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Python Data Structures

Charles Russell Severance

4.9

Based on 97,067 ratings

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Charles Russell Severance

This course will introduce the core data structures of the Python programming language. We will move past the basics of procedural programming and explore how we can use the Python built-in data structures such as lists, dictionaries, and tuples to perform increasingly complex data analysis. This course will cover Chapters 6-10 of the textbook “Python for Everybody”. This course covers Python 3.

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What's inside

Syllabus

Chapter Six: Strings

In this class, we pick up where we left off in the previous class, starting in Chapter 6 of the textbook and covering Strings and moving into data structures. The second week of this class is dedicated to getting Python installed if you want to actually run the applications on your desktop or laptop. If you choose not to install Python, you can just skip to the third week and get a head start.

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Taught by Charles Russell Severance, who is widely recognized for Python development and education

Teaches the foundational Python data structures to effectively perform data analysis

Provides step-by-step instruction on key concepts and practical applications

Covers real-world data analysis scenarios to enhance understanding and make the concepts relatable

Emphasizes the use of Python built-in data structures for efficient and effective data processing

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Reviews summary

Python data structures fundamentals

Learners say this course provides an excellent foundation in core Python data structures like strings, files, lists, dictionaries, and tuples. Many highlight the instructor's clear and engaging teaching style as a significant strength, making complex concepts easy to grasp. The course is particularly praised for its hands-on coding exercises and practical examples, which effectively reinforce learning. While some advanced learners found the pacing a bit slow or the content less in-depth on algorithmic complexity, it is widely considered perfect for beginners and those looking to solidify their understanding of fundamental Python concepts for data analysis. The optional Python Code Playground is also a noted positive feature.

Provides useful tools like the Python Code Playground.

"The Python Code Playground was super useful for quick tests without needing local installation."

"It was great to have the online playground to try out code snippets directly in the browser."

"I appreciated the flexible setup, allowing me to practice either locally or with the provided online tools."

Well-suited for learners new to data structures or Python basics.

"I found the pacing a bit slow at times as I already had some programming experience, but it's perfect for beginners."

"Fantastic course, perfect for taking after the Python basics. It makes data structures approachable."

"This course is a fantastic follow-up to the introductory Python course, making it great for early learners."

Offers effective hands-on coding exercises and practical examples.

"The hands-on coding exercises reinforce learning effectively."

"The examples are practical, and the way files are introduced is very helpful for real-world applications."

"I found the practical examples in the course very helpful for understanding how to apply the concepts."

Instructor's teaching style praised for clarity and engagement.

"Dr. Charles Severance's teaching style is engaging and easy to follow."

"The instructor's explanations are very methodical, which I appreciated."

"Dr. Chuck is a great instructor, making even complex topics easy to understand."

Exceptionally clear explanations for fundamental data structures.

"The explanations for lists, dictionaries, and tuples are incredibly clear, making complex concepts easy to grasp."

"Absolutely brilliant! This course solidified my understanding of how to effectively use Python's built-in data structures."

"I learned how to effectively use Python's built-in data structures, which was a huge help for my data analysis work."

Too basic for experienced programmers seeking advanced topics.

"While the content is good for beginners, I found it a bit too basic for my needs."

"I wish there were more challenging projects or a deeper dive into algorithmic complexity for using these structures."

"It largely rehashes what's in the 'Python for Everybody' book. If you've read that, this might feel redundant."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Python Data Structures with these activities:

Organize Course Materials for Future Reference

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Compile and organize course materials such as notes, assignments, and quizzes for easy access and future review.

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Create a dedicated folder or notebook for course materials.
Organize materials by topic or week.
Review materials periodically to reinforce learning.

Participate in Peer Coding Sessions

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Engage in peer coding sessions to collaborate, share knowledge, and collectively solve programming challenges.

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Join or create a peer coding group or forum.
Participate in discussions and ask questions on specific coding topics.
Collaborate on coding projects and provide feedback to peers.

Delve into Python File Handling Operations

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Follow guided tutorials to grasp the fundamentals and advanced techniques of file handling operations in Python.

Browse courses on Files

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Study tutorials on file open, read, write, and close operations.
Practice working with text and binary files.
Explore techniques for handling large files and optimizing file operations.

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Practice with Lists and Dictionaries Data Structures

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Practice working with lists and dictionaries data structures to solidify understanding of their usage and implementation.

