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Scott Rixner
and
Joe Warren
This course will continue the introduction to Python programming that started with Python Programming Essentials and Python Data Representations. We'll learn about reading, storing, and processing tabular data, which are common tasks. We will also teach you about CSV files and Python's support for reading and writing them. CSV files are a generic, plain text file format that allows you to exchange tabular data between different programs. These concepts and skills will help you to further extend your Python programming knowledge and allow you to process more complex data.
Read more
This course will continue the introduction to Python programming that started with Python Programming Essentials and Python Data Representations. We'll learn about reading, storing, and processing tabular data, which are common tasks. We will also teach you about CSV files and Python's support for reading and writing them. CSV files are a generic, plain text file format that allows you to exchange tabular data between different programs. These concepts and skills will help you to further extend your Python programming knowledge and allow you to process more complex data.
Read more
This course will continue the introduction to Python programming that started with Python Programming Essentials and Python Data Representations. We'll learn about reading, storing, and processing tabular data, which are common tasks. We will also teach you about CSV files and Python's support for reading and writing them. CSV files are a generic, plain text file format that allows you to exchange tabular data between different programs. These concepts and skills will help you to further extend your Python programming knowledge and allow you to process more complex data.
By the end of the course, you will be comfortable working with tabular data in Python. This will extend your Python programming expertise, enabling you to write a wider range of scripts using Python.
This course uses Python 3. While most Python programs continue to use Python 2, Python 3 is the future of the Python programming language. This course uses basic desktop Python development environments, allowing you to run Python programs directly on your computer.
Register for this course and see more details by visiting:
OpenCourser.com/course/ymo8w6/python
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What's inside
Syllabus
Dictionaries
This module will teach you about Python's dictionary data type and its capabilities. Dictionaries are used to map keys to values within programs.
Read more
Syllabus
Dictionaries
This module will teach you about Python's dictionary data type and its capabilities. Dictionaries are used to map keys to values within programs.
Read more
Tabular Data and Nested Data Structures
This module will teach you about storing tabular data within Python programs using lists and dictionaries.
Tabular Data and CSV Files
This module will teach you the basics of CSV files and how to read them from Python programs. We will discuss the use of Python's csv module to help you access tabular data in CSV files.
Organizing Data
This module will teach you how to sort data in Python. You will organize and analyze tabular data.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Covers Python 3, which is the future of Python
Examines working with tabular data, which is common in industry
Teaches dictionaries, tabular data, and CSV files, which are core to Python programming
Develops Python programming expertise, which is useful in a variety of settings
Strengthens existing foundations in Python programming
Taught by Scott Rixner and Joe Warren, who are recognized for their work in Python
Save this course
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Reviews summary
Helpful python data analysis resource
Learners say that this course provides great learning and is particularly good for beginners. It helps learners practice writing and reading CSV files and develop their data analysis skills in Python. There are many exercises that enable learners to build a strong understanding of the concepts. The course is found to be challenging but worthwhile, and learners appreciate the support from the instructors and the active discussion forums. The final project is often mentioned as being complex and time-consuming, but overall, learners recommend this course.
Suitable for beginners in Python data analysis
"Great class. It might not be perfect for beginners, but good for someone who has had one semester in Python programming"
"I am a 17 year old high school student and want to be a data scientist one day. This course really helped me develop my python knowledge"
"If anyone likes to learn more about python, I would say this is the course you should take"
Focuses on reading and writing CSV files in Python
"This course is so great. The baseball project is very interesting"
"This module is very good for learning about reading/writing of CSV file and making use of lists or dictionaries to store contents of the CSV files"
"this course is very helpful to me to increase my coding skills on data analysis and the facuilty are very knowledgable and willing to share their knowledge"
Instructors are awesome and helpful
"Instructors are awesome and very helpful"
"the instructors way of teaching is quite attractive and interactive"
"Many thanks for the two amazing Professors"
Many helpful assignments to reinforce concepts
"need more practice exercises, but very good course overall"
"Assignments get tough for a beginner like me. But that is exactly what is required to learn the material"
"The assignments in this course teach you to learn very much due to difficulty level"
The complex final project requires a lot of practice
"This course requires a lot of practice to be able to solve the project"
"The final project was demanding not due to programming, but due to the idea of "code refactoring" and unclear dependencies on csv files"
"Final project is way more difficult than what they explain in the course"
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 Analysis with these
activities:
Review Python Basics Before Starting the Course
Show steps
If you have some experience with Python, this activity will help you brush up on the basics before starting the course.
