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Jason Browning, Ph.D.
This course will introduce you to basic data plotting functions in Python that will help you to create clear and dynamic data visualizations to communicate analysis and findings with various audiences.
When performing data analysis, the ability to visualize your data is extremely important for both the analysis process itself as well as for sharing your results with others.
In this course, Plotting Data with Pandas, you’ll learn how to use basic plotting functions in Python to create data visualizations.
Read more
This course will introduce you to basic data plotting functions in Python that will help you to create clear and dynamic data visualizations to communicate analysis and findings with various audiences.
When performing data analysis, the ability to visualize your data is extremely important for both the analysis process itself as well as for sharing your results with others. In this course, Plotting Data with Pandas, you’ll learn how to use basic plotting functions in Python to create data visualizations.
Read more
This course will introduce you to basic data plotting functions in Python that will help you to create clear and dynamic data visualizations to communicate analysis and findings with various audiences.
When performing data analysis, the ability to visualize your data is extremely important for both the analysis process itself as well as for sharing your results with others. In this course, Plotting Data with Pandas, you’ll learn how to use basic plotting functions in Python to create data visualizations.
First, you’ll be introduced to Matplotlib, a built-in Python plotting library, and some of its fundamental features.
Next, you’ll discover methods about preparing your data for visualization and how to use it to create basic plots.
Finally, you’ll explore how to use Python to customize your visualizations.
When you’re finished with this course, you’ll have the knowledge needed to prepare effective data visualizations that will allow you to clearly communicate results and findings from your data analysis work with a wide variety of audiences.
Register for this course and see more details by visiting:
OpenCourser.com/course/oxzq9a/plotting
What's inside
Syllabus
Course Overview
Introducing the Plotting Ecosystem
Plotting Using Pandas
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Introduces learners to basic data-plotting functions in Python, a fundamental skill many industries and roles expect
Provides tools that enable learners to effectively communicate findings with various audiences through visual representations
Leverages Matplotlib, a well-established and widely used Python library, which increases industry relevance and alignment
Instructor Jason Browning, Ph.D., brings expertise in the subject matter to the course, enhancing its credibility
Save this course
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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 Plotting Data with Pandas with these
activities:
Data Visualization Mentorship
Show steps
Connecting with a mentor can provide invaluable guidance, feedback, and support on your data visualization journey.
Browse courses on
Mentorship
Show steps
-
Identify potential mentors in the field of data visualization, such as experienced professionals or researchers.
-
Reach out and schedule a meeting to explore mentorship opportunities.
Data Visualization Resources
Show steps
Gathering a collection of resources will aid your process of learning and retaining data visualization techniques.
Browse courses on
Python Libraries
Show steps
-
Compile a list of Python libraries for data visualization (e.g., Matplotlib, Seaborn, Plotly).
-
Collect online resources, such as tutorials, articles, and documentation, on data visualization using Python.
Interactive Data Visualization
Show steps
Seeking out additional tutorials will further supplement your understanding of data visualization concepts and techniques.
Show steps
-
Find online tutorials or courses on interactive data visualization using Python.
-
Follow the tutorials and practice the techniques.
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Data Visualization Peer Group
Show steps
Participating in a study group will facilitate the exchange of knowledge and perspectives with your peers, promoting a deeper understanding of data visualization.
Show steps
-
Form a study group with other course participants.
-
Meet regularly to discuss the course material and work on projects together.
Practice using Matplotlib functions
Show steps
Reinforce the practical application of Matplotlib's functions for data visualization.
Browse courses on
Matplotlib
Show steps
-
Use Matplotlib to create a line plot and scatter plot.
-
Experiment with different plot styles and colors.
Plotting Basics Part 1
Show steps
Practicing basic plotting functions will help you refine and strengthen your understanding of data visualization techniques.
Browse courses on
Plotting
Show steps
-
Understand Matplotlib fundamentals, such as figure and axes objects.
