Hi ,
I used proc import and get datasets a and b
PROC IMPORT OUT= WORK.auto&i DATAFILE= "C:\auto\&&price&i.xlsx" |
DBMS=xlsx REPLACE; |
SHEET="auto"; |
GETNAMES=YES; |
RUN; |
and i get two datasets as below and how to delete the columns which are empty like C,D,E,F,G,H from auto1and column D in auto2
Auto1
Zone | pricing | C | D | E | F | G | H |
876231 | 1428 | ||||||
650123 | 1556 | ||||||
754258 | 1235 |
Auto2
Safety | measures | dimension | D |
floor | 1 | 2 | |
lock | 0.95 | 3 | |
alarm | 0.85 | 5 | |
alarm | 0.98 | 7 |
Welcome to the wonderful word of Excel and poor data results.
You could drop the variables for any purpose. Or if you really want a new data set:
data work.want;
set work.auto1 (drop=C D E F G H);
run;
Hi ,
I am running in a loop if i drop C column when i running i a loop i will not have C column in Auto2 also right but i want that column in Auto2
I need to write code n0284330in such a way that it drops the empty columns automatically from each dataset while creating the output
so that the same code used for Auto1 it will drop CD EFGH
and for Auto2 it will drop D
Can anyone pls help
Thanks
If one really wants to automate a process then using Excel as a data source and Proc import to read the data are two suboptimal choices.
Excel in the form of XLSX or XLS files has no actual structure and manipulation of files can creat "phantom" variables and rows of data as you are experiencing.
Proc Import has to guess every single time a file is read as to the types of data and characteristics. Using default settings for proc import and Excel spreadsheets you can get different data types just by changing the sort order of the data before proc import.
If these files are supposed to contain the same data it may be worth the effort to convert the XLSX to CSV and write, or modify the program creatd by proc import for one file, a custom program to read in a consistent manner.
The simplest way is using proc freq+nlevels, if you want more flexibilty ,try SQL. data have; set sashelp.class; call missing(sex,age); if _n_=3 then call missing(weight); run; ods select none; ods output nlevels=temp; proc freq data=have nlevels; tables _all_; run; proc sql; select tablevar into : drop separated by ',' from temp where NNonMissLevels=0; alter table have drop &drop; quit;
If you use a textual file format and a data step for the transfer, the data step specifies the columns. Any Excel-typical "extras" are automatically dropped.
Proc Import is nice for tests, but should never be used in production-stage programs.
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