This course was created by Madecraft. We are pleased to host this content in our library.
- Use a Jupyter notebook to execute a series of commands.
- Describe common commands to load and export data.
- Explain pandas usage basics.
- Modify a DataFrame using common data methods.
- Create simple plots using Matplotlib.
- Apply advanced techniques to produce complex plots.
Skill Level Intermediate
- The amount of data being generated is enormous. Today, most companies are looking to use their data to create efficiencies, go after new markets, and build new products. But, it's one thing to capture data, if you want to communicate and understand your data, you need to use tools to help you create data visualizations. A great way to do this is using Python. Python has a powerful data science ecosystem with libraries that can help you create visualizations that are compelling and ready for publication. My name is Michael Galarnyk, I'm a data scientist, a Python instructor, and blogger.
In this course, I want to show you how to build compelling data visualizations using Python. I'll give you an overview of the tools available, then I'll share how to manipulate your data using Pandas, and how to take that data and create visualizations using Matplotlib. I'll also show you how to create boxplots, heat maps, histograms, and more. By the end of this course, you'll feel confident and ready to go build your own powerful visualizations using Python. So, if you're ready to dive in, let's go.
Data Visualization in R with ggplot2with Mike Chapple2h 27m Intermediate
1. Data Visualization Tools
4. Advanced Plotting
Next steps1m 10s
- Mark as unwatched
- Mark all as unwatched
Are you sure you want to mark all the videos in this course as unwatched?
This will not affect your course history, your reports, or your certificates of completion for this course.Cancel
Take notes with your new membership!
Type in the entry box, then click Enter to save your note.
1:30Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.