In light of current events, we decided that what better way is there to cheer up others than showcasing our data analysis and visualization of the World Happiness Index.

What it does

Pursuit of Happiness is a thorough data analysis and visualization of the World Happiness Index dataset, which contains statistics regarding an overall "happiness" score of citizens, as well as factors that affect it, such as GDP, perceptions of corruption, and freedom to make life choices. On the web app to display our findings, there are interactive 2D and 3D plots that show different correlations found in the data.

How We built it

In order to analyze the dataset, we used a jupyter notebook along with various python libraries to dive deeper into the data and find interesting correlations. After finding correlations, we used Plotly and Tableau to generate plots of the various findings. As well, we used SciKit-Learn to generate linear and non-linear regression lines to show trends and predictions in the data.

Challenges we ran into

One challenge we ran into was embedding the plots generated by plotly and tableau into our react web app. Since React has almost no support for embedding html files, we had to tediously convert the files into react components in order to get them to show.

Accomplishments that we're proud of

We are proud that we were able to coordinate and create the web app within the given time frame. Due to the difference in timezones, we were not able to work on our project at the same time. However, in the end we figured out how to coordinate and develop our project together through the use of planning tools.

What We learned

We were able to expand our knowledge of data science over the course of this hackathon. We all learned a bit more on how to effectively analyze large datasets, and visualize them using various tools.

What's next for Data Day Grind 2020

We hope to expand on our project in the future, and use multiple datasets in tandem with the WHI dataset to perform even more detailed analysis and visualizations.


Share this project: