Читать книгу Introduction to Python Programming for Business and Social Science Applications - Frederick Kaefer - Страница 16

The development of the Internet has both made large amounts of information available to users, as well as enabled users to create large amounts of information and make it available to the rest of the world. Data are manipulated and processed using computer programming by both business and the social sciences to gain insights that would be too difficult to obtain otherwise. The Python programming language has been the most popular introductory programming language taught at American universities for good reasons. The explosive growth of “big data” in disciplines such as bioinformatics, neuroscience, and astronomy has made programming know-how ever more crucial, in that researchers who can write code in Python can manage their data sets and work more efficiently on research-related tasks, including analyzing and visualizing data (Perkel, 2015). The corporate world also recognizes the importance of analyzing data to gain insights about current and potential customers. In addition, corporations are developing business applications using Python for numerous purposes, including developing strategic information systems, including enterprise resource planning (ERP), customer relationship management (CRM), and ecommerce applications (Smets, 2019).

Several advantages that Python has compared to commercial packages such as SPSS and SAS are that Python is open source and can run on many platforms. Users are free to make copies, distribute, and even change the software. Python is perfect for teaching statistics in a data-rich environment and has simplified debugging for the programmer using its built-in debugging feature (Ozgur, Colliau, Rogers, Hughes, & Myer-Tyson, 2017). Like Python, the R programming language is also an open-source programming language used for data analytics. There is prolific use of both R and Python in the business world and for academic and research purposes. We focus on Python because we see a need for a text that presents Python programming specifically for those in the fields of social sciences and business to develop applications for data analytics. Whereas some may prefer R for statistical analysis and plotting charts, Python is a general-purpose scripting language used to develop applications with graphical user interfaces (GUIs) and may be favored when working with text-based data.