Macros - the key to efficient data processing

My first introduction to Macro was in Microsoft Excel with VBA Macros. I haven’t used it extensively, but my last job required me to work with macros on few occasions.

MSBA
DataScience
Data Analytics
SAS
Coding
Macros
Author

Mohit Shrestha

Published

June 17, 2019

Image source: https://www.lynda.com/Excel-tutorials/Excel-2010-Macros/74463-2.html

Image source: https://www.lynda.com/Excel-tutorials/Excel-2010-Macros/74463-2.html

My first introduction to Macro was in Microsoft Excel with VBA Macros. I haven’t used it extensively, but my last job required me to work with macros on few occasions. But, to be honest, I didn’t really liked working with macros then as most of the macros I worked with were created by someone else, without any instructions and proper descriptions of what the macros supposed to do. So, if you are not the one who wrote the macro, it is a bit more difficult to understand it. Unlike formulas, where it is very easy to backtrack the output; in macros, the output is a hard-coded number, so one has to look at the codes in detail to understand how the output was calculated. Therefore, I preferred working with formulas more than macros, however, I understand that working with huge datasets it is very efficient to create macros to automate tasks as it also reduces the possibility of human error that increases with many, repetitive keystrokes and tasks.

Last week we learnt about using SQL (PROC SQL statements) in SAS language. It helped us to merge different sources of data, and process and analyze huge datasets. This week, we took a step further and learnt how to write Macros to i) automate processing huge chunks of the same code to analyze different components in the dataset, and ii) minimize the number of lines of codes for the data analysis. Macros are especially useful for automating and doing repeatable discrete tasks, where the analysis is an iterative process, and to pass data from step to step.

Here are the key steps of writing any macro:

  1. Is it worth writing a macro vs lines of codes/formula?

    • If it is just few line of codes, then we can just repeat the codes, its a lesser hassle than creating macros.

    • But if the lines of code is 10 or more, and we have to repeat the same code multiple times for analyzing different variables, then it is worth writing a macro.

    • If we think we would use the code frequently in future, then it is worth writing a macro and saving for future use.

  2. Once you decide to write a macro, start with writing the core part of the program. If it helps, break that program into multiple tasks. It is easier to write each block of code based on the order in which a user would perform this task if it were to be done manually.

  3. Take one component/field/variable that you want to analyze and make sure that the core lines of code runs smoothly without any error, and it does what it needs to do.

  4. Once you have verified that the core lines of code are working, then you can create a macro as follows:

    1. To start a macro:

      • %MACRO macro-name <(parameter-list)></ option-1 <…option-n>>;
    2. Paste the clean code

      • Start replacing the hard-coded input parameters that we defined earlier
    3. To end a macro:

      • %MEND
  5. When we run the chunk of code, it doesn’t return any output. We have to call the macro that we created with the defined input parameters.

    Here is an example:

PROC FREQ DATA=NC_OPIOID_ANALYSIS nlevels; 
TABLE Gender / out=freq_out; 
RUN;

Now writing macros for the above code, but making it dynamic to be used for analyzing other variables as well:

%MACRO charProfile(inDat=, charField=); 
PROC FREQ DATA=&inDat nlevels; 
TABLE &charField / out=freq_out; 
RUN; 
%MEND;

Now we call macro to analyze lets say field Medical School Name instead of Gender from NC_OPIOID_ANALYSIS table.

%charProfile(inDat= NC_OPIOID_ANALYSIS, charField=Medical_school_name);

In this example, at first I wrote lines of core code to analyze Gender field only, but later when i created Macro named charProfile, I was able to reuse the same chunk of code to analyze 20 different character variables of that table, not just Gender. It was amazing to see how I was able to analyze all interested character variables from that datasets in such an efficient way using Macros.

Previously at work, I had to struggle understanding macros created by others without proper descriptions and instructions. So, my experience with macros were not pleasant; however from this weeks project, I got to learn about the key steps for writing a macro. I got to practice writing macros from the beginning and analyze the real world data set. Thus, it was much easier to follow and understand. I’ll definitely give writing Macros another chance, and given that I enjoyed this weeks assignment using macros, I think I use Macros more often to perform iterative tasks and analyze big data sets.

Cheers! to overcoming the fear of using Macros.

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Citation

BibTeX citation:
@misc{shrestha2019,
  author = {Mohit Shrestha},
  title = {Macros - the Key to Efficient Data Processing},
  date = {2019-06-17},
  url = {https://www.mohitshrestha.com.np/posts/2019-06-17-macros-the-key-to-efficient-data-processing},
  langid = {en}
}
For attribution, please cite this work as:
Mohit Shrestha. 2019. “Macros - the Key to Efficient Data Processing.” June 17, 2019. https://www.mohitshrestha.com.np/posts/2019-06-17-macros-the-key-to-efficient-data-processing.

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