Hi @jesmaxavier ,
Despite the fact that I have not attempted this project myself, I couldn’t help but get drawn into the compelling storytelling you have used in the course of this analysis. I had to get myself a drink, then sit through and read the project in entirety. Nicely crafted puns and phrases too
:
Not so Long ago, In a Dataset
Clean the Data We Must…
Fan Force
Wait… I have seen that!
Quite the Character
Hans? Greedo? Who Knows?
May the force be with you (An appropriate way to conclude things).
YOUR CODE
Your code is understandable and easy to follow. Even without reading the comments, I found it so easy to understand what you were executing at each point. This is amazing! 
SOME VISUALS CAUGHT MY EYE
I loved all your visualisations, especially the horizontal bar charts, good data ink ratio, and the central message in them stood out (Gestalt genius!!)

IF I MAY ASK
In the visualisation for fans demographic data. I was immediately drawn to the green color signifying prevalent groups (Males, Gen X, Lower middle and Bachelors), did you do this intentionally or was it a coincidence. If it was intentional, it worked, and you are more than a Gestalt genius, my friend!! 
SUGGESTIONS
I slightly got distracted by some libraries that were being imported later along the code. I’d suggest importing all your libraries in one code cell, that way readers like me can know all the libraries you are employing at a glance.
I was once advised here that it could be beneficial to have a summary of your findings up at the top. However, your storytelling was so smooth that I believe anyone would have read the entire work either ways.
You initially mentioned
‘I think I did a good job’
You have never been more wrong. You did an amaaaaazing Job with great touch of originality!!! Definitely belongs in the community champion class! @Elena_Kosourova 