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Trym Sorum's avatar

Good stuff, Martin! Will absolutely give Polars a try. The logic reminds me a bit about SQL language actually. Looks perfect if you know what you want to analyze from the get go. Would love to see more advanced examples with Polars - for example building a player ranking or percentiles calculations that makes up a radar chart 💯 Maybe something we could look into together?

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MartinOnData's avatar

Thank you, Trym.

Yes it definitely does. The verbs are so expressive. I find more resemblance with R’s tidyverse but I guess everyone has his own thing 😀

Great idea! Let’s think of something!

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Dewi's avatar

Yep I'm with Martin on that comment about Polar looking nicer! I'm on a learning journey now of working through Data camp exercises and it's all about pandas... I think this post length is just right too. Combining two of my favourite things, data and Arsenal! Do you know if there are equivalent datasets for Arsenal Women?

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MartinOnData's avatar

Thank you for the feedback, Dewi. Polars is the future :)

As for the Arsenal women datasets, you can check out Statsbomb's free datasets: https://github.com/statsbomb/open-data?tab=readme-ov-file

There should be detailed data for the FA Women's Super League for 3 seasons (18/19 - 20/21) and data for the last two Euro and World cups.

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Dewi's avatar

Nice, thank you!

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Martin Wong's avatar

Polars looks way more intuitive. You’ve convinced me to try it out.

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MartinOnData's avatar

It's the chaining and the verbs. Love it :)

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