Author(s): Richard Warepam

Originally published on Towards AI.

In Part 2: It is about handling missing values and data transformation

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This is the second article of the series “How to Automate Data Science Tasks Using Python.” If you haven’t read the first part, start with this article.

In Part 1: It is about loading and understanding the data.

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What did we learn from the first article? — Tell me in the comments below. I want to know: “How different are the takeaways of each reader from the article.”

I’ll tell you what I intended to educate you there:

If any task seems repeated and redundant in your project. Always define a function and automate your work.

We are all aware that some of the tasks on our data science worklist are redundant and can be automated.

The only reason we want to automate these tasks is to save time by not having to write the same code every time.

But how can we automate? Using AI tools? No! -We will automate the tasks by defining a function and calling it as needed.

Some of the tasks we can automate include:

Data loading and understanding the dataHandling missing values and… Read the full blog for free on Medium.

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Published via Towards AI