As you already know, Python has become one of the most popular, standard languages and is a complete package for data science-based operations. Python offers numerous libraries, such as NumPy, Pandas, SciPy, Scikit-Learn, Matplotlib, Seaborn, and Plotly. These libraries provide a complete ecosystem for data analysis that is used by data analysts, data scientists, and business analysts. Python also offers other features, such as flexibility, being easy to learn, faster development, a large active community, and the ability to work on complex numeric, scientific, and research applications. All these features make it the first choice for data analysis.
In this chapter, we will focus on various data analysis processes, such as KDD, SEMMA, and CRISP-DM. After this, we will provide a comparison between data analysis and data science, as well...
