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First, thanks for this library which is really awesome!
I have this dataset where I'm analyzing Premie league football since 1992. I want to plot a Ridge plot with each subplot being Yellow_card, red_card, goal, penalty, etc, and see the distribution over a 90mn period to see when these actions happen the most. Of course, there is way more yellow cards than goals and way more goals that red card which results in a plot like this:
Is there a way to see everything, I check the parameters and the code but I'm not that good in python to understand everything yet...
Any help?
The text was updated successfully, but these errors were encountered:
This looks like a nice feature to implement. I will have a look at this in the coming days. In the meantime, you could achieve this by normalising each trace yourself. Let me get back to you on this 🚀
Hey! I just logged back on Github but went with the Plotly solution as I found it works pretty well. But yeah, now that you talk about normalization, it totally makes sense and I'm sure it would work!
Hi!
First, thanks for this library which is really awesome!
I have this dataset where I'm analyzing Premie league football since 1992. I want to plot a Ridge plot with each subplot being Yellow_card, red_card, goal, penalty, etc, and see the distribution over a 90mn period to see when these actions happen the most. Of course, there is way more yellow cards than goals and way more goals that red card which results in a plot like this:
Is there a way to see everything, I check the parameters and the code but I'm not that good in python to understand everything yet...
Any help?
The text was updated successfully, but these errors were encountered: