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Data Analysis and Visualization with Python

Adwith Malpe and Steven Osburn

In this course, you will learn how to read and write data from and to a file. You will also examine how to manipulate and analyze the data using lists, tuples, dictionaries, sets, and the pandas and Matplot libraries.

As a developer, it's important to understand how to deal with issues that could cause an application to crash. You will learn how to implement exceptions to handle these issues.

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In this course, you will learn how to read and write data from and to a file. You will also examine how to manipulate and analyze the data using lists, tuples, dictionaries, sets, and the pandas and Matplot libraries.

As a developer, it's important to understand how to deal with issues that could cause an application to crash. You will learn how to implement exceptions to handle these issues.

You do not need a programming or computer science background to learn the material in this course. This course is open to anyone who is interested in learning how to code and write programs in Python. We are very excited that you will be learning with us and hope you enjoy the course!

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What's inside

Syllabus

Module 1: Sequences
In this module, we will discuss lists, tuples, dictionaries and sets.
Module 2: File Input and Output
In this module, you will explore how to read in data from a file, store information to a file, and modify a file.
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Provides a solid foundation in programming concepts and data manipulation for novice learners
Taught by instructors with expertise in their field, ensuring high-quality content
Students will learn essential data analysis skills using industry-standard libraries and tools
Covers a wide range of data structures, providing a comprehensive understanding of data organization
Introduces exception handling for managing errors and ensuring code robustness

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Reviews summary

Foundational python data analysis

According to learners, this course is an excellent starting point for those new to programming or data analysis with Python. Many would find it exceptionally clear and accessible, appreciating the step-by-step approach to core concepts like Python data structures, file input/output, and error handling. The emphasis on practical application through libraries like pandas and Matplotlib would be a major strength, equipping students with foundational skills for manipulating and visualizing data. While it provides a solid introduction, some learners with prior programming experience might find the pace slow or the depth of coverage limited, as it focuses strictly on beginner-level concepts and might not delve into advanced data science techniques.
Emphasizes hands-on application of concepts and libraries.
"I'd appreciate the practical examples and the opportunities to apply what I learned immediately."
"The course would help me understand how to actually use Python for data manipulation, not just theoretical concepts."
"I would feel confident in applying Python for basic data analysis tasks after completing the course's exercises."
Provides a strong base in Python for data analysis.
"I would gain a solid understanding of manipulating data using lists, dictionaries, and file I/O operations."
"This course would give me practical skills in using the pandas and Matplotlib libraries for basic data tasks and visualization."
"It would provide an excellent starting point for learning how to analyze and visualize data effectively with Python."
Exceptionally clear and accessible for new programmers.
"This course would be perfect for me as someone entirely new to Python and coding!"
"I had no programming background and found the explanations of core concepts incredibly clear and easy to follow."
"It's truly open to anyone, making complex topics like data structures and exceptions very approachable for a beginner."
May be too basic or slow for learners with prior experience.
"For someone with existing Python knowledge, this course might feel a bit too slow or foundational."
"I might hope for more advanced topics or complex projects than what is covered in this introductory course."
"It's clearly a foundational course, so don't expect deep dives into highly advanced data science techniques or niche applications."

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 Data Analysis and Visualization with Python with these activities:
Review Python Basics
Refreshes understanding of Python fundamentals, ensuring a strong foundation for the course.
Browse courses on Python
Show steps
  • Review online resources or tutorials on Python basics.
  • Take practice quizzes or exercises to test your knowledge.
Review 'Python Crash Course' by Eric Matthes
Provides a comprehensive review of Python fundamentals, complementing the course content.
View Python Crash Course, 3rd Edition: A Hands-On,... on Amazon
Show steps
  • Read the book.
  • Take notes and summarize key concepts.
  • Complete the practice exercises in the book.
Join a Study Group
Facilitates collaboration and discussion, fostering a deeper understanding of course concepts.
Show steps
  • Find fellow students interested in forming a study group.
  • Set regular meeting times.
  • Discuss course material, share insights, and work on assignments together.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice Reading and Writing Files
Reinforces understanding of file operations by providing practical exercises.
Browse courses on File Handling
Show steps
  • Open a file for reading or writing.
  • Read data from the file line by line.
  • Write data to the file.
  • Close the file.
Create a New Pandas DataFrame from Scratch
Provides hands-on experience in creating and manipulating data structures in Python.
Browse courses on Pandas
Show steps
  • Import the Pandas library.
  • Create a new DataFrame using the DataFrame() constructor.
  • Specify the column names and data types.
  • Populate the DataFrame with data.
  • Print the DataFrame to console to verify its contents.
Follow Matplotlib Tutorials
Enhances understanding of data visualization techniques through guided tutorials.
Browse courses on Data Visualization
Show steps
  • Find online tutorials or documentation for Matplotlib.
  • Follow the tutorials to create different types of visualizations.
  • Experiment with different options and parameters.
  • Apply the learned techniques to real-world data.
Attend a Python Workshop
Provides hands-on experience and exposure to advanced Python techniques.
Browse courses on Python
Show steps
  • Find and register for a Python workshop.
  • Attend the workshop and actively participate.
  • Practice the concepts learned in the workshop.
Build a Simple Data Analysis Dashboard
Enhances data analysis skills by applying the concepts learned in the course to a practical project.
Browse courses on Data Visualization
Show steps
  • Gather and prepare the data.
  • Choose appropriate visualizations (e.g., charts, graphs).
  • Create the dashboard using a visualization tool (e.g., Tableau, Power BI).
  • Share the dashboard and gather feedback.

