Summary
Generating and gathering information using different analysis techniques and using it for decision-making is a growing field. Fields such as business intelligence (BI), AI, and ML require, and use, various data analysis techniques. Python programming provides a great infrastructure for the processes of data collection, data processing, information abstraction, and knowledge discovery. Libraries such as pandas, NumPy, csv, json, and plotly are the core Python libraries of the overall systematic process.
A practical introduction to the concepts related to data mining, data analysis, EDA, and data visualization was the main agenda of this chapter.
In the next chapter, we will be learning about machine learning and web scraping.
