Using the Openpyxl Python Library

In the Dorky World of Data (especially the data analytics sector), Excel is the king. No matter how much you love SQL or Python, Excel will always reign.

It’s never going away.

So sorry to those who hate it.

Honestly, I’m not the biggest fan. I won’t lie. I’d rather use Python. But since Excel’s here to stay, I’m about to double down on it.

I’m fortune teller Mike now, so let me tell you about what I see in the future…

I believe the best data analysts, engineers, and scientists will be the ones who can integrate multiple technologies together. I’m talking about using Excel with SQL, Python with SQL, or, as you can guess…

Python with Excel.

Now that last one sounds like the money-maker.

Most data professionals will never be able to use Python and Excel in sync. But that’s a major mistake because it offers incredible opportunities to work faster and automate tasks.

Anyway, this prediction is making me learn how to use the openpyxl library.

Now I’m not rushing into things like a boy dating a new girl would do. I’m taking my sweet time to master the basics and become an expert with this integration.

Here’s an example of the first script I wrote using the library…

It’s nothing fancy like I said.

All I’m doing is creating a new workbook, adding some rows, and making the header row have a bold font.

That’s it.

This simple code does this. So just imagine what a creative mind with a fearless attitude toward programming can do.

Once I learn more about the library and apply it to the real world, I’m gonna become a dangerous monster.

So watch out…

I’m taking over the Dorky World of Data.