Career center

Learners who complete Data Analysis and Visualization with Python will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst collects, organizes, and interprets data to help businesses make informed decisions. This course provides a solid foundation in data manipulation and analysis techniques, which are essential skills for Data Analysts. The course covers topics such as data cleaning, data transformation, data visualization, and statistical analysis, which are all commonly used by Data Analysts in their daily work.
See salaries and explore the career path for Data Analyst
Data Scientist
A Data Scientist uses data to build models that can predict future outcomes or identify trends. This course provides a strong foundation in data analysis and visualization techniques, which are essential skills for Data Scientists. The course covers topics such as data mining, machine learning, and deep learning, which are all commonly used by Data Scientists in their daily work.
See salaries and explore the career path for Data Scientist
Business Analyst
A Business Analyst uses data to help businesses improve their operations. This course provides a solid foundation in data analysis and visualization techniques, which are essential skills for Business Analysts. The course covers topics such as data mining, data modeling, and data presentation, which are all commonly used by Business Analysts in their daily work.
See salaries and explore the career path for Business Analyst
Market Researcher
A Market Researcher collects and analyzes data to help businesses understand their customers. This course provides a strong foundation in data analysis and visualization techniques, which are essential skills for Market Researchers. The course covers topics such as survey design, data analysis, and data presentation, which are all commonly used by Market Researchers in their daily work.
See salaries and explore the career path for Market Researcher
Financial Analyst
A Financial Analyst uses data to make investment decisions. This course provides a strong foundation in data analysis and visualization techniques, which are essential skills for Financial Analysts. The course covers topics such as financial modeling, data analysis, and data presentation, which are all commonly used by Financial Analysts in their daily work.
See salaries and explore the career path for Financial Analyst
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This course may be useful for Software Engineers who want to learn more about data analysis and visualization techniques. The course covers topics such as data structures, algorithms, and software design, which are all commonly used by Software Engineers in their daily work.
See salaries and explore the career path for Software Engineer
Data Engineer
A Data Engineer builds and maintains data pipelines. This course may be useful for Data Engineers who want to learn more about data analysis and visualization techniques. The course covers topics such as data warehousing, data mining, and data visualization, which are all commonly used by Data Engineers in their daily work.
See salaries and explore the career path for Data Engineer
Database Administrator
A Database Administrator manages and maintains databases. This course may be useful for Database Administrators who want to learn more about data analysis and visualization techniques. The course covers topics such as database design, data optimization, and data security, which are all commonly used by Database Administrators in their daily work.
See salaries and explore the career path for Database Administrator
Statistician
A Statistician collects, analyzes, and interprets data. This course may be useful for Statisticians who want to learn more about data visualization techniques. The course covers topics such as statistical modeling, data analysis, and data presentation, which are all commonly used by Statisticians in their daily work.
See salaries and explore the career path for Statistician
Actuary
An Actuary uses data to assess risk and uncertainty. This course may be useful for Actuaries who want to learn more about data analysis and visualization techniques. The course covers topics such as probability, statistics, and financial modeling, which are all commonly used by Actuaries in their daily work.
See salaries and explore the career path for Actuary
Epidemiologist
An Epidemiologist investigates the causes of disease and other health problems. This course may be useful for Epidemiologists who want to learn more about data analysis and visualization techniques. The course covers topics such as data collection, data analysis, and data presentation, which are all commonly used by Epidemiologists in their daily work.
See salaries and explore the career path for Epidemiologist
Biostatistician
A Biostatistician applies statistical methods to medical research. This course may be useful for Biostatisticians who want to learn more about data analysis and visualization techniques. The course covers topics such as clinical trials, data analysis, and data presentation, which are all commonly used by Biostatisticians in their daily work.
See salaries and explore the career path for Biostatistician
Economist
An Economist studies the production, distribution, and consumption of goods and services. This course may be useful for Economists who want to learn more about data analysis and visualization techniques. The course covers topics such as econometrics, data analysis, and data presentation, which are all commonly used by Economists in their daily work.
See salaries and explore the career path for Economist
Sociologist
A Sociologist studies human society and social behavior. This course may be useful for Sociologists who want to learn more about data analysis and visualization techniques. The course covers topics such as social research, data analysis, and data presentation, which are all commonly used by Sociologists in their daily work.
See salaries and explore the career path for Sociologist
Psychologist
A Psychologist studies the mind and behavior. This course may be useful for Psychologists who want to learn more about data analysis and visualization techniques. The course covers topics such as psychological research, data analysis, and data presentation, which are all commonly used by Psychologists in their daily work.
See salaries and explore the career path for Psychologist

