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Python Data Structures
Charles Russell Severance
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/wts33i/python
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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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.
Read more
Unit: Installing and Using Python
In this module you will set things up so you can write Python programs. We do not require installation of Python for this class. You can write and test Python programs in the browser using the "Python Code Playground" in this lesson. Please read the "Using Python in this Class" material for details.
Chapter Seven: Files
Up to now, we have been working with data that is read from the user or data in constants. But real programs process much larger amounts of data by reading and writing files on the secondary storage on your computer. In this chapter we start to write our first programs that read, scan, and process real data.
Chapter Eight: Lists
As we want to solve more complex problems in Python, we need more powerful variables. Up to now we have been using simple variables to store numbers or strings where we have a single value in a variable. Starting with lists we will store many values in a single variable using an indexing scheme to store, organize, and retrieve different values from within a single variable. We call these multi-valued variables "collections" or "data structures".
Chapter Nine: Dictionaries
The Python dictionary is one of its most powerful data structures. Instead of representing values in a linear list, dictionaries store data as key / value pairs. Using key / value pairs gives us a simple in-memory "database" in a single Python variable.
Chapter Ten: Tuples
Tuples are our third and final basic Python data structure. Tuples are a simple version of lists. We often use tuples in conjunction with dictionaries to accomplish multi-step tasks like sorting or looping through all of the data in a dictionary.
Graduation
To celebrate your making it to the halfway point in our Python for Everybody Specialization, we welcome you to attend our online graduation ceremony. It is not very long, and it features a Commencement speaker and very short commencement speech.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
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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Career center
Learners who complete Python Data Structures will develop knowledge and skills
that may be useful to these careers:
Data Analyst
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.
Data Scientist
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.
Machine Learning Engineer
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.
Data Engineer
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.
Software Engineer
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.
Web Developer
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.
Quantitative Analyst
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.
Business Analyst
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.
Product Manager
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.
Software Tester
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.
Database Administrator
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.
Information Security Analyst
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.
Technical Writer
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.
IT Support Specialist
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.
Computer Programmer
Computer Programmer
Computer Programmers write and maintain computer programs. Familiarity with Python and its data structures is essential for this role.
For more career information including salaries, visit:
OpenCourser.com/course/wts33i/python
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.
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This is the required textbook for the course. The course covers chapters 6-10 of the book.
This comprehensive textbook covers a wide range of data structures and algorithms in Python, making it a valuable resource for learners looking to deepen their understanding of these topics.
Great supplemental read to the course. More valuable as additional reading than reference.
Would serve as a good background read as it covers not only data structures but also algorithms, which could provide a deeper understanding of the topics covered in this course.
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Another great supplemental read. Serves as a useful reference tool.
Would serve as a useful supplemental resource for this course, especially for learners interested in data analysis using Python.
While this book is more focused on algorithms than data structures, it provides a solid foundation for understanding the concepts behind the data structures covered in this course.
Provides a more accessible and engaging approach to learning algorithms, making it a good choice for learners who want a less technical introduction.
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Goes in-depth into computer science as a whole, including data structures.
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In-depth exploration of Python. Useful as a reference when reviewing topics from the course.
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Serves as a solid reference text.
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Provides a collection of practical recipes for solving common Python programming problems.
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Takes a deep look at advanced Python programming.
Provides a comprehensive introduction to data structures and algorithms in Python. It covers a wide range of topics, including lists, dictionaries, sets, stacks, queues, trees, and graphs.
Save
Provides a buffet of add-on features for Python programming.
Provides a comprehensive introduction to data structures and algorithms in Java. It covers a wide range of topics, including lists, dictionaries, sets, stacks, queues, trees, and graphs.
Provides a comprehensive introduction to data structures and algorithms in Java. It covers a wide range of topics, including lists, dictionaries, sets, stacks, queues, trees, and graphs.
Provides a comprehensive introduction to data structures and algorithms in C++. It covers a wide range of topics, including lists, dictionaries, sets, stacks, queues, trees, and graphs.
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Takes a pragmatic approach to learning Python, focusing on code quality.
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Provides a comprehensive introduction to algorithms, covering a wide range of topics, including sorting, searching, graph algorithms, and dynamic programming.
Provides a comprehensive introduction to algorithms, covering a wide range of topics, including sorting, searching, graph algorithms, and dynamic programming.
Provides a comprehensive introduction to algorithm design, covering a wide range of topics, including sorting, searching, graph algorithms, and dynamic programming.
Useful for beginners to Python and to data structures.
Serves as a handy reference for Python.
Save
Comprehensive reference for Python programming.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/wts33i/python
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2-4 hours/week
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Introductory
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University of Michigan
Instructor
Charles Russell Severance
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This course belongs to a
collection
called
Python for Everybody. It's comprised of five courses:
Good to know
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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