I need to find a ratio of two mean values, that I have found using proc means.
proc means data=a;
class X Y;
var x1 x2;
run;
Then I get the output mean values for variables x1 and x2 in the two categories of X and Y, but it is x1/x2 for each category that I am interested in, and doing it by hand is not really a solution.
I am not a professional programmer, so I hope there is a simple piece of code that I can understand and use.
You need to precompute x1/x2 or postcompute x1/x2 (Depending on whether you want mean(x1/x2) or mean(x1)/mean(x2), which can have different answers of x1 and x2 have different numbers of responses).
So either (... means fill in what you have already)
data premean;
set have;
x1x2 = x1/x2;
run;
proc means ... ;
class ... ;
var x1x2;
run;
or
proc means ...;
class ... ;
var x1 x2;
output out=postmeans mean=;
run;
data want;
set postmeans;
x1x2=x1/x2;
run;
proc sql noprint;
create table xy_ratio as /* New table name*/
select distinct X, Y, avg(x1)/avg(x2) as x1_x2_ratio /* selects distinct rows containing variables listed here. (Must include group by variables) mean of x1 / mean of x2 to form ratio*/
from a /*source dataset*/
group by X, Y /*Similar to class statement, will provide an average for each distinct combination of X and Y that appear in the dataset*/
;
quit;
Related
I have two groups, A and B, and two numeric variables, X and Y. I want to create two new variables, new1 and new2, based on the values of X and Y (respectively) for group B (i.e., IF group = B THEN new1 = X, new2 = Y). I want to take those newly created variables, append them to group A, and then delete group B. In the end, there should be one row for group A containing X, Y, new1, and new2. I'm uncertain how to accomplish this.
I've looked into using PROC TRANSPOSE, but I'm unsure if that's the right starting point. My internet searches are lacking because I'm not even sure what to call what I'm attempting to do, though I'm betting this is a common procedure requiring a common solution.
EXAMPLE
Not sure how to generalize the problem, but for the given problem this will work:
/* Just reversing the records */
proc sort data = have;
by descending group;
run;
data want;
set have;
retain new1 new2;
if _N_ = 1 then do;
new1 = x;
new2 = y;
end;
else output;
run;
This sounds like a case of 1 to 1 merging (merge with out BY).
data have; input
group $1. x y; datalines;
A 3 4
B 2 6
run;
data want;
merge
have(where=( group='A'))
have(where=(Bgroup='B') rename=(x=Bx y=By group=Bgroup))
;
drop Bgroup;
run;
Im a new SAS User and I have a small problem
I have one large empty table A with lets say 100 columns that I have created with a simple proc sql; create table
I have another table B with lets say 40 columns and table C with 55 columns.
I want to add these two tables into table A, basically I want a table with 100 columns containing the data from table B & C and I'm doing this with a Union command.
Since I dont have values for all 100 variables I have to set default values.
Lets say I have a column named nourishment in table A, food in table B and has no equivalent in table C. I have rules like "If the data comes from table B then value =xxx if its from table C then Value="DefaultValue"
I'd do this easily with R or python but Im struggling with sas.
I'm using SAS sql commands (a Union command)
How do you set default values ? (for all data types : character, numeric or dateI'm using SAS sql commands )
Dates in SAS are actually just numeric values. Often they have a date format applied to make them readable.
So you could just assign a missing value by default like so:
. as ColumnName
or any default date like so
'17NOV2017'd as ColumnName
. as MyColumnName
SAS can deal with missing values.
Using a specially coded value, such as 'NA', to represent a missing value condition can work but may lead to headaches and extra coding. Recommended read in SAS help: "Working with Missing Values"
The default SAS missing value for numerics (which also includes dates) is period.
. as MyColumnName
SAS also has 27 special missing values for numerics that are expressed as . < character >
.A as MyColumnName
...
.Z as MyColumnName
._ as MyColumnName
The missing value for character variables is a single space
' '
'' empty quote string also works
' ' as does a longer empty string
Rule of thumb: be consistent when coding your missing values.
You can use OPTIONS MISSING to specify what character is shown when a missing value is printed.
OPTIONS MISSING = '*'; * My special representation of missing for this report;
Proc PRINT data=myData;
run;
OPTIONS MISSING = '.'; * Restore to the default;
SAS custom formats can also be used to customize what is printed for missing values.
Proc FORMAT;
value MissingN
. = 'N/A'
.N = 'Special N/A different than regular N/A' /* for .N */
;
value $MissingC
' ' = 'N/A'
;
value SillyChristmasStocking
.C = 'Bad'
.O = 'children'
.A = 'get'
.L = 'No toys'
;
The token after the value keyword can be any new valid SAS name that you want to used for your format name.
Proc PRINT data=myData;
format myColumnName MissingN.;
format name $MissingC.;
format behaviour SillyChristmasStocking.;
run;
As for your character missing value conditions, I would continue to use " " or ' '
You mention UNION which is a SQL feature. In SQL, JOIN also occur, perhaps more often then UNION. When JOINing and values from two source columns collide, you will want to use either COALESCE() function or CASE
statements to select the non-missing value.
