I have the following data but not sure about the best way to visualize it.
Average assignment scores for the users starting to participate in the first, second, third, and so on, days of the course.
Assign1 | Assign2 | Assign3 | Assign4 | Assign5 | Assign6 day-1-participants 15 | 20 | 8 | 12 | 15 | 22 day-2-participants 13 | 17 | 9 | 14 | 15 | 21 . . day 90-participants 5 | 7 | 12 | 0 | 0 | 0
And similarly I have the percentage of users from each day who completed the assignment:
Assign1 | Assign2 | Assign3 | Assign4 | Assign5 | Assign6 day-1-participants 90 | 88 | 84 | 75 | 69 | 63 day-2-participants 88 | 87 | 83 | 74 | 67 | 60 . . day 90-participants 10 | 7 | 5 | 0 | 0 | 0
I wonder what would be an effective way of visualizing this data to show that late comers generally performs worse in the assignments. To the degree they are late, their performance gets worse (especially toward the latest assignments) and their participation rate decreases significantly.
I wonder if you guys have any suggestions? I can use the table as I posted here, but normally have around 200 days, and reading such a large table and making inferences would be very hard. I am comfortable using any visualization tool (but mostly a python library).