I am working with a table with more than 50 columns. I am trying to replace the value of multiple columns using a lookup table.
Table:
data have;
infile datalines delimiter=",";
input ID $1. SUB_ID :$2. COUNTRY :$2. A $1. B $1.;
datalines;
1,A,FR,A,B
2,B,CH,,B
3,C,DE,B,A
4,D,CZ,,B
5,E,GE,A,
6,F,EN,B,
7,G,US,,A
;
run;
Lookup table:
data lookup;
infile datalines delimiter=",";
input value_before $1. value_after :$2.;
datalines;
A,1
B,2
C,3
;
run;
Actual code:
data want;
if 0 then set lookup;
if _n_ = 1 then do;
declare hash lookup(dataset:'lookup');
lookup.defineKey('value_before');
lookup.defineData('value_after');
lookup.defineDone();
end;
set have;
if (lookup.find(key:A) = 0) then
A = value_after;
if (lookup.find(key:B) = 0) then
B = value_after;
/* ... */
/* if (lookup.find(key:Z) = 0) then
Z = value_after; */
drop value_before value_after;
run;
I guess this code would do the job if I would hardcode the 50 columns.
I wonder if there is a way to "apply" the hash.find() to all variables except the first three (ID, SUB_ID and Country) (maybe by indexing ?) without having to hardcode them or to use macros. For the sake of example I only computed 2 variables to replace the value (A and B) but there are more than 50 (with really different names and no pattern like var1,var2,...,varn).
In cases like this, I like to use proc sql and the dictionary table to fill in the column names for me to create an array. The below code will pull the variable names from dictionary.columns and save them as space-delimited into the macro variable varnames. We can feed this into an array and then use array logic to do the rest.
proc sql noprint;
select name
into :varnames separated by ' '
from dictionary.columns
where libname = 'WORK'
AND memname = 'HAVE'
AND name NOT IN('ID', 'SUB_ID', 'COUNTRY')
;
quit;
data want;
if 0 then set lookup;
if _n_ = 1 then do;
declare hash lookup(dataset:'lookup');
lookup.defineKey('value_before');
lookup.defineData('value_after');
lookup.defineDone();
end;
set have;
array vars[*] &varnames.;
do i = 1 to dim(vars);
if lookup.Find(key:vars[i])=0 then vars[i] = value_after;
end;
drop value_before value_after i;
run;
Related
I have a dataset (a) that looks like this:
Name Value
Cost_1 28
Cost_2 22
Unit_1 Fixed
Unit_2 C
Is it possible to use an array to have a dataset that looks like this:
Name Cat_1 Cat_2
Cost 28 22
Unit Fixed C
%let Cat_Count = 2;
data b;
set a;
array category [&Cat_Count] cat_1-cat_&Cat_count;
.
.
.
run;
Not sure how to execute this...the macro variable cat_count will be dynamic.
You can use array's but a transpose is more efficient.
First create a new column that separates name into the name and count and then use a proc transpose.
data have;
input Name $ Value $;
cards;
Cost_1 28
Cost_2 22
Unit_1 Fixed
Unit_2 C
;;;;
run;
data have_cat;
set have;
cat = input(scan(name, 2, "_"), 8.); *numeric conversion not required for this approach but for array approach;
name = scan(name, 1, "_");
run;
proc sort data=have_cat;
by name cat value;
run;
proc transpose data=have_cat out=want prefix=cat_;
by name;
id cat;
var value;
run;
Array method - requires everything before PROC TRANSPOSE and max_count macro variable.
%let Cat_Count = 2;
data want_array;
set have_cat;
by name;
array category(&cat_count) $ cat_1-cat_&cat_count;
retain cat_1-cat_&cat_count;
if first.name then
call missing(of category (*));
category(cat) = value;
if last.name then output;
run;
I have the following data
DATA HAVE;
input yr_2001 yr_2002 yr_2003 area;
cards;
1 1 1 3
0 1 0 4
0 0 1 3
1 0 1 6
0 0 1 4
;
run;
I want to do the following proc freq for variable yr_2001 to yr_2003.
proc freq data=have;
table yr_2001*area;
where yr_2001=1;
run;
Is there a way I can do it without having to repeat it for each year, may be using a loop for proc freq??
