SAS/Data Management

< SAS

Library

Data are stored in a directory. You can give a name to that directory using the 'libname' statement.

```LIBNAME name_of_the_libraray "W:/Desktop" ;
```

• Proc dataset
• Proc content
• Proc print

The Proc datasets allow to list the content of all the datasets in a library

```libname lib "W:\…\data" ;
proc datasets library = lib;
contents data=_all_;
run;
```

Generate Random Variables

The following program draws 5 observations from a normal distribution with expectancy 1.75 and standard deviation 0.1. The rannor() function draws from a standard normal distribution. The argument specifies the seed. This allows reproducibility.

```data taille ;
do i = 1 to 5 ;
x = 1.75 + 0.1 * rannor(1) ;
output ; end ; run;
```

If you know the quantile function (inverse CDF), you can draw in the distribution using the inverse CDF method. You simple have to draw in a uniform distribution and transform the draw using the inverse CDF function. Here is an example with a Gumbel distribution :

```gumbel = - log(-log(ranuni(0))) ;
```

Input Data

```data base ;
input x u ;
cards ;
1 -1
2 1
3 -1
4 1
5 -1 ;
run ;

proc print data = base ; run ;
```

Sorting

``` proc sort data=lib.data out=lib.data2 tagsort;
by x1 x2;
run;
```

The default is ascending sort. If you want to put the highest values first, you can use by descending.

``` proc sort data=lib.data out=lib.data2 tagsort;
by x1 descending x2;
run;
```

Merge

It is better to sort the data before merging them.

``` data lib_name.data_name3;
merge lib_name.data_name3 (in=a) lib_name.data_name2 (in=b);
by x1;
if a and b;
run;
```

```DATA a; INPUT famid name \$ inc98;
DATALINES;
2 Art  22000
1 Bill 30000
3 Paul 25000;RUN;
DATA b;
INPUT famid inc96 inc97 inc99;
DATALINES;
3 75000 76000 77000
1 40000 40500 41000
2 45000 45400 45800
4 200 300 100
;RUN;
PROC SORT DATA=a; BY famid;
RUN;
PROC SORT DATA=b; BY famid; RUN;
DATA merge121;
MERGE a(in = a) b(in = b) ;
BY famid;
froma = a;
fromb = b;
RUN;
```

Import from other format

You can import from a CSV:

```proc import datafile="E:/Data/recidiv.csv"
out=lib.recidiv replace;
run;
```

You can also specify the delimiter.

```proc import datafile='W:/…/australia2.csv' out=work.australia replace;
delimiter = ";";
run;
```

You can import from an xls file.

```proc import datafile="C:/Documents and Settings/.../Bureau/base.xls"
out=work.base replace;
sheet = "Table 1" ;
run;
```

Export to other format

First one can export to Excel :

```PROC EXPORT DATA= lib.database OUTFILE= "W:/Desktop/export.xls"
DBMS=EXCEL2000 REPLACE;
RUN;
```

Creating aggregate tables

One can create aggregate table using the output delivery system (ODS). The following program creates a table of the cross tabulation and store it in a new dataset.

```ods trace on  ;
ods output CrossTabFreqs = lib.aggregate ;
ods listing close ;
proc freq data = lib.ficus (where = (effec < 100));
table effec * eff_moy ;
run ;
ods output clear  ;
ods output close ;
ods trace off ;
ods listing ;
```