Summary
In this chapter, we went over the definitions of experimental data and validity, reliability, and generalizability in the context of experiments. We also discussed how to install and use the pandas, NumPy, and Matplotlib libraries so that we could use them to organize and display data. Some of the skills you learned include defining an experiment, data gathering, and how computational thinking helps us define problems and design what we'd use to display our results.
In addition, we learned about data analysis and data science and its growth and importance in our current world. We were able to use the libraries to produce a plot that represented a subset of a data file using a Matplotlib bar chart.
In the next chapter, we'll be learning more about data and other applications of data science and data analysis.
