Inspiration

We were interested in this particular dataset because of the on going climate crisis. We wanted to see how various industries impact the climate with large amounts of emissions. In general, we were inspired to build a model that would indicate which sectors need to focus on cutting emissions in order to help stop climate change.

What it does

Our visualizations illustrate how emissions have varied over time within all types of industry sectors. We also look at how each sector has increased or decreased their emissions relative to one another.

How we built it

We used Python Pandas, Excel, R, and Tableau to build our project. From data wrangling, cleaning, to visualizations, these all helped to create the project!

Challenges we ran into

One of our primary challenges was the fact that while working with one of our CSV files in Pandas, the emissions numbers were actual strings so we had to convert them to floats to be able to do any calculations with them.

Accomplishments that we're proud of

We are proud of the work we did to take our data from a large, conglomeration of numbers and turn it into something meaningful and accessible.

What we learned

Our team comes from differing backgrounds regarding data science. Thus, we were all able to teach each other something new when it comes to working with data. We particularly got to use R and Python frequently, which allowed some of our groups members who weren't familiar with one or the other, to become more familiar with it.

We also learned a lot about what sectors of industry are largely contributing to Green House Gas (GHG) emissions. Many of these were surprising to us, as they are not industries that would initially come to mind when thinking about large amounts of emissions.

What's next for CDC Project 2022

We want to continue to work with data in order to provide meaningful, accessible visualizations and come to important conclusions. Climate change is a problem which must be taken care of and we hope to contribute to this by utilizing data in meaningful ways.

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