I don't think you should learn Python 😭

Now don't get me wrong. I love Python. It's my favorite data tool. And it's absolutely incredible.

But here’s why you shouldn’t learn it 👇

It just takes a long time to get good at it.

Things like Power BI or Tableau are just much easier to get good at, much quicker.

Personally, I think you can get to proficiency in one of these BI tools in about a month. But I think it would take around 6 months to feel the same level of comfort in Python.

Simply stated: it’s 6x harder to start in Python than something like Tableau

Why is Python so hard to learn?

• It’s hard to install

• It’s programming & programming is hard

• You can do infinite things in Python

📊 Is Python in demand?

And even if you’re thinking, “Avery, I’ve got this. Trust me. I can learn Python.”

I would reply, “Well do you realize that 2 out of 3 data analyst jobs don’t even mention Python anywhere in the JD?”

In fact, for entry-level positions, that number is probably closer to 4 out of 5.

For the data on this, watch today's YouTube video.

🐍 Still going to learn Python?

If you want to delay your job search by 6-8 months, just so you can apply to an extra 1 out of 5 jobs….then go ahead. But that’s not what I would do. And it’s not what I suggest to all my Data Analytics Accelerator students.

If that’s the choice you make, here’s what you should know & in what order:

✅ Variables

✅ Print statements

✅ Mathematical Operations

✅ Functions

✅ Loops

✅ IDE's

✅ Libraries (the big ones in data to know are Pandas, MatPlotLib, Seaborn, Plotly, and NumPy)

✅ Read in data w/ Pandas

✅ Descriptive analytics w/ Pandas

✅ Filtering w/ Pandas

✅ Data visualization (I like seaborn the most for getting started)

I explain this whole concept in a lot more detail in today’s YouTube video.

<< Watch it here >>

Of if you’d rather listen, here’s the podcast link.

Upskill Smarter, Not Harder,

Avery