Welcome to this 1 hour long guided project on Data Visualization using Plotly. Plotly is a python graphing library which is used to make interactive, publication-quality graphs. It allows users to import, copy and paste, or stream data to be analyzed and visualized.
(39 reviews)
Recommended experience
What you'll learn
Basics of Exploratory Data Analysis and Plotly and install it on your colab noteboo
Learn how to import necessary libraries and visualize data through simple as well as multi line plots with different markers using plotly
Visualize data through barplots, Area Chart and Stacked Area Chart using plotly
Skills you'll practice
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About this Guided Project
Learn step-by-step
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Learner Task 1 : You will be able to learn the basics of Exploratory Data Analysis, Plotly and install it on your colab notebook
Learner Task 2 : You will be able to learn how to import necessary libraries and visualize data through simple as well as multi line plots with different markers using plotly
Learner Task 3 : You will be able to visualize data through barplots, Area Chart and Stacked Area Chart using plotly
Learner Task 4 : You will be able to visualize data through Pie Chart and Multilevel Piechart using plotly
Learner Task 5 : You will be able to visualize data through scatter plot using plotly
Recommended experience
Some elementary knowledge of Python and Pandas
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Instructor
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How you'll learn
Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
Expert guidance
Follow along with pre-recorded videos from experts using a unique side-by-side interface.
No downloads or installation required
Access the tools and resources you need in a pre-configured cloud workspace.
Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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Reviewed on Apr 13, 2022
Hello! I recommend downloading the videos because you have limited time when doing this project. I learned a lot by watching them over & over and running the code in Jupyter notebook.
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