Big Data is helpful to understanding progress on important goals. Analyzing which renewable energy sources help reduce GHG emissions for energy. While questioning what factors are most important to sstudent success in education.



  • Hypothesis Formation
  • Finding Datasets
  • Data Cleaning and Merging (Pandas)
  • Graphing (Matplotlib)
  • Statistical Analysis and Significance Tests

Key Learnings

  • Data analysis helps us come to conclusions about the root causes of a problem because it identifies the effects. Further research is done to identify the causes and finally identify solutions.
  • Data cleaning is a pain.
  • Significance tests are necessary to identify correlations from coincidences
  • Merging data is the best way to arrive at new discoveries. What you compare is also important. Although people may have the same data, their perspectives are different, which gives different meaning to the data.