When should you use Python’s built-in data types, and when should you develop your own? In this video course, George Heineman introduces Python programmers to several important data structures and demonstrates their use with example algorithms. Generic data structures such as arrays, linked lists, and stacks can solve many problems, but to work through some specialized problems, you need to learn different ways to structure data appropriately.
Pandas Data Analysis with Python Fundamentals LiveLessons provides analysts and aspiring data scientists with a practical introduction to Python and pandas, the analytics stack that enables you to move from spreadsheet programs such as Excel into automation of your data analysis workflows.
Don't be limited by the Python you already know. You're ready to move beyond the skills you use everyday to more ambitious programming—and you're in the right place. Part of Python's appeal is how easily it can be used for a wide range of purposes. Get ready to learn some of the amazing features that are unique to Python and see how powerful it can be.
This course shows you how to build data pipelines and automate workflows using Python 3. From simple task-based messaging queues to complex frameworks like Luigi and Airflow, the course delivers the essential knowledge you need to develop your own automation solutions. You'll learn the architecture basics, and receive an introduction to a wide variety of the most popular frameworks and tools.
Learn how to make your Python code more efficient by using algorithms to solve a variety of tasks or computational problems. In this video course, you’ll learn algorithm basics and then tackle a series of problems—such as determining the shortest path through a graph and the minimum edit distance between two genomic sequences—using existing algorithms.
A practical guide that will give you hands-on experience with the popular Python data mining algorithms.
The need for building highly performant and maintainable user interfaces is now greater than ever. React, a library designed and developed by Facebook, can solve many of the existing problems users face today–including poor browser performance while handling dynamic interactions with high loads of data. React also solves a lot of challenges for front-end developers. Due to its popularity, other supporting frameworks, such as Redux, came into the picture to make applications more predictable, testable, and easier to debug. However, they come with a different approach to front-end development and testing.