I want to sweep each table in a libname and calculate a hash over each row.
For that purpose, i have already a table with libname, memname, concatenated columns with ',' and number of observations
libname
memname
columns
num_obs
lib_A
table_A
col1a,col2a...colna
1
lib_A
table_B
col1b,col2b...colnb
2
lib_B
table_C
col1c,col2c...colnc
1
I first get all data into ranged macro variables (i think its easier to work, but could be wrong, ofc)
proc sql;
select libname, memname, columns, num_obs
into :lib1-, :tab1-, :column1-, :sqlobs1-
from have
where libname="&sel_livraria"; /*macro var = prompt from user*/
quit;
Just for developing guideline i made the code just to check one specific table without getting the row number of it since with a simple counter doesn't work (i get the order of the rows mess up each time i run) and it works for that purpose
%let lib=lib_A;
%let tab=table_B;
%let columns=col1b,col2b,colnb;
data want;
length check $32.;
format check $hex32.;
set &lib..&tab;
libname="&lib";
memname="&tab";
check = md5(cats(&columns));
hash = put(check,$hex32.);
keep libname memname hash;
put hash;
put _all_;
run;
So, what’s the best approach for getting a MD5 from each row (same order as tables) of all tables in a libname? I saw problems i couldn’t overcame using data steps, procs or macros.
The result i wanted if lib_A was selected in prompt were something like:
libname
memname
obs_row
hash
lib_A
table_A
1
64A29CCA15F53C83A9583841294A26AA
lib_A
table_B
1
80DAC7B9854CF71A67F9C00A7EC4D9EF
lib_A
table_B
2
0AC44CD79DAB2E33C93BB2312D3A9A40
Need some help.
Tks in advance.
You're pretty close. This is how I would approach it. We'll create a macro with three parameters: data, lib, and out. data is the dataset you have with the column information. lib is the library you want to pull from your dataset, and out is the output dataset that you want to have.
We'll read each column into an individual macro variable:
memname1
memname2
memname3
libname1
libname2
libname3
etc.
From here, we simply need to loop over all of the macro variables and apply them where appropriate. We can easily count how many there are in a data step. All we need to do is add double-ampersands to resolve them correctly. For more information on why this is, check out this MWSUG paper.
%macro get_md5(data=, lib=, out=);
/* Save all variables into macro variables:
memname1 memname2 ...
columns1 columns2 ...
*/
data _null_;
set &data.;
where upcase(libname)=upcase("&lib.");
call symputx(cats('memname', _N_), memname);
call symputx(cats('columns', _N_), columns);
call symputx(cats('obs', _N_), obs);
call symputx('n_datasets', _N_);
run;
/* Loop through all the datasets and access each macro variable */
%do i = 1 %to &n_datasets.;
/* Double ampersand needed:
First, resolve &i. to get &memname1
Then resolve &mename1 to get the value stored in the macro variable memname1
*/
%let memname = &&memname&i.;
%let columns = &&columns&i.;
%let obs = &&obs&i.;
/* Calculate md5 in a temporary dataset */
data _tmp_;
length lib $8.
memname $32.
obs_row 8.
hash $32.
;
set &lib..&memname.(obs=&obs.);
lib = "&lib.";
memname = "&memname.";
obs_row = _N_;
hash = put(md5(cats(&columns.)), $hex32.);
keep libname memname obs_row hash;
run;
/* Overwrite the dataset so we don't keep appending */
%if(&i. = 1) %then %do;
data &out.;
set _tmp_;
run;
%end;
%else %do;
proc append base=&out. data=_tmp_;
run;
%end;
%end;
/* Remove temporary data */
proc datasets lib=work nolist;
delete _tmp_;
quit;
%mend;
Example:
data have;
length libname memname columns $15.;
input libname$ memname$ columns$ obs;
datalines;
sashelp cars make,model,msrp 1
sashelp class age,height,name 2
sashelp comet dose,length,sample 1
;
run;
%get_md5(data=have, lib=sashelp, out=want);
Output:
libname memname obs_row hash
sashelp cars 1 258DADA4843E7068ABAF95667E881B7F
sashelp class 1 29E8F4F03AD2275C0F191FE3DAA03778
sashelp class 2 DB664382B88BE7E445418B1A1C8CE13B
sashelp comet 1 210394B77E7696506FDEFD78890A8AB9
I would make a macro that takes as input the four values in your metadata dataset. Note that commas are anathema to SAS programs, especially macro code, so make the macro so it can accept space delimited variable lists (like normal SAS program statements do).
To reduce the risk of name conflict I will name the variable using triple underscores and then rename them back to human friendly names when the dataset is written.