Reading list

We've selected nine 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 Data Analysis and Visualization with Python.
Cover image
Python Data Science Handbook
Save
Provides a comprehensive guide to data visualization with Python and Matplotlib, a popular Python library for data visualization. It is particularly useful for those who want to learn how to create high-quality data visualizations.
Python Data Science Handbook: Essential Tools for...
Paperback
$$$
Cover image
Python for Data Analysis
Save
Provides a comprehensive guide to data analysis with Python, including data manipulation, analysis, and visualization. It is particularly useful for those who want to learn the fundamentals of data analysis with Python.
Python for Data Analysis
Paperback
Check
Python for Data Analysis
Kindle Edition
Check
Cover image
Machine Learning Q and AI
Save
Provides a comprehensive overview of machine learning with Python, including supervised learning, unsupervised learning, and deep learning. It is particularly useful for those who want to learn the fundamentals of machine learning with Python.
Machine Learning Q and AI: 30 Essential Questions...
Paperback
$$
Machine Learning Q and AI: 30 Essential Questions...
Kindle Edition
$$
Cover image
Natural Language Processing with Python
Save
Provides a comprehensive overview of natural language processing with Python, including text preprocessing, text classification, and text generation. It is particularly useful for those who want to learn the fundamentals of natural language processing with Python.
Natural Language Processing with Python: Analyzing...
Paperback
$$$
Natural Language Processing with Python: Analyzing...
Kindle Edition
$$
Cover image
Deep Learning with Python, Second Edition
Save
Provides a comprehensive overview of deep learning with Python, including convolutional neural networks, recurrent neural networks, and generative adversarial networks. It is particularly useful for those who want to learn the fundamentals of deep learning with Python.
Deep Learning with Python, Second Edition
Paperback
$$
Deep Learning with Python, Second Edition
Kindle Edition
$$
Financial Theory with Python
Save
Provides a comprehensive overview of Python for finance, including financial data analysis, financial modeling, and financial risk management. It is particularly useful for those who want to learn the fundamentals of finance with Python.
Financial Theory with Python: A Gentle Introduction
Paperback
$$
Cover image
Flask Web Development
Save
Provides a comprehensive overview of Python for web development, including web frameworks, web servers, and web security. It is particularly useful for those who want to learn the fundamentals of web development with Python.
Flask Web Development
Paperback
Check
Flask Web Development
Kindle Edition
Check
Cover image
Think Python
Save
Provides a comprehensive overview of Python for software development, including software design, software testing, and software deployment. It is particularly useful for those who want to learn the fundamentals of software development with Python.
Think Python
Kindle Edition
$$
Think Python: How to Think Like a Computer Scientist
Paperback
$$
Think Bayes: Bayesian Statistics in Python...
Paperback
$$
Think DSP: Digital Signal Processing in Python
Paperback
$$
Python for Software Design: How to Think Like a...
Kindle Edition
$$
Think Python
Paperback
$$$
(Deutsch) Think Python: Systematisch programmieren lernen mit...
Kindle Edition
$$
(العربية) Think python: Arabic version (Arabic Edition)
Kindle Edition
$
Think Bayes: Bayesian Statistics in Python
Paperback
$$
Learning With Python: How To Think Like A Computer...
Paperback
$$
Cover image
Working with Network Data
Save
Provides a comprehensive overview of Python for big data, including data storage, data processing, and data analysis. It is particularly useful for those who want to learn the fundamentals of big data with Python.
Working with Network Data
Paperback
Check
Working with Network Data
Kindle Edition
Check

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Course image
Effort
16 hours to complete
Level
Introductory
Via
Coursera
Institution
Arizona State University
Instructors
Adwith Malpe
Steven Osburn
Language
English
This course belongs to a collection called Python: A Guided Journey from Introduction to Application. It's comprised of three courses:
  1. Data Analysis and Visualization with Python (viewing)
  2. Introduction to Machine Learning with Python
  3. Object-Oriented Programming and GUI with Python
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Provides a solid foundation in programming concepts and data manipulation for novice learners
Taught by instructors with expertise in their field, ensuring high-quality content
Students will learn essential data analysis skills using industry-standard libraries and tools
Covers a wide range of data structures, providing a comprehensive understanding of data organization
Introduces exception handling for managing errors and ensuring code robustness
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