Two ways:
1. Transpose it
Add a counter variable to your data, n, and transpose it by n area, then only keep values where the year flag is equal to 1. Because we set an index on the transposed group year, we do not need to re-sort it before doing by-group processing.
data have2;
set have;
n = _N_;
run;
proc transpose data=have
name=year
out=have2_tpose(rename = (COL1 = year_flag)
where = (year_flag = 1)
index = (year)
drop = n
);
by n area;
var yr_:;
run;
proc freq data=have2_tpose;
by year;
table area;
run;
2. Macro loop
Since they all start with yr_, it will be easy to get all the variable names from dictionary.columns and loop over all the variables. We'll use SQL to read the names into a |-separated list and loop over that list.
proc sql noprint;
select name
, count(*)
into :varnames separated by '|'
, :nVarnames
from dictionary.columns
where memname = 'HAVE'
AND libname = 'WORK'
AND name LIKE "yr_%"
;
quit;
/* Take a look at the variable names we found */
%put &varnames.;
/* Loop over all words in &varnames */
%macro freqLoop;
%do i = 1 %to &nVarnames.;
%let varname = %scan(&varnames., &i., |);
title "&varname.";
proc freq data=have;
where &varname. = 1;
table &varname.*area;
run;
title;
%end;
%mend;
%freqLoop;
So I have a dataset with one primary key: unique_id and 1200 variables. This dataset is generated from a macro so the number of columns will not be fixed. I need to split this dataset into 4 or more datasets of 250 variables each, and each of these smaller datasets should contain the primary key so that I can merge them back later. Can somebody help me with either a sas function or a macro to solve this?
Thanks in advance.
A simple way to split a datasets in the way you request is to use a single data step with multiple output datasets where each one has a KEEP= dataset option listing the variables to keep. For example:
data split1(keep=Name Age Height) split2(keep=Name Sex Weight);
set sashelp.class;
run;
So you need to get the list of variables and group then into sets of 250 or less. Then you can use those groupings to generate code like above. Here is one method using PROC CONTENTS to get the list of variables and CALL EXECUTE() to generate the code.
I will use macro variables to hold the name of the input dataset, the key variable that needs to be kept on each dataset and maximum number of variables to keep in each dataset.
So for the example above those macro variable values would be:
%let ds=sashelp.class;
%let key=name;
%let nvars=2;
So use PROC CONTENTS to get the list of variable names:
proc contents data=&ds noprint out=contents; run;
Now run a data step to split them into groups and generate a member name to use for the new split dataset. Make sure not to include the KEY variable in the list of variables when counting.
data groups;
length group 8 memname $41 varnum 8 name $32 ;
group +1;
memname=cats('split',group);
do varnum=1 to &nvars while (not eof);
set contents(keep=name where=(upcase(name) ne %upcase("&key"))) end=eof;
output;
end;
run;
Now you can use that dataset to drive the generation of the code:
data _null_;
set groups end=eof;
by group;
if _n_=1 then call execute('data ');
if first.group then call execute(cats(memname,'(keep=&key'));
call execute(' '||trim(name));
if last.group then call execute(') ');
if eof then call execute(';set &ds;run;');
run;
Here are results from the SAS log:
NOTE: CALL EXECUTE generated line.
1 + data
2 + split1(keep=name
3 + Age
4 + Height
5 + )
6 + split2(keep=name
7 + Sex
8 + Weight
9 + )
10 + ;set sashelp.class;run;
NOTE: There were 19 observations read from the data set SASHELP.CLASS.
NOTE: The data set WORK.SPLIT1 has 19 observations and 3 variables.
NOTE: The data set WORK.SPLIT2 has 19 observations and 3 variables.