-
Practice creating basic plots (scatter, line, bar).
Explore additional data visualization libraries
Show steps
Expand your skillset by delving into additional data visualization libraries that complement Pandas.
Browse courses on
Data Visualization
Show steps
-
Research and select a relevant library based on project requirements.
-
Review documentation and tutorials to understand its capabilities.
-
Apply the library in a practical setting to reinforce learning.
Plotting Basics Part 2
Show steps
Refining your skills in advanced plotting techniques will enable you to generate more sophisticated and impactful data visualizations.
Browse courses on
Python
Show steps
-
Explore advanced plot types, such as histograms, box plots, and subplots.
-
Customize plots by setting colors, markers, labels, and titles.
Create interactive data visualizations
Show steps
Challenge yourself by implementing a practical project that demonstrates your proficiency in data visualization.
Browse courses on
Data Visualization
Show steps
-
Choose a dataset and identify key insights.
-
Design and develop interactive visualizations, such as dashboards or charts.
-
Present your findings effectively.
Data Visualization Project
Show steps
Completing a data visualization project will provide you with hands-on experience in applying your skills to real-world scenarios.
Browse courses on
Data Analysis
Show steps
-
Choose a dataset and define a research question.
-
Explore and clean the data.
-
Create visualizations to answer the research question.
-
Present your findings.
Data Visualization Mentorship
Show steps
Connecting with a mentor can provide invaluable guidance, feedback, and support on your data visualization journey.
Browse courses on
Mentorship
Show steps
Show steps
Show steps
- Identify potential mentors in the field of data visualization, such as experienced professionals or researchers.
- Reach out and schedule a meeting to explore mentorship opportunities.
Data Visualization Resources
Show steps
Gathering a collection of resources will aid your process of learning and retaining data visualization techniques.
Browse courses on
Python Libraries
Show steps
Show steps
Show steps
- Compile a list of Python libraries for data visualization (e.g., Matplotlib, Seaborn, Plotly).
- Collect online resources, such as tutorials, articles, and documentation, on data visualization using Python.
Interactive Data Visualization
Show steps
Seeking out additional tutorials will further supplement your understanding of data visualization concepts and techniques.
Show steps
Show steps
Show steps
- Find online tutorials or courses on interactive data visualization using Python.
- Follow the tutorials and practice the techniques.
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Data Visualization Peer Group
Show steps
Participating in a study group will facilitate the exchange of knowledge and perspectives with your peers, promoting a deeper understanding of data visualization.
Show steps
Show steps
Show steps
- Form a study group with other course participants.
- Meet regularly to discuss the course material and work on projects together.
Practice using Matplotlib functions
Show steps
Reinforce the practical application of Matplotlib's functions for data visualization.
Browse courses on
Matplotlib
Show steps
Show steps
Show steps
- Use Matplotlib to create a line plot and scatter plot.
- Experiment with different plot styles and colors.
Plotting Basics Part 1
Show steps
Practicing basic plotting functions will help you refine and strengthen your understanding of data visualization techniques.
Browse courses on
Plotting
Show steps
Show steps
Show steps
- Understand Matplotlib fundamentals, such as figure and axes objects.
- Practice creating basic plots (scatter, line, bar).
Explore additional data visualization libraries
Show steps
Expand your skillset by delving into additional data visualization libraries that complement Pandas.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Research and select a relevant library based on project requirements.
- Review documentation and tutorials to understand its capabilities.
- Apply the library in a practical setting to reinforce learning.
Plotting Basics Part 2
Show steps
Refining your skills in advanced plotting techniques will enable you to generate more sophisticated and impactful data visualizations.
Browse courses on
Python
Show steps
Show steps
Show steps
- Explore advanced plot types, such as histograms, box plots, and subplots.
- Customize plots by setting colors, markers, labels, and titles.