Browse courses on
Python Basics
Show steps
-
Review the Python documentation.
-
Take a Python practice test.
-
Complete a few Python coding exercises.
Follow a Python Tutorial Series
Show steps
Following a tutorial series can help you learn the basics of Python and get up to speed quickly.
Browse courses on
Python
Show steps
-
Choose a tutorial series that is appropriate for your skill level.
-
Follow the tutorials in the series and complete the exercises.
-
Create a small Python program that you can use to solve a problem in your life.
Create a Python Study Guide
Show steps
Creating a study guide can help you organize your notes and prepare for the course.
Browse courses on
Python Programming
Show steps
-
Compile notes from the class lectures.
-
Review the Python documentation and add any important information to your notes.
-
Organize your notes into a logical format.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Read Introduction to Python Programming
Show steps
This book provides a quick and easy way to learn the basics of Python without having to know anything about programming.
View
Introduction to Computation and Programming...
on Amazon
Show steps
-
Read Chapters 1-3.
-
Complete the exercises at the end of each chapter.
-
Create a small Python program that you can use to solve a problem in your life.
Join a Python Study Group
Show steps
Joining a study group can help you stay motivated and learn from others.
Browse courses on
Python Programming
Show steps
-
Find a study group that meets regularly.
-
Attend the study group meetings.
-
Participate in discussions and ask questions.
Practice Python Coding Exercises
Show steps
Practice is key to learning Python. These exercises can help you master the basics and improve your skills.
Browse courses on
Python Coding
Show steps
-
Find a set of Python coding exercises (such as those on LeetCode).
-
Attempt to solve the exercises on your own.
-
Review the solutions to the exercises to see how you can improve your approach.
Write a Blog Post or Article on Python
Show steps
Writing about what you learn is a great way to reinforce your understanding and share your knowledge with others.
Browse courses on
Python Programming
Show steps
-
Choose a topic that you are familiar with.
-
Research the topic to make sure you have a good understanding of it.
-
Write a blog post or article that explains the topic in a clear and concise way.
Contribute to an Open Source Python Project
Show steps
Contributing to open source projects can help you learn how to work with others and make a real-world impact.
Browse courses on
Python Programming
Show steps
-
Find an open source Python project that you are interested in.
-
Read the project documentation and start contributing to the project.
-
Submit pull requests to the project and work with others to improve the project.
Review Python Basics Before Starting the Course
Show steps
If you have some experience with Python, this activity will help you brush up on the basics before starting the course.
Browse courses on
Python Basics
Show steps
Show steps
Show steps
- Review the Python documentation.
- Take a Python practice test.
- Complete a few Python coding exercises.
Follow a Python Tutorial Series
Show steps
Following a tutorial series can help you learn the basics of Python and get up to speed quickly.
Browse courses on
Python
Show steps
Show steps
Show steps
- Choose a tutorial series that is appropriate for your skill level.
- Follow the tutorials in the series and complete the exercises.
- Create a small Python program that you can use to solve a problem in your life.
Create a Python Study Guide
Show steps
Creating a study guide can help you organize your notes and prepare for the course.
Browse courses on
Python Programming
Show steps
Show steps
Show steps
- Compile notes from the class lectures.
- Review the Python documentation and add any important information to your notes.
- Organize your notes into a logical format.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Read Introduction to Python Programming
Show steps
This book provides a quick and easy way to learn the basics of Python without having to know anything about programming.
View
Introduction to Computation and Programming...
on Amazon
Show steps
Show steps
Show steps
- Read Chapters 1-3.
- Complete the exercises at the end of each chapter.
- Create a small Python program that you can use to solve a problem in your life.
Join a Python Study Group
Show steps
Joining a study group can help you stay motivated and learn from others.
Browse courses on
Python Programming
Show steps
Show steps
Show steps
- Find a study group that meets regularly.
- Attend the study group meetings.
- Participate in discussions and ask questions.
Practice Python Coding Exercises
Show steps
Practice is key to learning Python. These exercises can help you master the basics and improve your skills.
Browse courses on
Python Coding
Show steps
Show steps
Show steps
- Find a set of Python coding exercises (such as those on LeetCode).
