You might want to look at these kinds of error band line plots in seaborn:

[![enter image description here][1]][1]

https://seaborn.pydata.org/examples/errorband_lineplots.html


  [1]: https://i.sstatic.net/1UmA2.png

You could compute this for each colour/ day of the week. The central line would be a mean value of each colour/day, the shadow being the distribution.

Then it's probably best to look at days individually to compare the distributions of functions. A box-whisker plot might be good to compare distributions, although this is typically only for 1-D data.