Baker Hughes Emission Analysis

Inspiration

We were inspired by the goal of Baker Hughes to reach net zero emissions. With our backgrounds in statistics, we knew we could provide visualizations that bring insight into which factors contribute to a higher CO2 output

What it does

We built correlation plots, time series plots, and an interactive map to visualize the differences in emissions among customers, plants, and engines.

How we built it

We used RStudio to do our data cleaning and visualization, and Git to work together seamlessly.

Challenges we ran into

We faced initial difficulty because the data was split into over 100 files. Once we were able to combine data and write loops to access all the files, it was much easier to create our visualizations.

Accomplishments that we're proud of

We are proud of our clear and informative visualizations, and especially our interactive map of the emissions at each location.

What we learned

We learned about the main factors related to the performance and output of gas engines. We learned that there is some relationship between the CO2 output of the plant and the longitude, latitude, and elevation of the plant. We were able to detect outlier observations and create plots that allow us to diagnose seasonal trends in efficiency and emissions.

What's next for Baker Hughes Emission Analysis

Using this preliminary analysis, we could create statistical models that could provide a quantitative relationship between variables that contribute the most to CO2 emission. We could also predict the CO2 emissions for future months and years.

Built With

• git
• github
• r
• rstudio