- Attempt to solve the exercises on your own.
- Review the solutions to the exercises to see how you can improve your approach.
Write a Blog Post or Article on Python
Show steps
Writing about what you learn is a great way to reinforce your understanding and share your knowledge with others.
Browse courses on
Python Programming
Show steps
Show steps
Show steps
- Choose a topic that you are familiar with.
- Research the topic to make sure you have a good understanding of it.
- Write a blog post or article that explains the topic in a clear and concise way.
Contribute to an Open Source Python Project
Show steps
Contributing to open source projects can help you learn how to work with others and make a real-world impact.
Browse courses on
Python Programming
Show steps
Show steps
Show steps
- Find an open source Python project that you are interested in.
- Read the project documentation and start contributing to the project.
- Submit pull requests to the project and work with others to improve the project.
Career center
Learners who complete Python Data Analysis will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts use their programming skills to analyze data. They often must read and understand large amounts of tabular data, and reshape the data into different formats. This course teaches the basics of working with tabular data in Python, which is one of the most popular programming languages for data analysis. This course will teach you how to overcome obstacles that can occur while trying to read, store, and process tabular data, which will make you a more effective Data Analyst.
Business Analyst
Business Analyst
Business Analysts often partner with Data Analysts. Both roles collect and analyze data, but Business Analysts typically focus on the business side of data from a high level. This course provides a foundation in working with tabular data, which will be useful to a Business Analyst who wants to understand data in more detail.
Data Scientist
Data Scientist
Data Scientists are similar to Data Analysts, but they typically deal with much more complex problems and are often expected to build predictive models. This course is a useful introduction to reading and writing tabular data in Python, which are important skills for Data Scientists.
Software Engineer
Software Engineer
Software Engineers develop and maintain software products. While Software Engineers do not typically analyze data in the same way as Data Analysts or Data Scientists, they do often need to work with tabular data. This course can help you build a foundation in working with tabular data in Python, which is a valuable skill for Software Engineers.
Product Manager
Product Manager
Product Managers are responsible for the development and success of products. This course can be helpful in building a foundation in working with tabular data in Python, which can be useful for Product Managers who analyze large amounts of data.
Data Engineer
Data Engineer
Data Engineers build and maintain the infrastructure that allows Data Analysts and Data Scientists to do their jobs. This course can be helpful in building a foundation in working with tabular data in Python.
Actuary
Actuary
Actuaries use mathematical and statistical methods to assess risk in the insurance and finance industries. This course can help you build a foundation in working with tabular data in Python, which is a valuable skill for Actuaries.
Epidemiologist
Epidemiologist
Epidemiologists investigate the causes of disease and other health problems in populations. This course can be helpful in building a foundation in working with tabular data in Python, which can be useful for Epidemiologists who analyze large amounts of data.
Biostatistician
Biostatistician
Biostatisticians apply statistical methods to data in the biological sciences. This course can be helpful in building a foundation in working with tabular data in Python, which can be useful for Biostatisticians who analyze large amounts of data.
UX Researcher
UX Researcher
UX Researchers study how users interact with products and services. This course can be helpful in building a foundation in working with tabular data in Python, which can be useful for UX Researchers who analyze large amounts of data.
Market Researcher
Market Researcher
Market Researchers collect and analyze data about consumers and markets. This course can be helpful in building a foundation in working with tabular data in Python, which can be useful for Market Researchers who analyze large amounts of data.
Data Journalist
Data Journalist
Data Journalists use data to tell stories. This course can be helpful in building a foundation in working with tabular data in Python, which can be useful for Data Journalists who analyze large amounts of data.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical methods to solve problems in a variety of industries. This course can help you build a foundation in working with tabular data in Python, which is a useful skill for Operations Research Analysts.
Statistician
Statistician
Statisticians use mathematical and statistical methods to collect, analyze, interpret, and present data. This course can help you build a foundation in working with tabular data in Python, which is useful for Statisticians.
Financial Analyst
Financial Analyst
Financial Analysts analyze financial data to make investment recommendations. This course can be helpful in building a foundation in working with tabular data in Python, which is useful for reading and analyzing financial data.
For more career information including salaries, visit:
OpenCourser.com/course/ymo8w6/python
Reading list
We've selected 18 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 Analysis.
