Summary
ADD FILES is an SPSS command that’s mainly used for merging data sources holding similar variables but different cases. (For the same cases but different variables, see MATCH FILES.) A second use is for reordering and/or dropping variables in a single dataset.
SPSS Add Files Matches Data Sources on Variable Names
SPSS Add Files – Basic Usage
The ADD FILES command illustrated in the screenshot above results from running the syntax below.
SPSS Add Files Syntax Example
*1. Create dataset d1.
data list free/v1 v2 v3.
begin data
1 1 1
end data.dataset name d1.
data list free/v1 v2 v3.
begin data
1 1 1
end data.dataset name d1.
*2. Create dataset d2.
data list free / v2 v1 v4.
begin data
2 2 2
end data.
dataset name d2.
*3. Merge d1 and d2.
add files file d1 / file d2.
exe.
dataset name merged.
SPSS Add Files Rules
- Up to 50 datasets or data files can be merged with a single
ADD FILEScommand. ADD FILEScan also be used for reordering and/or dropping variables in a single dataset. This is done by using theKEEPorDROPsubcommand. How it works is explained inMATCH FILES.
SPSS Add Files Pitfalls
-
- If a variable has inconsistent dictionary information across data sources, you may end up with nonsensical data. This is explained in SPSS Recode – Cautionary Note. For a tool that detects dictionary inconsistencies over files, see Compare Dictionaries over Files Before Merging.
- If there are string variables present, they should have the same lengths across all data sources. Adjust String Lengths before Merging Files shows how to do this automatically using Python.
- Especially with many data files, you may want to add the file names as a new variable to the files. Like so, you can easily see the source of each case in the merged data. See Add Filenames to Files Before Merging.
- An alternative for adding the data sources to the merged result is using the
INsubcommand as inadd files file d1 /in = d1 / file d2 /in = d2. - If you want to merge a lot of files, you can have Python do it for you. This is demonstrated in Merge Many Data Files.
