US Weather Events Analysis

Inspiration

I was inspired to perform this analysis in order to utilize the data science skills that I've learned. The weather data presented an interesting set of features and information to work on.

What it does

The analysis identifies similar states based on weather events information using a clustering analysis.

How we built it

The analysis was put together using Python's data analysis and visualization libraries (Python, Matplotlib, Seaborn, Scikit-learn).

Challenges I ran into

The biggest challenge I ran into was determining how to transform the categorical data into numerical data that could be utilized in the clustering analysis.

Accomplishments that I'm proud of

I learned how to create several complex visualizations to understand and interpret the data via Matplotlib and Seaborn.

What I learned

I learned to implement one-hot encoding using Pandas and learned to create visualizations that can showcase the results of the clustering analysis.

What's next for US Weather Events Data Analysis

In the future, I would add a supervised learning model that can predict the type or severity of the weather based on unseen data.

Built With

• matplotlib
• pandas
• python
• scikit-learn
• seaborn