Data Analysis

While I was studying abroad at Kyoto University in Japan, I took a project-based data class where the focus was a project of our choosing and using python to analyze data. I chose to analyze various data on Japan to create data visualizations since I believe it is incredibly easier to understand. I selected data sets that are organized by prefectures because I wanted to see how each prefecture differed from each other. I used plotly, numpy, and matplotlib to create the different visualizations. Main goal was to organize the data in different types of ways so I created basic line plots, scatter plots, histograms, and bubble maps. Additionally, I made the data interactive since I believe data is easier to consume if it is interactive so I created widgets to adjust the time period, which prefecture to view, search bar and etc.

Data sets used: -Duration of weather per prefecture

I can probably pinpoint my desire to go down the data analysis path to this class. The professor who assigned this project was brilliant and had such a charismatic enthusiasm for data that I wanted to learn more during my free time. I think interactive data visualization is an ideal way to get people more interested in the information they are consuming. It allows them to observe how datasets interact with each other and actually absorb the information presented to them instead of a pie chart that they probably did not even take the time to read and already has forgotten.