parts as data. SQL with :into and separated by can populate a macro variable for use in a proc datasets step that performs the column renaming without rewriting the entire data set. Finally, a DATA step with modify can remove a row in place, again, without rewriting the entire data set.
filename sandbox temp;
data _null_;
file sandbox;
put 'A,B,C';
put 'Name 1, Name 2, Name 3';
put '2,4,66';
put '3,5,6';
run;
proc import datafile=sandbox dbms=csv replace out=work.oops;
run;
proc transpose data=oops(obs=1) out=renames;
var _all_;
run;
proc sql noprint;
select cats(_name_,"=",compress(col1,,"KN"))
into :renames separated by ' '
from renames;
%put NOTE: &=renames;
proc datasets nolist lib=work;
modify oops;
rename &renames;
run;
data oops;
modify oops;
remove;
stop;
run;
%let syslast=oops;

SAS: Change dataset with loop count into append statement

TOPIC: Change dataset with loop count into append statement
I have a macro that will loop and create a new dataset with a counter behind.
Code like this:
PROC IMPORT OUT=WORK.out&i DATAFILE= "&dir/&name"
/excelout/
DBMS=csv REPLACE; delimiter='09'x; getnames=no; RUN;
data test&i (drop= %do k=1 %to &cnt; &&col&k.. %end;
);
length station $10 voltage $10 year 8 month $20 transformer $10 Day $20 Date Time MW_Imp MW_Exp MVAR_Imp MVAR_Exp MVA
Power_Factor 8; format Time hhmm.; set out&i. end=last;
Currently the script will generate about 4 data sets if i have 4 external files by PROC IMPORT.
What i want is to eliminate the creation of multiple datasets but just append them into the master file. Is there a way to do so?
An append statement inside the loop should be sufficient to achieve this. SAS will copy first dataset as base since it was not existing.
proc append base=test data=test&i force; run;
Appending is probably just as easy, but if you don't want to create many datasets to begin with, you could use a data step to read in several files at once, using wildcards. That would eliminate the need to loop through the files, but does require that the files have the same structure and aren't stored in a folder with other similarly named files. The firstobs-option caused som issues in my tests, but as you have specified getnames=no in your import, I guess you have no need for it.
The snippet below inputs all csv files in c:\test.
data test;
infile "c:\test\*.csv" dsd delimiter='09'x;
input varA $ varB $;
run;

Exporting to a text file in SAS with a double delimitter

I'm trying to use a double pipe delimiter "||" when I export a file from SAS to txt. Unfortunately, it only seems to correctly delimit the header row and uses the single version for the data.
The code is:
proc export data=notes3 outfile='/file_location/notes3.txt'
dbms = dlm;
delimiter = '||';
run;
Which results in:
ID||VAR1||VAR2
1|0|STRING1
2|1|STRING2
3|1|STRING3
If you want to use a two character delimiter, you need to use dlmstr instead of dlm in the file statement in data step file creation. You can't use proc export, unfortunately, as that doesn't support dlmstr.
You can create your own proc export fairly easily, by using dictionary.columns or sashelp.vcolumn to construct the put statement. Feel free to ask more specific questions on that side if you need help with it, but search around for data driven output and you'll most likely find what you need.
The reason proc export won't use a double pipe is because it generates a data step to do the export, which uses a file statement. This is a known limitation - quoting the help file:
Restriction: Even though a character string or character variable is
accepted, only the first character of the string or variable is used
as the output delimiter. This differs from INFILE DELIMITER=
processing.
The header row || works because SAS constructs it as a string constant rather than using a file statement.
So I don't think you can fix the proc export code, but here's a quick and dirty data step that will transform the output into the desired format, provided that your dataset has no missing values and doesn't contain any pipe characters:
/*Export as before to temporary file, using non-printing TAB character as delimiter*/
proc export
data=sashelp.class
outfile="%sysfunc(pathname(work))\temp.txt"
dbms = dlm;
delimiter = '09'x;
run;
/*Replace TAB with double pipe for all rows beyond the 1st*/
data _null_;
infile "%sysfunc(pathname(work))\temp.txt" lrecl = 32767;
file "%sysfunc(pathname(work))\class.txt";
input;
length text $32767;
text = _infile_;
if _n_ > 1 then text = tranwrd(text,'09'x,'||');
put text;
run;
/*View the resulting file in the log*/
data _null_;
infile "%sysfunc(pathname(work))\class.txt";
input;
put _infile_;
run;
As Joe suggested, you could alternatively write your own delimiter logic in a dynamically generated data step, e.g.
/*More efficient option - write your own delimiter logic in a data step*/
proc sql noprint;
select name into :VNAMES separated by ','
from sashelp.vcolumn
where libname = "SASHELP" and memname = "CLASS";
quit;
data _null_;
file "%sysfunc(pathname(work))\class.txt";
set sashelp.class;
length text $32767;
text = catx('||',&VNAMES);
put text;
run;

Need to repeate data reading from multiple files using sas and run freqs on separate dataset created from separate files

I am new to SAS and facing few difficulties while creating following program.
My requirement is to pass the filename generated dynamically and read it so that don't have to write code five times to read data from 5 different files and then run freqs on the datasets.
I have provided the code below and have to write this code for more than 50 files:
Code
filename inp1 '/chshttp/prod/clients/coms/raw/coms_coms_relg_f1102_t1102_c10216_vEL5535.raw';
filename inp2 '/chshttp/prod/clients/coms/raw/coms_coms_relg_f1103_t1103_c10317_vEL8312.raw';
filename inp3 '/chshttp/prod/clients/coms/raw/coms_coms_relg_f1104_t1104_c10420_vEL11614.raw';
filename inp4 '/chshttp/prod/clients/coms/raw/coms_coms_relg_f1105_t1105_c10510_vEL13913.raw';
filename inp5 '/chshttp/prod/clients/coms/raw/coms_coms_relg_f1106_t1106_c10628_vEL17663.raw';
data test;
Do i = 1 to 5;
infile_name = 'inp' || i;
infile infile_name recfm = v lrecl=1800 end=eof truncover;
INPUT
#1 E_CUSTDEF1_CLIENT_ID $CHAR5.
#1235 E_MED_PLAN_CODE $CHAR20.
#1090 MED_INS_ELIG_COVERAGE_IND $CHAR20.
#1064 MED_COVERAGE_BEGIN_DATE $CHAR8.
#1072 MED_COVERAGE_TERM_DATE $CHAR8.
;
if E_CUSTDEF1_CLIENT_ID ='00002' then
output test;
end;
run;
proc freq data = test;
tables E_CUSTDEF1_CLIENT_ID*E_MED_PLAN_CODE / list missing;
run;
Please help!!
Here's an example you can adapt. There are different ways to do this, but this is one- depending no how you want the frequencies.
Step 1: Create a dataset, 'my_filenames', that stores the filename you want to read in, one per line, in a variable FILE_NAME.
Step 2: Read in the files.
data my_data;
set my_filenames;
infile a filevar=file_name <the rest of your options>;
<your input statement>;
run;
proc freq data=mydata;
by file_name;
<your table statements>;
run;
This is simple, data driven code that doesn't require macros or storing large amounts of data in things that shouldn't have data in them (macro variables, filenames, etc.)
To directly answer your question, here is a SAS macro to read each file and run PROC FREQ:
%macro freqme(dsn);
data test;
infile "&dsn" recfm = v lrecl=1800 end=eof truncover;
INPUT #1 E_CUSTDEF1_CLIENT_ID $CHAR5.
#1235 E_MED_PLAN_CODE $CHAR20.
#1090 MED_INS_ELIG_COVERAGE_IND $CHAR20.
#1064 MED_COVERAGE_BEGIN_DATE $CHAR8.
#1072 MED_COVERAGE_TERM_DATE $CHAR8.
;
if E_CUSTDEF1_CLIENT_ID = '00002';
run;
proc freq data=test;
tables E_CUSTDEF1_CLIENT_ID*E_MED_PLAN_CODE / list missing;
run;
proc delete data=test;
run;
%mend;
%freqme(/chshttp/prod/clients/coms/raw/coms_coms_relg_f1102_t1102_c10216_vEL5535.raw);
%freqme(/chshttp/prod/clients/coms/raw/coms_coms_relg_f1103_t1103_c10317_vEL8312.raw);
%freqme(/chshttp/prod/clients/coms/raw/coms_coms_relg_f1104_t1104_c10420_vEL11614.raw);
%freqme(/chshttp/prod/clients/coms/raw/coms_coms_relg_f1105_t1105_c10510_vEL13913.raw);
%freqme(/chshttp/prod/clients/coms/raw/coms_coms_relg_f1106_t1106_c10628_vEL17663.raw);
Note that I added a PROC DELETE step to delete the SAS data set after creating the report. I did that more for illustration, since you don't say you need the file as a SAS data set for subsequent processing.
You can use this as a template for other macro programming.