Browse courses on Lists

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Create a list of strings and perform operations like indexing, slicing, and concatenation.
Create a dictionary of key-value pairs and perform operations like accessing, adding, and deleting elements.
Solve programming problems that involve manipulating lists and dictionaries.

Explore Advanced String Manipulation Techniques

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Follow guided tutorials to enhance understanding of advanced string manipulation techniques and their applications.

Browse courses on Strings

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Study tutorials on regular expressions and their use in string matching and processing.
Practice using string formatting methods to create complex and dynamic strings.
Explore advanced string algorithms and their implementation in Python.

Develop a Python Script for Data Visualization

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Create a Python script that utilizes libraries like Matplotlib or Seaborn to visualize data and enhance understanding of data patterns and trends.

Browse courses on Data Visualization

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Choose a dataset and gather necessary data.
Write a Python script using Matplotlib or Seaborn to create visualizations like bar charts, line graphs, or scatter plots.
Customize the visualizations by adjusting axis labels, colors, and styles.
Interpret the visualizations and draw insights from the data.

Read 'Python for Data Analysis'

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Review a comprehensive book on Python for data analysis to gain a deeper understanding of data manipulation and analysis techniques.

View Python for Data Analysis on Amazon

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Read chapters related to data structures, file handling, and data analysis.
Work through the practice exercises and examples provided in the book.
Apply the concepts learned to real-world data analysis projects.

Career center

Learners who complete Python Data Structures will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists gather and analyze data to identify meaningful insights and trends. Proficiency in Python is helpful because many of the tools used in Data Science, such as NumPy and Pandas, operate within the Python ecosystem. This course helps build a foundation in core Python data structures in support of this work.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts evaluate and interpret data, and make insights and recommendations. With the aid of tools like Python, they help prevent issues, identify trends, and develop new products and services. This course can help build a foundation in Python for working with data structures, a core aspect of Data Analysis.

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Machine Learning Engineer

Machine Learning Engineers develop and maintain machine learning models. The use of Python in Machine Learning is very widespread, and thus a strong command of Python's data structures is necessary.

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Data Engineer

Data Engineers build, maintain, and improve data pipelines. Familiarity with Python's data structures is very important, as Data Engineers use them to build a wide variety of data pipelines.

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Software Engineer

Software Engineers design, build, and improve software solutions. Proficient knowledge of Python and its data structures is required, as it is one of the most popular and in-demand programming languages used by companies today. This course provides practical experience working with Python's core data structures.

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Web Developer

Web Developers build and maintain websites and web applications. Python is commonly used for web development, particularly for backend development. Familiarity with Python's data structures is fundamental for this role.

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Business Analyst

Business Analysts help businesses understand their data and make better decisions. Business Analysts use a variety of tools and techniques, including Python, to analyze data and identify trends. This course can help build a foundation in Python and its data structures, which are essential for the role.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical modeling to analyze risk and make investment decisions. Proficient knowledge of Python and its data structures is a requirement for this role, as Python is widely used in the finance industry.

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Product Manager

Product Managers are responsible for the development and launch of new products. They work with engineers, designers, and marketers to bring products to market. Familiarity with Python and its data structures may be helpful for organizing and analyzing product data.

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Technical Writer

Technical Writers create documentation for software and other technical products. Familiarity with Python and its data structures may be helpful for understanding the products being documented.

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Database Administrator

Database Administrators manage and maintain databases. Familiarity with Python and its data structures may be helpful for optimizing database performance and managing data.

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Information Security Analyst

Information Security Analysts protect computer systems and networks from cyber attacks. Familiarity with Python and its data structures may be helpful for developing and implementing security solutions.

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IT Support Specialist

IT Support Specialists provide technical support to users of computers and networks. Familiarity with Python and its data structures may be helpful for troubleshooting technical issues.

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Computer Programmer

Computer Programmers write and maintain computer programs. Familiarity with Python and its data structures is essential for this role.

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Software Tester

Software Testers test software to ensure that it meets requirements and is free of defects. Familiarity with Python and its data structures may be helpful for developing and executing test cases.

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Featured in The Course Notes

This course is mentioned in our blog, The Course Notes. Read one article that features Python Data Structures:

5 New Specializations that Teach You Future-Proof Skills

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Reading list

We've selected 25 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Python Data Structures.

Python for Everybody

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This is the required textbook for the course. The course covers chapters 6-10 of the book.

Python Data Structures

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What's inside

Syllabus

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Reviews summary

Python data structures fundamentals

Activities

Career center

Featured in The Course Notes

Reading list

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