%macro next_ds(libname,memname,num_obs,varlist);
data next_ds;
length ___1 $8 ___2 $32 ___3 8 ___4 $32 ;
___1 = "&libname";
___2 = "&memname";
___3 + 1;
set &libname..&memname(obs=&num_obs keep=&varlist);
___4 = put(md5(cats(of &varlist)),$hex32.);
keep ___1-___4 ;
rename ___1=libname ___2=memname ___3=obs_row ___4=hash;
run;
%mend next_ds;
Let's make some test metadata that reference datasets everyone should have.
data have;
infile cards truncover ;
input libname :$8. memname :$32. num_obs columns $200.;
cards;
sashelp class 3 name,sex,age
sashelp cars 2 make,model
;
And make sure the target dataset does not already exists.
%if %sysfunc(exist(want)) %then %do;
proc delete data=want; run;
%end;
Now you can call that macro once for each observation in your source metadata dataset. There is no need to generated oodles of macro variables. Instead you can use CALL EXECUTE() to generate the macro calls directly from the dataset.
We can replace the commas in the column lists when making the macro call. You can add in a PROC APPEND step after each macro call to aggregate the results into a single dataset.
data _null_;
set have;
call execute(cats(
'%nrstr(%next_ds)(',libname,',',memname,',',num_obs
,',',translate(columns,' ',','),')'
));
call execute('proc append data=next_ds base=want force; run;');
run;
Notice that wrapping the macro call in %NRSTR() makes the SAS log easier to read.
1 + %next_ds(sashelp,class,3,name sex age)
2 + proc append data=next_ds base=want force; run;
3 + %next_ds(sashelp,cars,2,make model)
4 + proc append data=next_ds base=want force; run;
Results:
Obs libname memname obs_row hash
1 sashelp class 1 5425E9CEDA1DDEB71B2692A3C7050A8A
2 sashelp class 2 C532D227D358A3764C2D225DC8C02D18
3 sashelp class 3 13AD5F1517E0C4494780773B6DC15211
4 sashelp cars 1 777C60693BF5E16F38706C89301CD0A8
5 sashelp cars 2 07080C9321145395D1A2BCC10FBE6B83
Note that CATS() might not be the best method for generating the string to pass to the MD5() function. That can generate the same string for different combinations of the source variables. For example 'AB' || 'CD' is the same as 'A' || 'BCD'. Perhaps just use CAT() instead.
Stu's approach is nice, and will work most of the time but will fall over when you have wiiiide variables, a large number of variables, variables with large precision, and other edge cases.
So for the actual hashing part, you might consider this macro, which is extensively tested within Data Controller for SAS:
https://core.sasjs.io/mp__md5_8sas.html
Usage:
data _null_;
set sashelp.class;
hashvar=%mp_md5(cvars=name sex, nvars=age height weight);
put hashvar=;
run;
Related
Suppose there are ten datasets with same structure: date and price, particularly they have same time period but different price
date price
20140604 5
20140605 7
20140607 9
I want to combine them and create a panel dataset. Since there is no name in each datasets, I attempt to add a new variable name into each data and then combine them.
The following codes are used to add name variable into each dataset
%macro name(sourcelib=,from=,going=);
proc sql noprint; /*read datasets in a library*/
create table mytables as
select *
from dictionary.tables
where libname = &sourcelib
order by memname ;
select count(memname)
into:obs
from mytables;
%let obs=&obs.;
select memname
into : memname1-:memname&obs.
from mytables;
quit;
%do i=1 %to &obs.;
data
&going.&&memname&i;
set
&from.&&memname&i;
name=&&memname&i;
run;
%end;
%mend;
So, is this strategy correct? Whether are there a different way to creating a panel data?
There are really two ways to setup repeated measures data. You can use the TALL method that your code will create. That is generally the most flexible. The other would be a wide format with each PRICE being stored in a different variable. That is usually less flexible, but can be easier for some analyses.
You probably do not need to use macro code or even code generation to combine 10 datasets. You might find that it is easier to just type the 10 dataset names than to write complex code to pull the names from metadata. So a data step like this will let you list any number of datasets in the SET statement and use the membername as the value for the new PANEL variable that distinguishes the source dataset.
data want ;
length dsn $41 panel $32 ;
set in1.panel1 in1.panela in1.panelb indsname=dsn ;
panel = scan(dsn,-1,'.') ;
run;
And if your dataset names follow a pattern that can be used as a member list in the SET statement then the code is even easier to write. So you could have a list of names that have a numeric suffix.
set in1.panel1-in1.panel10 indsname=dsn ;
or perhaps names that all start with a particular prefix.
set in1.panel: indsname=dsn ;
If the different panels are for the same dates then perhaps the wide format is easier? You could then merge the datasets by DATE and rename the individual PRICE variables. That is generate a data step that looks like this:
data want ;
merge in1.panel1 (rename=(price=price1))
in1.panel2 (rename=(price=price2))
...