Provides a comprehensive overview of data analysis in Python, covering topics such as data cleaning, exploration, and visualization. It valuable resource for anyone looking to learn more about data analysis in Python.
Provides a comprehensive overview of machine learning in Python, covering topics such as supervised learning, unsupervised learning, and deep learning. It good choice for anyone who wants to learn more about machine learning in Python.
Provides a comprehensive overview of deep learning in Python, covering topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks. It good choice for anyone who wants to learn more about deep learning in Python.
Provides a comprehensive overview of natural language processing in Python, covering topics such as text classification, text clustering, and machine translation. It good choice for anyone who wants to learn more about natural language processing in Python.
Provides a comprehensive overview of computer vision in Python, covering topics such as image classification, object detection, and image segmentation. It good choice for anyone who wants to learn more about computer vision in Python.
Provides a comprehensive overview of data science in Python, covering topics such as data cleaning, exploration, and visualization. It good choice for anyone who wants to learn more about data science in Python.
Provides a comprehensive overview of deep learning, with a focus on using the Keras library. It good choice for anyone who wants to learn more about deep learning.
Provides a comprehensive overview of machine learning in Python, with a focus on using the Scikit-Learn, Keras, and TensorFlow libraries. It good choice for intermediate users who want to learn more about machine learning in Python.
Practical guide to machine learning in Python. It covers topics such as supervised learning, unsupervised learning, and deep learning. It good choice for beginners who want to learn more about machine learning in Python.
Save
Practical guide to data analysis in Python. It covers topics such as data cleaning, exploration, and visualization. It good choice for beginners who want to learn more about data analysis in Python.
Comprehensive guide to data analysis with Python and Pandas. It covers all the essential topics, from data cleaning and preparation to data visualization and modeling. It valuable resource for anyone who wants to learn how to use Python and Pandas for data analysis.
Comprehensive guide to data science. It covers all the essential topics, from data cleaning and preparation to data visualization and modeling. It valuable resource for anyone who wants to learn how to use data science for real-world problems.
Comprehensive guide to deep learning with Python. It covers all the essential topics, from data cleaning and preparation to data visualization and modeling. It valuable resource for anyone who wants to learn how to use deep learning for real-world problems.
Comprehensive guide to natural language processing with Python. It covers all the essential topics, from data cleaning and preparation to data visualization and modeling. It valuable resource for anyone who wants to learn how to use natural language processing for real-world problems.
Comprehensive guide to big data analysis with Python. It covers all the essential topics, from data cleaning and preparation to data visualization and modeling. It valuable resource for anyone who wants to learn how to use big data analysis for real-world problems.
Save
Comprehensive guide to Python for signal processing. It covers all the essential topics, from data cleaning and preparation to data visualization and modeling. It valuable resource for anyone who wants to learn how to use Python for signal processing.
Comprehensive guide to computer vision with Python. It covers all the essential topics, from data cleaning and preparation to data visualization and modeling. It valuable resource for anyone who wants to learn how to use computer vision for real-world problems.
Comprehensive guide to Python for finance. It covers all the essential topics, from data cleaning and preparation to data visualization and modeling. It valuable resource for anyone who wants to learn how to use Python for financial analysis.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/ymo8w6/python
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Effort
This is a four week class with an expected workload of 5-7 hours per week.
Level
Introductory
Via
Coursera
Institution
Rice University
Instructors
Scott Rixner
Joe Warren
Language
English
Transcripts
Español
Français
Português
Deutsch
Italiano
中文
العربية
한국어
日本語
हिंदी
Nederlands
Svenska
Pусский
Türkçe
Polski
Ελληνικά
українська мова
magyar nyelv
Bahasa Indonesia
ไทย
қазақша
اُردُو,
فارسی
বাংলা
tiếng Việt
پښتو
آذربایجان دیلی
This course belongs to a
collection
called
Introduction to Scripting in Python. It's comprised of four courses:
- Python Programming Essentials
- Python Data Visualization
- Python Data Representations
- Python Data Analysis (viewing)
Good to know
Covers Python 3, which is the future of Python
Examines working with tabular data, which is common in industry
Teaches dictionaries, tabular data, and CSV files, which are core to Python programming
Develops Python programming expertise, which is useful in a variety of settings
Strengthens existing foundations in Python programming
Taught by Scott Rixner and Joe Warren, who are recognized for their work in Python
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