Inspiration
We analyzed data from gas turbine engine factors to begin to identify potential advancements toward a net zero and sustainable energy future.
How we built it
We used Python and R to obtain site-level averaged data for each provided variable. The relationships with variables were investigated using Python. Visualization was carried out using Python seaborn and Google Earth.
Accomplishments that we're proud of
We have included the potential suggestion to improve higher thermal efficiency.
What we learned
We have learned to efficiently analyze a variety of tests and visually present them. We created a heatmap of correlation values and scatterplots in python, collected datasets into one cohesive dataframe in R, and used google my maps and google earth to present geographic data and individual differences data.
What's next for Baker Hughes: Gas Turbine Data Visualization Challenge
A more in-depth observation of factors that impact fuel efficiency would benefit real-world outcomes.
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