I would not recommend using UNION in PROC SQL at any point in your SAS usage. UNION is almost always inferior to a simple data step, or a data step view.
That's because the data step seamlessly handles issues like differing variables on different tables. SAS is quite comfortable with vertically combining datasets; SQL is always a bit trickier when they're not identical.
data c;
set a b;
run;
That runs whether or not a and b are identical, so long as a and b don't have conflicting variable names (that aren't intended to be in the same column); and if they do, just use the rename dataset option to resolve it.
If you do as the above, and don't use union, you'll get a missing value automatically for those dates.
NFN:
DATA Step
A DATA Step approach for stacking data is the simplest. Use SET to stack the data and array processing to apply your defaults. For example:
data stacked_data;
set
TARGET_TEMPLATE (obs = 0)
ONE
TWO
;
array allchar _character_;
array allnum _numeric_;
array dates d1-d5;
do over allchar; if missing(allchar) then allchar = '*UNKNOWN*'; end;
do over allnum; if missing(allnum) then allnum = -995; end;
do over dates; if missing(dates) then dates='01NOV1971'd; end;
run;
A subtle issue is that any missing values in ONE or TWO will be replaced with the default value.
Proc SQL
In Proc SQL you will want to create a single row table containing the default values for A. That table can be joined to the union of B and C. The join select will involve coalesce() in order to choose the predefined default value when a column is not from B or C.
For example, suppose you have an empty (zero rows), richly columned, target table (your A) acting as a template:
data TARGET_TEMPLATE;
length _n_ 8;
length a1-a5 $25 d1-d5 4 x1-x20 y1-y20 z1-z20 p1-p20 q1-q20 r1-r20 8;
call missing (of _all_);
format d1-d5 yymmdd10.;
stop;
run;
Because Proc SQL does not provide syntax for a default constraint you need to create a table of your own defaults. This is probably easiest with DATA Step:
data TARGET_DEFAULTS;
if 0 then set TARGET_TEMPLATE (obs=0); * prep pdv to match TARGET;
array allchar _character_ (1000 * '*UNKNOWN*');
array allnum _numeric_ (1000 * -995);
array d d1-d5 (5 * '01NOV1971'd); * override the allnum array initialization;
output;
stop;
run;
Here is some generated demo data, ONE and TWO, that correspond to your B and C:
data ONE;
if 0 then set TARGET_TEMPLATE (obs=0); * prep pdv of demo data to match TARGET;
do _n_ = 1 to 100;
array a a1 a3 a5;
array num x: y: z:;
array d d1 d2;
do over a; a = catx (' ', 'ONE', _n_, _i_); end;
do over num; num = 1000 + _n_ + _i_; end;
retain foodate '01jan1975'd;
do over d; d=foodate; foodate+1; end;
output;
end;
keep a1 a3 a5 x: y: z: d1 d2; * keep the disparate columns that were populated;
run;
data TWO;
if 0 then set TARGET_TEMPLATE (obs=0); * prep pdv of demo data to match TARGET;
do _n_ = 1 to 200;
array a a1 a2 a3;
array num x5 y5 z5 p: q: r:;
array d d1 d2;
do over a; a = catx (' ', 'TWO', _n_, _i_); end;
do over num; num = 20000 + _n_*10 + _i_; end;
retain foodate '01jan1985'd;
do over d; d=foodate; foodate+1; end;
output;
end;
keep a1 a2 a3 x5 y5 z5 p: q: r:; * keep the disparate columns that were populated;
run;
A stacking of A, B and C is simple SQL but does not introduce target specific default values:
proc sql noprint;
* generic UNION stack with SAS missing values (space and dot) for cells
* where ONE and TWO did not contribute any data;
create table stacked_data as
select * from have_data_TEMPLATE %*** empty template first ensures template column order and formats are honored in output data;
outer union corresponding %*** align by column name, do not remove duplicates;
select * from ONE
outer union corresponding
select * from TWO
;
When the stacking is put in a sub-query, it can be joined with the defaults. The choosing of the target default value for each column involves examining DICTIONARY.COLUMNS and generating the SQL source for selecting the coalescence of stack and default.
proc sql noprint;
* codegen select items ;
select cat('coalesce(STACK.',trim(name),',DEFAULT.',trim(name),') as ',trim(name))
into :coalesces separated by ','
from DICTIONARY.COLUMNS
where libname = 'WORK' and memname = 'HAVE_DATA_TEMPLATE' %* dictionary lib and mem name values are always uppercase;
order by npos
;
create table stacked_data_with_defaults as
select * from TARGET_TEMPLATE %*** output honors template;
outer union corresponding
select
source
, &coalesces %*** apply codegen;
from
(
select * from WORK.have_data_TEMPLATE %*** ensure fully columned sub-select that will align with coalesces;
outer union corresponding
select 'one' as source, * from ONE
outer union corresponding
select 'two' as source, * from TWO
) as STACK
join
TARGET_DEFAULTS as DEFAULT
on 1=1
;
quit;
Why would you create an empty dataset? What is it going to be used for? Perhaps you want to use it as a default structure definition? If so and you want to stack B and C and get them in the structure defined by A you could code this way.
data want ;
set a(obs=0) b c ;
run;
Not sure what the purpose would be to have default values. Couldn't you use formats if you want missing values to display in special ways?
