Vizualizing 5000 IMDb Movies

Getting started Movie Madness Face the Films Actors and Directors About Bonus!

Actors' Total Grossings
You can see more or less of the total bar chart on the left by either dragging the box in the mini chart on the right or by scrolling your mouse. You can also click anywhere in the mini chart to center the box on that region. And you can increase and decrease the size of the box by dragging the top or bottom handle up or down.

What is this?

In this final visualization, we explore actors and directors and how much their movies earn. We start out by looking at actors and total earnings they have grossed summed from all their movies. If you would like you can instead look at the average earnings of each actor by clicking in the bottom right on “Sort by Average.” Both total earnings and average earnings are also available for movie directors by clicking in the bottom right “Sort by Director.” The color still represents gross earnings with the darker the shade of the green meaning higher earnings. You can scroll up and down and zoom in on a certain group of individuals using the filter on the right side. By hovering over the bars, you can see specific details about each actor or director. By clicking on any of the bars the entire bar chart will transfigure into a tree-map in which the corresponding actors’ or directors’ earnings will be broken down by each movie in which they have been involved. The size of the boxes in the tree-map, along with the coloring, correspond with earnings, so the larger the box the higher the earnings were for that movie.

While this visualization is more exploratory we can find some very interesting things. First, we can see that out of the top 20 actors shown only 2 of them are females, and no females in the top 20 directors. By clicking on some of the more popular actors or directors we can also see the huge disparity in earnings between his or her earlier films and her later ones. What is most surprising is how much changes when we switch to averages. Most of the names at the top now are people that I do not recognize at all. Explore and find out more for yourself!



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About the Author

Profile

John LaGue is a Senior data science student at the Univeristy of San Francisco. His focus is computaional analytics and has recently been focused on using Tensorflow to explore neural networks. He also enjoys reading and working as a rock climbing instructor. To see a larger collection of of John's academic and personal projects go here: GitHub or LinkedIn





University of San Francisco: CS 360, 2017