;
by date;
run;
Or perhaps it would be easier to add a BY statement to the data set that makes the TALL dataset and then transpose it into the WIDE format.
data tall;
length dsn $41 panel $32 ;
set in1.panel1 in1.panela in1.panelb indsname=dsn ;
by date ;
panel = scan(dsn,-1,'.') ;
run;
proc transpose data=tall out=want ;
by date;
id panel;
var price ;
run;
I can't comment on the SQL code but the strategy is correct. Add a name to each data set and then panel on the name with the PANELBY statement.
That is a valid way to achieve what you are looking for.
You are going to need 2 . in between the macros for library.data syntax. The first . is used to concatenate. The second shows up as a ..
I assume you will want to append all of these data sets together. You can add
data &going..want;
set
%do i=1 %to &obs;
&from..&&memname&i
%end;
;
run;
You can combine your loop that adds the names and that data step like this:
data &going..want;
set
%do i=1 %to &obs;
&from..&&memname&i (in=d&i)
%end;
;
%do i=1 %to &obs;
if d&i then
name = &&memname&i;
%end;
run;
I have an output table that contains 300+ variables from 30 different tables that are joined by UNION, which is used for modelling. I have created a macro that creates a report with a number of statistics, such as mean, min/max values etc. using this output table. I am trying to add a column to the report that details which table(s) the variables come from. I say table(s) as some of the variables are shared across different tables. I want to avoid having the same variable in the report multiple times as the statistics are the same irrespective of what table the variable comes from. Is there an efficient way to do this?
Instead of UNION consider using a DATA STEP and then use the INDSNAME option instead.
data want;
set sashelp.class sashelp.cars indsname=source;
source_dataset = source;
run;
If it were me, I would loop over each of the union datasets and just put the table name and variable names into a compiled dataset. You probably have all the table names in either a macro list or typed out, so you can just add a few more lines of code to run proc contents on each of those to compile a full list of table and variable names. Note that like your example, there will be duplicate variable names that you can modify after the table is compiled:
** create different tables **;
data height; set sashelp.class(keep=name height); run;
data weight; set sashelp.class(keep=name weight); run;
data sex; set sashelp.class(keep=name sex); run;
** put your datasets into a list either manually or dynamically **;
/* manually */
%let ds_list=height weight sex;
/* dynamically -- be careful to include only tables in your union */
proc sql noprint;
select MEMNAME
into: ds_list separated by " "
from sashelp.vmember
where libname = "WORK" and memname not in ("SASMACR","FORMATS");
quit;
%put &ds_list.;
** loop over each table to put the table name and variables in a dataset **;
%MACRO get_names(ds_list);
%do i=1 %to %sysfunc(countw(&ds_list.));
%let ds = %scan(&ds_list.,&i.);
proc contents data = &ds. noprint
out=names_&ds.(keep=MEMNAME NAME rename=(MEMNAME=SOURCE_DATASET));
run;
proc append data = names_&ds. base=full force; run;
%end;
%MEND;
%get_names(&ds_list.);
I managed to do this using the following:
Create table with source tables.
PROC SQL;
CREATE TABLE SOURCES AS
SELECT NAME
,MEMNAME
FROM DICTIONARY.COLUMNS
WHERE LIBNAME='LIBNAME'
ORDER BY 1,2;
RUN;
Join to my stats table.
PROC SQL;
CREATE TABLE STATS_NEW AS
SELECT memname AS TABLE_NAME,a.*
FROM STATS a
LEFT JOIN SOURCES b
ON a.name = b.name
GROUP BY a.name
ORDER BY a.name;
QUIT;
Transpose data and add in comma separators.
DATA STATS_TRANSPOSE (drop=TABLE_NAME);
LENGTH INPUT_TABLES $1000;
SET STATS_NEW;
BY name;
RETAIN INPUT_TABLES;
IF FIRST.name THEN DO; INPUT_TABLES=TABLE_NAME; END;
IF NOT FIRST.name
THEN DO;
INPUT_TABLES=CATS(INPUT_TABLES,', ',TABLE_NAME);
END;
IF LAST.name THEN DO;
IF name IN ('FIELD1','FIELD2')
THEN DO; INPUT_TABLES='ALL'; END;
OUTPUT;
END;
RUN;
I have multiple tables in a library call snap1:
cust1, cust2, cust3, etc
I want to generate a loop that gets the records' count of the same column in each of these tables and then insert the results into a different table.
