Sankey visualizations generated based on connections between artists' nationality, decade when they were born, and their gender.

This project leverages survey data from the artists represented at the Museum of Contemporary Art (MCA) Chicago. The dataset is a JSON file containing over 10,000 artists whose works are displayed at the museum.

Overall, as threshold amount being 20 and 44 and groupby index of ‘counts’, ‘American’ and ‘male’ have two largest proportions in this analysis. Firstly, in Sankey diagram of Nationality and Gender, it is remarkable of how American male artists had contributed. The weighting value of American male artist is as heavy as 3540 whereas American female artist is only 1000. But American female artist still outweighs female of German, French, British and Japanese. Surprisingly yet unfortunately, as counting threshold being 44, only these five countries’ female data are eligible to this criterion, meaning only five countries have five or more female artists in this dataset. In addition, more countries have 44 or more male artists based on this diagram across the world.

However, limitations in this dataset are also critical to be notified. It possibly collects artists’ information from U.S. initially and loses sights of some other countries with less contacts. Besides, artists who were born in centuries of war may also had less chances to be recorded in history. I am curious to learn further about how better we can do to maintain such data and information and deliver it to next generations. I will explore accordingly. :)