(First self-project) Best method to visualize skill trend?


I love to play video games and one of my favorite competitive online game is Rocket League. Figured it would be fun to track about 500+ games (unfortunately they aren’t consecutive but for the most part pretty close!) and use my current skills to track my progress via python.

The dataset contains the following columns:
Games: number of games played
Match Result: numeric value of match result, win (1), lose(0)
Goals: goals scored per game
Assists: assists per game
Saves: saves per game
Shots: shots taken per game
Points: total points per game
Result_W/L: non-numeric value of match result (based on Match Result column)
Interval_Games: each 100 games grouped

Screenshot of the dataframe below

I’m considering replicated a Grid Chart based off this DQ example (Learn data science with Python and R projects) where each subplot would be line graph of Interval_Games, and the x-axis is Games and y-axis is Points. However, I am stuck on how to exactly create that in terms of code. Any suggestions or feedback would be greatly appreciated! Let me know if additional information is required.

Hi @jeprim

Maybe this can help you. seaborn.FacetGrid — seaborn 0.11.2 documentation.

In your case, you can pass Interval_Games as a value for the col parameter in the below code:

# you may not need the row parameter unless you want to introduce another variable!
g  =  sns.FacetGrid(your_df , col = "Interval_Games").  

And then plot a line/scatter whichever works best for your data.


Hi @Rucha,

Thank you so much for the suggestion! The documentation link was simple to follow and implement within my project.

Here is a screenshot of the current results -

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