My desired output is:
Table Count
cust1 5,000
cust2 5,555
cust3 6,000
I'm trying this but its not working:
%macro sqlloop(data, byvar);
proc sql noprint;
select &byvar.into:_values SEPARATED by '_'
from %data.;
quit;
data_&values.;
set &data;
select (%byvar);
%do i=1 %to %sysfunc(count(_&_values.,_));
%let var = %sysfunc(scan(_&_values.,&i.));
output &var.;
%end;
end;
run;
%mend;
%sqlloop(data=libsnap, byvar=membername);
First off, if you just want the number of observations, you can get that trivially from dictionary.tables or sashelp.vtable without any loops.
proc sql;
select memname, nlobs
from dictionary.tables
where libname='SNAP1';
quit;
This is fine to retrieve number of rows if you haven't done anything that would cause the number of logical observations to differ - usually a delete in proc sql.
Second, if you're interested in the number of valid responses, there are easier non-loopy ways too.
For example, given whatever query that you can write determining your table names, we can just put them all in a set statement and count in a simple data step.
%let varname=mycol; *the column you are counting;
%let libname=snap1;
proc sql;
select cats("&libname..",memname)
into :tables separated by ' '
from dictionary.tables
where libname=upcase("&libname.");
quit;
data counts;
set &tables. indsname=ds_name end=eof; *9.3 or later;
retain count dataset_name;
if _n_=1 then count=0;
if ds_name ne lag(ds_name) and _n_ ne 1 then do;
output;
count=0;
end;
dataset_name=ds_name;
count = count + ifn(&varname.,1,1,0); *true, false, missing; *false is 0 only;
if eof then output;
keep count dataset_name;
run;
Macros are rarely needed for this sort of thing, and macro loops like you're writing even less so.
If you did want to write a macro, the easier way to do it is:
Write code to do it once, for one dataset
Wrap that in a macro that takes a parameter (dataset name)
Create macro calls for that macro as needed
That way you don't have to deal with %scan and troubleshooting macro code that's hard to debug. You write something that works once, then just call it several times.
proc sql;
select cats('%mymacro(name=',"&libname..",memname,')')
into :macrocalls separated by ' '
from dictionary.tables
where libname=upcase("&libname.");
quit;
¯ocalls.;
Assuming you have a macro, %mymacro, which does whatever counting you want for one dataset.
* Updated *
In the future, please post the log so we can see what is specifically not working. I can see some issues in your code, particularly where your macro variables are being declared, and a select statement that is not doing anything. Here is an alternative process to achieve your goal:
Step 1: Read all of the customer datasets in the snap1 library into a macro variable:
proc sql noprint;
select memname
into :total_cust separated by ' '
from sashelp.vmember
where upcase(memname) LIKE 'CUST%'
AND upcase(libname) = 'SNAP1';
quit;
Step 2: Count the total number of obs in each data set, output to permanent table:
%macro count_obs;
%do i = 1 %to %sysfunc(countw(&total_cust) );
%let dsname = %scan(&total_cust, &i);
%let dsid=%sysfunc(open(&dsname) );
%let nobs=%sysfunc(attrn(&dsid,nobs) );
%let rc=%sysfunc(close(&dsid) );
data _total_obs;
length Member_Name $15.;
Member_Name = "&dsname";
Total_Obs = &nobs;
format Total_Obs comma8.;
run;
proc append base=Total_Obs
data=_total_obs;
run;
%end;
proc datasets lib=work nolist;
delete _total_obs;
quit;
%mend;
%count_obs;
You will need to delete the permanent table Total_Obs if it already exists, but you can add code to handle that if you wish.
