A hands-on guide that will help you to write clean and efficient code in Python
Description
Python is one of the most popular programming languages in the world, with a vast community of developers and users. In order to start using Python effectively, it is important to have a strong understanding of its core concepts.
This comprehensive guide provides you with a solid foundation in the fundamental concepts of Python programming. It covers a range of important topics, including working with strings, flow control statements, exception handling, and regular expressions. You will also learn about the essential functions and data structures, and explore the use of pre-built packages to extend Python's capabilities. Numpy and data visualization with packages like Matplotlib are also discussed in depth, along with the popular data analysis and manipulation package, Pandas. This book is an essential resource for anyone looking to master Python and use its power to tackle real-world projects.
With a strong grasp of these core concepts, you will be well-equipped to write efficient and effective Python code.
What you will learn
● Learn how to write Python code in different IDEs like VSCode and Jupyter Notebook.
● Learn how to work with packages and modules in python.
● Get familiar with Python data science libraries.
● Understand how to use Regular expressions in Python.
● Learn how to write Python comments that are clean, concise, and useful.
Who this book is for
This book is designed to cater to a diverse audience, including students pursuing diplomas, undergraduate, and postgraduate degrees in any branch of Engineering and Science. It is also suitable for programming and software professionals looking to enhance their skills in Python.
Author(s): Saurabh Chandrakar; Dr. Nilesh Bhaskarrao Bahadure
Publisher: BPB Publications
Year: 2023
Language: English
Pages: 264
Chapter 1: Basic Python Introduction – will cover the basic elements of writing a Python program where readers can gain an understanding of the fundamental topics.
Chapter 2: Concept of Strings in Python – will cover strings in detail, as well as different string methods, usage of command-line arguments, and string access with some examples.
Chapter 3: Concept of Flow Control Statements in Python – will cover the concept of conditional, iterative, and transfer statements, with loop patterns such as star pattern, alphabet pattern, and number pattern, with examples.
Chapter 4: Concept of Exception Handling in Python – will cover the concept of multiple ways of using the try-except block, for preventing errors during runtime. Users will be able to create their exceptions for handling the errors. Moreover, the user will see different use cases and control flow of Python exception hierarchy.
Chapter 5: Concept of Regular Expressions in Python – will cover the declarative mechanism for the representation of a group of strings, according to a particular pattern called regular expressions, which is quite difficult to understand, and also perform its usage. Each regex expression is explained in a very lucid
manner with examples.
Chapter 6: Concept of Functions in Python – will cover function types, and different types of function arguments such as positional arguments, keyword arguments, default arguments, variable length arguments, and kwargs. Moreover, concepts on local, global and non-local variable are well explained with examples, along with Python closures.
Chapter 7: Concept of Data Structures in Python – will cover non-primitive inbuilt data structures such as list, tuple, set and dictionary, which are unique on their own. All the data structures definitions, methods, and different types of comprehensions such as list comprehension, tuple comprehension, set comprehension, and dictionary comprehension are well discussed.
Chapter 8: Concept of Packages in Python – will cover the demonstration of package examples, with different approaches to module usage.
Chapter 9: Numpy Introduction – will cover different examples of scientific computing and data analysis library, that is, numpy library.
Chapter 10: Data Visualization Introduction – will cover Matplotlib data visualization library by creating a line plot with examples.
Chapter 11: Pandas Introduction – will cover Pandas Series and Pandas DataFrame with examples.