Just another way of doing it using macro variables:
/* Number of columns you want in each chunk */
%let vars_per_part = 250;
/* Get all the column names into a dataset */
proc contents data = have out=cols noprint;
run;
%macro split(part);
/* Split the columns into 250 chunks for each part and put it into a macro variable */
%let fobs = %eval((&part - 1)* &vars_per_part + 1);
%let obs = %eval(&part * &vars_per_part);
proc sql noprint;
select name into :cols separated by " " from cols (firstobs = &fobs obs = &obs) where name ~= "uniq_id";
quit;
/* Chunk up the data only keeping those varaibles and the uniq_id */
data want_part∂
set have (keep = &cols uniq_id);
run;
%mend;
/* Run this from 1 to whatever the increment required to cover all the columnns */
%split(1);
%split(2);
%split(3);
this is not a complete solution but some help to give you another insight into how to solve this. The previous solutions have relied much on proc contents and data step, but I would solve this using proc sql and dictionary.columns. And I would create a macro that would split the original file into as many parts as needed, 250 cols each. The steps roughly:
proc sql; create table as _colstemp as select * from dictionary.columns where library='your library' and memname = 'your table' and name ne 'your primary key'; quit;
Count the number of files needed somewhere along:
proc sql;
select ceil(count(*)/249) into :num_of_datasets from _colstemp;
select count(*) into :num_of_cols from _colstemp;
quit;
Then just loop over the original dataset like:
%do &_i = 1 %to &num_of_datasets
proc sql;
select name into :vars separated by ','
from _colstemp(firstobs=%eval((&_i. - 1)*249 + 1) obs = %eval(min(249,&num_of_cols. - &_i. * 249)) ;
quit;
proc sql;
create table split_&_i. as
select YOUR_PRIMARY_KEY, &vars from YOUR_ORIGINAL_TABLE;
quit;
%end;
Hopefully this gives you another idea. The solution is not tested, and may contain some pseudocode elements as it's written from my memory of doing things. Also this is void of macro declaration and much of parametrization one could do.. This would make the solution more general (parametrize your number of variables for each dataset, your primary key name, and your dataset names for example.
I'm trying to transpose a dataset however i'm getting the attached result in my table. I'm creating thee extra repeated rows but I'm not sure how to summarize my data so that there are only unique "test" labels and no blank GLH values SASresult
array leaners{*} Learners1-Learners3;
do index = 1 to dim(leaners);
ind = index;
test = leaners{index};
output;
end;
array GLH{*} TotalGLHYear1-TotalGLHYear3;
do index = 1 to dim(GLH);
ind = index;
GLHall = GLH{index};
output;
end;
keep Region test GLHall;
Option 1: You can save the distinct rows to a new table using proc sql:
proc sql;
create table work.want as
select distinct(*) from work.have ;
quit;
Option 2: You can remove duplicates from your table using proc sort:
proc sort data=work.have noduprecs;
by _all_ ; Run;
Data set have has some columns with prefix Dex. But I don't know how many columns exactly with that prefix.
I want to create an array with values equal to those columns.
data want;
set have;
array Dex[100];
for i = 1 to 100;
[assign values]
end;
run;
Is there a way to do this without knowing those columns' names?
Yes, you could define your array such as:
array vars Dex:;
do i=1 to dim(vars);
[assign values]
end;
run;
Use dictionary.columns to find out the number of columns which has prefix - dex
/Sample dataset/
data have;
dex_random1=1;
dex_1=2;
dex_3=4;
dex_dex_random=2;
run;
proc sql;
select count(*) into: Number_of_vars from dictionary.columns where
upcase(libname)="WORK" and upcase(memname)="HAVE" and upcase(name) like "DEX%";
select name into: All_vars separated by " " from dictionary.columns where
upcase(libname)="WORK" and upcase(memname)="HAVE" and upcase(name) like "DEX%";
quit;
data want(drop=i);
set have;
array dex[&Number_of_vars.] &All_vars. ;
do i=1 to &Number_of_vars.;
dex[i]=1;
end;
run;