Python Data Structures and Comprehensions
Published by Pearson
Level Up Your Python Skills
- Provides much-needed focus on key topics to help Python coders advance
- Shows data structures that are in modules/libraries and not just the built-in ones
- Demonstrates how list comprehensions help you move to the next level of competency
Most Python courses out there are either catered to beginner or experienced developers, making it hard to progress if you’re somewhere in between. This intermediate Python class is geared toward those looking to move beyond the beginner level. It uses interactive labs to explore more advanced built-in features and cover some of the common modules and libraries one should know as a professional developer.
This class on data structures and comprehensions focuses on:
- Built-in features: sets, tuples, and comprehensions
- Built-in module: the collections module for named tuples, ordered dictionaries, and more
- External libraries: Numpy and Pandas libraries for modeling multi-dimensional arrays
You’ll get live, hands-on practice with experienced instructor, Arianne Dee, who has numerous trainings and videos getting people up to speed with Python.
What you’ll learn and how you can apply it
- The main features of tuples and sets, and how to use them
- How to use comprehensions as a powerful and Pythonic way to build lists, dicts, and sets
- Why to use data structures from other modules or libraries instead of built-in ones
And you’ll be able to:
- Make use of set operations, tuple unpacking, and the zip function
- Use basic, conditional, and nested comprehensions
- Create and use ndarray and DataFrame types for modeling multi-dimensional data for use in data science
This live event is for you because...
- You have learned the basics of the Python language and are looking for the next step
- You are interested in getting started with data analysis
- You have heard of list comprehensions but need hands-on practice to finally understand them and be comfortable using them
Prerequisites
- Basic Python knowledge, with an understanding of lists and dictionaries
Course Set-up
Follow instructions in github to:
- Install Python 3.7+
- Install an IDE that supports Jupyter notebooks
- Download the source code
- Fill out the survey to be used in class
- Download the source code
Recommended Preparation
- For Python basics, including lists, watch: Lessons 1-4 of Introduction to Python Programming Live Lessons by Arianne Dee
OR
- Attend: Introduction to Python Programming by Arianne Dee
- For dictionaries, watch: Lesson 1.3 of Next Level Python by Arianne Dee
- For lists and dictionaries, practice: Steps 1 and 2 of Python Foundations: Data Structures by Arianne Dee
Recommended Follow-up
- Read: Data Structures & Algorithms in Python by John Canning, Alan Broder, and Robert Lafore
- Watch: Data Structures, Algorithms, and Machine Learning Optimization by Jon Krohn
- Read: Foundational Python for Data Science by Kennedy Behrman
Schedule
The time frames are only estimates and may vary according to how the class is progressing.
Segment 1: Course Setup (15 minutes)
- Intro
- Get Jupyter notebooks running
Segment 2: Built-in Data Structures (50 minutes)
- Lists
- Dictionaries
- Tuples
- Sets
Q&A and Break (10 minutes)
Exercise: Built-in data types data analysis (15 minutes)
Segment 3: Comprehensions (50 minutes)
- Basic list comprehensions
- Conditionals and nesting
- Dictionaries, sets, and generators
Q&A and Break (10 minutes)
Exercise: Comprehensions refactoring (5 minutes)
Segment 4: Standard Library Modules (50 minutes)
- Arrays
- The “collections” module
Q&A and Break (10 minutes)
Exercise: Collections library refactoring(5 minutes)
Segment 5: Data Science (50 minutes)
- Numpy arrays
- Pandas data frames
Exercise: Pandas data frames analysis(15 mins)
Segment 6: Custom Classes (10 mins)
- Subclassing built-ins
- Subclassing collections classes
- Dataclasses
Course wrap-up and next steps (5 minutes)
Your Instructor
Arianne Dee
Arianne is a full-stack software developer and freelancer, with a passion for user-focused design for the public good. She has bachelor’s degrees in Civil Engineering and Computer Science from the University of British Columbia, and has taught thousands of students, aged 9 – 99 through Engineers Without Borders, Canada Learning Code, and Pearson on the O’Reilly platform. Arianne’s most popular videos and live trainings help beginners and experienced developers get up to speed with Python