If you want to get the total number of non-missing observations for a particular column, do the same code as above, but delete the 3 %let statements below %let dsname = and replace the data step with:
data _total_obs;
length Member_Name $7.;
set snap1.&dsname end=eof;
retain Member_Name "&dsname";
if(NOT missing(var) ) then Total_Obs+1;
if(eof);
format Total_Obs comma8.;
run;
(Update: Fixed %do loop in step 2)
I'm working with a rather large several dataset that are provided to me as a CSV files. When I attempt to import one of the files the data will come in fine but, the number of variables in the file is too large for SAS, so it stops reading the variable names and starts assigning them sequential numbers. In order to maintain the variable names off of the data set I read in the file with the data row starting on 1 so it did not read the first row as variable names -
proc import file="X:\xxx\xxx\xxx\Extract\Live\Live.xlsx" out=raw_names dbms=xlsx replace;
SHEET="live";
GETNAMES=no;
DATAROW=1;
run;
I then run a macro to start breaking down the dataset and rename the variables based on the first observations in each variable -
%macro raw_sas_datasets(lib,output,start,end);
data raw_names2;
raw_names;
if _n_ ne 1 then delete;
keep A -- E &start. -- &end.;
run;
proc transpose data=raw_names2 out=raw_names2;
var A -- &end.;
run;
data raw_names2;
set raw_names2;
col1=compress(col1);
run;
data raw_values;
set raw;
keep A -- E &start. -- &end.;
run;
%macro rename(old,new);
data raw_values;
set raw_values;
rename &old.=&new.;
run;
%mend rename;
data _null_;
set raw_names2;
call execute('%rename('||_name_||","||col1||")");
run;
%macro freq(var);
proc freq data=raw_values noprint;
tables &var. / out=&var.;
run;
%mend freq;
data raw_names3;
set raw_names2;
if _n_ < 6 then delete;
run;
data _null_;
set raw_names3;
call execute('%freq('||col1||")");
run;
proc sort data=raw_values;
by StudySubjectID;
run;
data &lib..&output.;
set raw_values;
run;
%mend raw_sas_datasets;
The problem I'm running into is that the variable names are now all set properly and the data is lined up correctly, but the labels are still the original SAS assigned sequential numbers. Is there any way to set all of the labels equal to the variable names?
If you just want to remove the variable labels (at which point they default to the variable name), that's easy. From the SAS Documentation:
proc datasets lib=&lib.;
modify &output.;
attrib _all_ label=' ';
run;
I suspect you have a simpler solution than the above, though.
The actual renaming step needs to be done differently. Right now it's rewriting the entire dataset over and over again - for a lot of variables that is a terrible idea. Get your rename statements all into one datastep, or into a PROC DATASETS, or something else. Look up 'list processing SAS' for details on how to do that; on this site or on google you will find lots of solutions.
You likely can get SAS to read in the whole first line. The number of variables isn't the problem; it is probably the length of the line. There's another question that I'll find if I can on this site from a few months ago that deals with this exact problem.
My preferred option is not to use PROC IMPORT for CSVs anyway; I would suggest writing a metadata table that stores the variable names and the length/types for the variables, then using that to write import code. A little more work at first, but only has to be done once per study and you guarantee PROC IMPORT isn't making silly decisions for you.
In the library sashelp is a table vcolumn. vcolumn contains all the names of your variables for each library by table. You could write a macro that puts all your variable names into macro variables and then from there set the label.
Here's some code that I put together (not very pretty) but it does what you're looking for:
data test.label_var;
x=1;
y=1;
label x = 'xx';
label y = 'yy';
run;
proc sql noprint;
select count(*) into: cnt
from sashelp.vcolumn
where memname = 'LABEL_VAR';quit;
%let cnt = &cnt;
proc sql noprint;
select name into: name1 - :name&cnt
from sashelp.vcolumn
where memname = 'LABEL_VAR';quit;
%macro test;
%do i = 1 %to &cnt;
proc datasets library=test nolist;
modify label_var;
label &&name&i=&&name&i;
quit;
%end;
%mend test;
%test;
I have several databases, one per geographical variables, that I want to append in the end. I am doing some data steps on them. As I have large databases, I select only the variables I need when I first call each table. But on tables in which one variable always equals 0, the variable is not in the table.
So when I select my (keep=var) in a for loop, it works fine if the variable exists, but it produces an error in the other case, so that these tables are ignored.
%do i=1 to 10 ;
data temp;
set area_i(keep= var1 var2);
run;
proc append base=want data=temp force;
run;
%end;
Is there a simple way to tackle that ?
In fact I have found a solution : the DKRICOND (or DKROCOND) options specify the level of error detection to report when a variable is missing from respectively an input (or output) data set during the processing of a DROP=, KEEP=, or RENAME= data set option.
The options are DKRICOND=ERROR | WARN | WARNING | NOWARN | NOWARNING, so you just wave to set
dkricond=warn
/*your program, in my case :*/
%do i=1 to 10 ;
data temp;
set area_i(keep= var1 var2);
run;
proc append base=want data=temp force;
run;
%end;
dkricond=error /* the standard value, probably better to set it back after/ */
How about just adding it to the table if it doesn't already exist?
/*look at dictionary.columns to see if the column already exists*/
proc sql;
select name into :flag separated by ' ' from dictionary.columns where libname = 'WORK' and memname = 'AREA_I' and name = 'VAR1';
run;
/*if it doesn't, then created it as empty*/
%if &flag. ne VAR1 %then %do;
data area_i;
set area_i;
call missing(var1);
run;
%end;