Create interactive data visualizations
Show steps
Challenge yourself by implementing a practical project that demonstrates your proficiency in data visualization.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a dataset and identify key insights.
- Design and develop interactive visualizations, such as dashboards or charts.
- Present your findings effectively.
Data Visualization Project
Show steps
Completing a data visualization project will provide you with hands-on experience in applying your skills to real-world scenarios.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Choose a dataset and define a research question.
- Explore and clean the data.
- Create visualizations to answer the research question.
- Present your findings.
Career center
Learners who complete Plotting Data with Pandas will develop knowledge and skills
that may be useful to these careers:
Data Visualization Engineer
Data Visualization Engineer
Data Visualization Engineers specialize in creating interactive and visually appealing data visualizations. This course in Plotting Data with Pandas can provide a strong foundation for Data Visualization Engineers by teaching them the fundamentals of data visualization, including data preparation, basic plotting techniques, and customization of visualizations. The course will enable them to create clear and effective data visualizations that communicate insights effectively.
Data Scientist
Data Scientist
Data Scientists analyze and interpret large amounts of data to extract meaningful insights and make informed decisions. This course in Plotting Data with Pandas can help build a foundation for Data Scientists by providing them with the skills to visualize and communicate their findings effectively. The course covers topics such as data preparation, basic plotting techniques, and customization of visualizations, which are essential for presenting data insights in a clear and compelling manner.
Data Analyst
Data Analyst
Data Analysts play a crucial role in transforming raw data into valuable insights for businesses. This course in Plotting Data with Pandas can be beneficial for Data Analysts as it provides them with hands-on experience in data visualization, which is a key skill for communicating analysis and findings to stakeholders. The course covers topics such as data preparation, basic plotting techniques, and customization of visualizations, enabling Data Analysts to create informative and visually appealing data presentations.
Statistician
Statistician
Statisticians use mathematical and statistical techniques to analyze and interpret data. This course in Plotting Data with Pandas can be beneficial for Statisticians as it provides them with hands-on experience in data visualization, which is a key skill for communicating complex statistical concepts and findings to a wider audience. The course covers topics such as data preparation, basic plotting techniques, and customization of visualizations, enabling Statisticians to create visually appealing and informative data presentations.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. This course in Plotting Data with Pandas can be beneficial for Quantitative Analysts as it provides them with hands-on experience in data visualization, which is a key skill for communicating complex financial concepts and findings to clients and stakeholders. The course covers topics such as data preparation, basic plotting techniques, and customization of visualizations, enabling Quantitative Analysts to create visually appealing and informative data presentations.
User Experience (UX) Designer
User Experience (UX) Designer
User Experience (UX) Designers focus on creating user-friendly and engaging digital experiences. This course in Plotting Data with Pandas can be useful for UX Designers as it provides them with the skills to visualize and communicate data effectively. The course covers topics such as data preparation, basic plotting techniques, and customization of visualizations, enabling UX Designers to create visually appealing and informative data presentations that support user research and design decisions.
Financial Analyst
Financial Analyst
Financial Analysts use data to analyze financial performance and make investment recommendations. This course in Plotting Data with Pandas can be beneficial for Financial Analysts as it provides them with the skills to visualize and communicate financial data effectively. The course covers topics such as data preparation, basic plotting techniques, and customization of visualizations, enabling Financial Analysts to create clear and compelling data presentations for clients and stakeholders.
Business Analyst
Business Analyst
Business Analysts use data to identify and solve business problems. This course in Plotting Data with Pandas can be useful for Business Analysts as it provides them with the skills to visualize and communicate data insights effectively. The course covers topics such as data preparation, basic plotting techniques, and customization of visualizations, which are essential for presenting data-driven recommendations and solutions to business stakeholders.
Consultant
Consultant
Consultants provide expert advice and support to businesses. This course in Plotting Data with Pandas can be useful for Consultants as it provides them with the skills to visualize and communicate data effectively. The course covers topics such as data preparation, basic plotting techniques, and customization of visualizations, enabling Consultants to create visually appealing and informative data presentations that support their recommendations and insights.
