Inspiration
When looking at our data set, we were curious to find trends regarding flight emissions, and specifically how they vary between different nations. Are the more powerful, bigger countries correlated with higher emissions, and does the type of flight affect that?
How we Built it
Through Jupyter we were able to organize data, decide which variable we would be actually considering, and use visualization tools to create a stacked bar graph that allowed us to compare the emission totals of the countries with the largest totals. In Tableau, we created an interactive dashboard with a map of all the countries. When you click on a country, you get more in depth graphs about their CO2 emissions.
Challenges we ran into
Some challenges we experienced was as complete beginners, finding an initial direction of how to approach the data set and deciding what we were trying to learn from it. Additionally, we ran into some problems with creating our bar graph due to our knowledge limitations with python, but were able to google and ask mentors to help us through this.
Accomplishments that we're proud of
We were able to sort the data and separate the actual emissions by their flight types (freight and passenger) and also compare those emissions against the other countries with large emmisions
What we learned
We learned how to create a stacked bar graph through pandas, how to filter data and prisitize different variables in a data set, and how to import data in as a data fram versus a table. We also got familiar with the powerful data visualization tool, Tableau.
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