20.12.2022
Manipulating Python Strings as part of the Working with Text Data in Python provide a clear basic understanding of the Python Programming.
Great learning!
with Martin Ganchev
This course teaches you how to work with text data, list comprehensions, anonymous (Lambda) functions, and other Python tools that will be your indispensable stepping stones to becoming an advanced Python user.
This course is short yet intense. We assume you’re no stranger to Jupyter and Python fundamentals, such as conditionals, functions, sequences, and iterations. Nevertheless, a lack of experience working with text data, list comprehensions, and anonymous (Lambda) functions would immediately reveal to your data science colleagues that coding in Python hasn’t become second nature. In the following sections, we explain these intermediate programming tools in detail and provide an extensive set of exercises to ensure your ability to comply with today’s best practices in the field.
This course allows you to dig deeper than Python fundamentals. It focuses on intermediate tools that prove effective and efficient when processing large amounts of text and quantitative data.
What are intermediate Python tools, and why do we need to learn and practice them?
Course Introduction Free Python Refresher and Setting Up the EnvironmentWhether you use Python for general programming or analytics, you’ll not only manage quantitative data; you’ll also need to clean and preprocess vast amounts of text data. This section covers various tools—such as argument specifiers and string accessors—to help you manipulate text data. We’ll also work with widely-applicable Python string methods, such as .split(), .strip(), and .format().
Dealing with Text Data and Argument Specifiers Free Working with Python Strings at the Next Level Free Exploring Python String Methods - Part I Exploring Python String Methods - Part II Learning How to Use String Accessors Working with the .format() MethodOnce accustomed to manipulating text data, doors will open for you to employ several tools that will optimize the use of iterations and functions to the highest level. You’ll learn and apply iteration over range objects, nested for loops, list comprehensions, and anonymous (Lambda) functions.
The Concept of Iterating Over Range Objects in Python Free Introduction to Nested For Loops Working with Triple Nested For Loops Using List Comprehensions Working with Anonymous (Lambda) Functionswith Martin Ganchev