Product Manager
Product Manager
Product Managers are responsible for managing the development and launch of products. This course in Plotting Data with Pandas can be beneficial for Product Managers as it provides them with the skills to visualize and communicate data effectively. The course covers topics such as data preparation, basic plotting techniques, and customization of visualizations, enabling Product Managers to create clear and compelling data presentations for stakeholders and track product performance.
Market Researcher
Market Researcher
Market Researchers gather and analyze data to understand consumer behavior and market trends. This course in Plotting Data with Pandas can be beneficial for Market Researchers as it provides them with the skills to visualize and communicate research findings effectively. The course covers topics such as data preparation, basic plotting techniques, and customization of visualizations, enabling Market Researchers to create visually appealing and informative data presentations for clients and stakeholders.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve complex business problems. While data visualization is not a primary responsibility of Operations Research Analysts, this course may be useful for those who are involved in data exploration and analysis as part of their role. The course covers topics such as data preparation, basic plotting techniques, and customization of visualizations, which can enhance their understanding of data and improve communication with stakeholders.
Data Engineer
Data Engineer
Data Engineers design and build systems for data storage, processing, and analysis. While data visualization is not a primary responsibility of Data Engineers, this course may be useful for those who are involved in data exploration and analysis as part of their role. The course covers topics such as data preparation, basic plotting techniques, and customization of visualizations, which can enhance their understanding of data and improve communication with stakeholders.
Actuary
Actuary
Actuaries analyze and interpret data to assess risk and financial implications. While data visualization is not a primary responsibility of Actuaries, this course may be useful for those who are involved in data exploration and analysis as part of their role. The course covers topics such as data preparation, basic plotting techniques, and customization of visualizations, which can enhance their understanding of data and improve communication with stakeholders.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. While data visualization is not a primary responsibility of Software Engineers, this course may be useful for those who work on data-driven software applications. The course covers topics such as data preparation, basic plotting techniques, and customization of visualizations, which can enhance their understanding of data and improve communication with stakeholders.
For more career information including salaries, visit:
OpenCourser.com/course/oxzq9a/plotting
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
Plotting Data with Pandas.
Provides a comprehensive overview of the Python data science ecosystem, including Pandas. It covers topics such as data manipulation, data analysis, machine learning, and visualization.
Provides a practical guide to creating effective data visualizations. It covers topics such as choosing the right chart type, designing for readability, and avoiding common pitfalls.
Save
Provides an overview of the history, principles, and best practices of data visualization. It covers topics such as visual perception, color theory, and typography.
Save
Provides an introduction to data visualization. It covers topics such as choosing the right chart type, designing for readability, and avoiding common pitfalls.
Provides an introduction to data visualization. It covers topics such as the history of data visualization, the principles of visual perception, and the different types of data visualization.
Provides an introduction to Python for data analysis. It covers topics such as data structures, data manipulation, and visualization.
Save
Provides a practical guide to using Pandas for data analysis. It covers topics such as data cleaning, transformation, and visualization.
Save
Provides a practical guide to using Pandas effectively. It covers topics such as data cleaning, transformation, and visualization.
Save
Provides an overview of Python for data science. It covers topics such as data structures, data manipulation, and machine learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/oxzq9a/plotting
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Time
25 hours
Level
Introductory
Via
Pluralsight
Instructor
Jason Browning, Ph.D.
Language
English
Good to know
Introduces learners to basic data-plotting functions in Python, a fundamental skill many industries and roles expect
Provides tools that enable learners to effectively communicate findings with various audiences through visual representations
Leverages Matplotlib, a well-established and widely used Python library, which increases industry relevance and alignment
Instructor Jason Browning, Ph.D., brings expertise in the subject matter to the course, enhancing its credibility
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