Thread by @f1dataanalytics

Tomorrow the first #F1 race weekend of 2023 starts!

You'll probably see a lot of data 📈 flying around your timeline.

Why not analyze the data yourself?! Let me show you how with #Python 👀

Start with firing up a Jupyter notebook and installing Fastf1:

Now that Fastf1 is installed, we need to load the package.

This is how you do it:

Cool, that was easy!

Now we need to configure the cache ⚙️

In the same folder as your Jupyter notebook, create another folder called "cache" 📁

We now can select that folder with the following code:

Perfect, all the 'boring' stuff is over! Let's get some actual data.

We start with specifying our session. Make sure to change the year to 2023 tomorrow 😉

The "SESSION" can either be 'FP1', 'FP2', 'FP3', 'Q', 'SQ', and 'R'.

Last step is loading the actual data, which is very straightforward:

Perfect, now we have data!

You can for example see all the laps of the session by accessing the "laps" attribute of the session variable.

Here's a few tricks you can use to easily access data and get...

👉 Fastest laps
👉 Driver laps
👉 Telemetry data

If you want to go more in-depth with this data (like making visualisations), check out my Medium.

There's plenty of tutorials there with many different use cases, all based on the #Formula1 data you just extracted!
medium.com/towards-formul…

Also, if you want to see a live demo of how this works:

I hosted a ~1h webinar doing exactly all this, which you can access via this link:

buymeacoffee.com/f1analysis/e/9…