Chapter 12 - Data handling using Python

Abstract

Recent advances in the life and computer sciences have permitted the use of computational techniques to address critical problems. Python is a free general-purpose programming language that is simple to learn and apply to a wide range of computational tasks. Python may be used to handle a variety of difficulties that research labs confront on a daily basis. Using computers and an appropriate programming language, it is possible to execute tasks such as data manipulation, biological data retrieval and parsing, automation, and simulation of biological problems efficiently. The goal of this chapter is to give a high-level look at the Python programming language, showing how it works and what it can do. The main data structures and flow control statements are shown. Following these fundamental concepts, topics such as file access, functions, and modules are addressed in greater depth. This chapter introduces the reader to Anaconda, a distribution software that includes libraries, packages, and editors (such as Jupyter notebooks) essential for Python development. The datatypes, regularly used operators in each datatype, and a range of helpful built-in data structures, such as strings, lists, tuples, and dictionaries, are introduced. Iterations are also described using terms such as while and for loops. Finally, objects and modules were introduced, and their use in data processing was described. At the end, there are references to more advanced Python topics.