CDC Natural Science Track

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  Most damaging classes of fire

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  Most common classes of fire

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  Locations of Class G fires

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  Top 10 states by Class G Fires

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  Most common causes for Class G Fires

Inspiration

Based on the theme of nostalgia, we were inspired to specialize our problem statement on focusing where fires would cause the most household damage in the US.

What it does

We analyzed the data given to determine the main causes and locations of the most severe fires.

How we built it

Using Python and the Pandas, Numpy, and Matplotlib libraries, we parsed, cleaned, and summarized data into key insights on wildfires.

Challenges we ran into

Cultivating a problem statement relating to nostalgia that the data could support.

Accomplishments that we're proud of

We know have a deep understanding of the dataset we worked with through the formation of numerous thought-provoking questions.

What we learned

Better understanding of Python libraries listed above and working with large datasets.

What's next for CDC Natural Science Track

Using the insights gathered from the dataset, efforts can be specifically focused on certain regions in the US to maximize efficiency in protecting households from wildfires.

Built With

• python