Or you could create code to default values and perhaps just %include it or wrap the logic into a macro. So it you had a code file name 'defaults.sas' with lines like this.
startdate=coalesce(startdate,'01JAN2013'd);
gender=coalescec(gender,'UNKNOWN');
Then your little program to make a new dataset that looks like A and uses the data from B and C would look like this.
data want ;
set a(obs=0) b c ;
%include 'defaults.sas';
run;
If you really did want to aggregate the records into some large dataset then perhaps you want to use PROC APPEND to add the records once they are created in the right structure.
proc append data=want base=a ;
run;
I have a database with serveral variables, including one, RIF, that hase an x^2 shape relative to another variable, Y.
I want to obtain two seperate databases, separated based on whether the observation is on the decreasing or the increasing part of the curve.
I thought I had something by using the lag function, but my code does not work.
proc sort data=have; by y; run;
data want;
set have;
do while (rif<=lag(rif));
Part=1;
end;
if Part ne 1 then Part=2
run;
And the separating given Part, but it seems to create infintite loop.
Is there a mistake in my code / is there a better way of doing this
data have;
do x = -10 to 10 by 1;
y = x**2;
output;
end;
run;
data want;
set have;
lag_y = lag(y);
if _n_ = 1 then Part=.;
else if y <= lag_y then Part=1;
else Part=2;
drop lag_y;
run;
SAS newbie here.
My question is about PROC REG in SAS; let's assume I have already created a model and now I would like to use this model, and known predictor variables to estimate a response value.
Is there a clean and easy way of doing this in SAS? So far I've been manually grabbing the intercept and the coefficients from the output of my model to calculate the response variable but as you can imagine it can get pretty nasty when you have a lot of covariates. Their user's guide is pretty cryptic...
Thanks in advance.
#Reese is correct. Here is some sample code to get you up the learning curve faster:
/*Data to regress*/
data test;
do i=1 to 100;
x1 = rannor(123);
x2 = rannor(123)*2 + 1;
y = 1*x1 + 2*x2 + 4*rannor(123);
output;
end;
run;
/*Data to score*/
data to_score;
_model_ = "Y_on_X";
y = .;
x1 = 1.5;
x2 = -1;
run;
/*Method 1: just put missing values on the input data set and
PROC REG will do it for you*/
data test_2;
set test to_score;
run;
proc reg data=test_2 alpha=.01 outest=est;
Y_on_X: model y = x1 x2;
output out=test2_out(where=(y=.)) p=predicted ucl=UCL_Pred lcl=LCL_Pred;
run;
quit;
proc print data=test2_out;
run;
/*Method 2: Use the coefficients and the to_score data with
PROC SCORE*/
proc score data=to_score score=est out=scored type=parms;
var x1 x2;
run;
proc print data=scored;
var Y_on_X X1 X2;
run;
2 ways:
Append the data you want into the data set you're going to use to get estimates but leave the y value blank. Grab the estimates using the output statement from proc reg.
Use Proc Score
http://support.sas.com/documentation/cdl/en/statug/63347/HTML/default/viewer.htm#statug_score_sect018.htm
I have been trying to make a Vector plot in SAS using the SAShelp library 'Class'. The goal is to make a vector plot with the origins of the vectors in the respective means of the x and y variables. I used the following code:
DATA class2;
SET Sashelp.class;
x = mean(height);
y=mean(weight);
run;
PROC SGPLOT DATA = class2;
VECTOR X = height Y = weight / XORIGIN = x YORIGIN = y;
run;
I thus first created two new variables, containing the means of the X and Y variable. Then I wanted to place the origin of the vectors in these origins, but when I do this, the vectors disappear in my plot and all I get is a plot with some dots.
Any suggestions on how to solve this, and especially, how this disappearance of the vectors has been caused?
Thank you in advance,
Koen
The mean() function does not work across the entire data set. Data Steps deal with a single record at a time (think of it as SAS writing an outer loop for processing for you.
You can use SQL to get the means and then add them to the data set. I also added data labels for you.
proc sql noprint;
select mean(height), mean(weight)
into :mh, :mw
from class2;
quit;
DATA class2;
SET Sashelp.class;
x = &mh;
y= &mw;
run;
PROC SGPLOT DATA = class2;
VECTOR X = height Y = weight / XORIGIN = x YORIGIN = y datalabel=name;
run;
Produces this: