Plastic Pollution

Global production of plastics is increasing every year. The amount of plastic litter that is finding its way into the environment and the oceans are also increasing, especially in the world where waste management practices are not keeping up with the rapid development.

There is, however, a lack of information on how much plastic debris finds its way to the oceans and how much of it there already is in the oceans. To understand the magnitude of input of plastics to the natural environment and the world’s oceans, we must understand various elements of the plastic production, distribution, and waste management chain. This is crucial, not only in understanding the scale of the problem but in implementing the most effective interventions for reduction.

The data and visualizations which follow in this project provide this overview step-by-step.

The project’s goal is to utilize the tools to understand the human aspects of data science and build data-driven interactive systems. The broad aim is to tell a story with the data and explore opportunities enabled by interactive data analysis.

Unlike previous “byte” projects, this final project was done simply the process of data visualization by using creation tools like Tableau. However, early data analysis (EDA), resolving common problems with data such as incomplete datasets, outliers, structural issues, were cleaned using pandas on Jupyter notebook.

Language(s): Python – Pandas
Tool(s): Tableau
Duration: 1 week

Web App | Exploratory Data Analysis | Video

05839: Interactive Data Science
HCI Department
Carnegie Mellon University – Pittsburgh
Fall 2021