Streamlining Repetitive Tasks During Exploratory Data Analysis | by Christabelle Pabalan | Oct, 2023

Automation in Data Science

An invitation to identify your repetitive EDA tasks and create an automated workflow, illustrated through an example utility.

Christabelle Pabalan
Towards Data Science
Image by Author (DALL-E Generated)

Programming Principle: Automate the Mundane

They often say lazy programmers make the best programmers. However, it’s more accurate to say that programmers who don’t have the patience for repetitive workflows will take the upfront investment of time to automate whatever they can so they can avoid such tasks. In short, the best programmers don’t patiently repeat mundane tasks — they automate them. Skilled programmers are “lazy” because they invest time upfront to create tools that will save them effort down the road. This may mean learning keyboard shortcuts, creating custom modules, or finding smart software to automate workflows.

In a post titled, “Why Good Programmers are Lazy and Dumb,” Philipp Lenssen states:

“Only a lazy programmer will avoid writing monotonous, repetitive code — thus avoiding redundancy, the enemy of software maintenance and flexible refactoring […] for a lazy programmer to be a good programmer, he (or she) also must be incredibly unlazy when it comes to learning how to stay lazy — that is, which software tools make his work easier, which approaches avoid redundancy, and how he can make his work be maintained and refactored easily.”

Nobody enjoys tedious and monotonous tasks and if anyone should find themselves repeating the same functions across projects, this overarching frustration should start to creep in to haunt them and whisper, “package them into a module.”

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The Repetitive Nature of EDA

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This post originally appeared on TechToday.

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