Interactive Data Visualization with rbokeh
Learn rbokeh: a visualization library for interactive web-based plots.
- 4 hours
- 12 Videos
- 47 Exercises
- 784 Participants
- 4,000 XP
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Course Description
Data visualization is an integral part of the data analysis process. This course will get you introduced to rbokeh: a visualization library for interactive web-based plots. You will learn how to use rbokeh layers and options to create effective visualizations that carry your message and emphasize your ideas. We will focus on the two main pieces of data visualization: wrangling data in the appropriate format as well as employing the appropriate visualization tools, charts and options from rbokeh.
Learn rbokeh: a visualization library for interactive web-based plots.
Course Outline
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1
rbokeh Introduction
FreeIn this chapter we get introduced to rbokeh layers. You will learn how to specify data and arguments to create the desired plot and how to combine multiple layers in one figure.
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Data Manipulation for Visualization and More rbokeh Layers
In this chapter, you will learn how to put your data in the right format to fit the desired figure. And how to transform between the wide and long formats. You will also see how to combine normal layers with regression lines. In addition you will learn how to customize the interaction tools that appear with each figure.
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rbokeh Aesthetic Attributes and Figure Options
In this chapter you will learn how to customize your rbokeh figures using aesthetic attributes and figure options. You will see how aesthetic attributes such as color, transparancy and shape can serve a purpose and add more info to your visualizations. In addition, you will learn how to activate the tooltip and specify the hover info in your figures.
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Grid Plots and Maps
In this chapter you will learn how to combine multiple plots in one layout using grid plots. In addition, you will learn how to create interactive maps.
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1
rbokeh Introduction
FreeIn this chapter we get introduced to rbokeh layers. You will learn how to specify data and arguments to create the desired plot and how to combine multiple layers in one figure.
-
rbokeh Aesthetic Attributes and Figure Options
In this chapter you will learn how to customize your rbokeh figures using aesthetic attributes and figure options. You will see how aesthetic attributes such as color, transparancy and shape can serve a purpose and add more info to your visualizations. In addition, you will learn how to activate the tooltip and specify the hover info in your figures.
-
Data Manipulation for Visualization and More rbokeh Layers
In this chapter, you will learn how to put your data in the right format to fit the desired figure. And how to transform between the wide and long formats. You will also see how to combine normal layers with regression lines. In addition you will learn how to customize the interaction tools that appear with each figure.
-
Grid Plots and Maps
In this chapter you will learn how to combine multiple plots in one layout using grid plots. In addition, you will learn how to create interactive maps.
Omayma Said
Data Scientist
Omayma is a Data Scientist who likes to engage with data, challenge assumptions and help others make data-informed decisions. She worked on developing algorithms and analyzing users data at a tech company providing a marketplace for jobs and career services. Prior to that she obtained her Master’s degree in “Systems Engineering and Engineering Management” with a focus on electronics where she worked with wearable sensors data. She writes about data science and R in her blog onceupondata.com.
See MoreCollaborators
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David Campos
-
Shon Inouye
Prerequisites
Course Instructor
Omayma Said
Data Scientist
Omayma is a Data Scientist who likes to engage with data, challenge assumptions and help others make data-informed decisions. She worked on developing algorithms and analyzing users data at a tech company providing a marketplace for jobs and career services. Prior to that she obtained her Master’s degree in “Systems Engineering and Engineering Management” with a focus on electronics where she worked with wearable sensors data. She writes about data science and R in her blog onceupondata.com.
See MoreCollaborator(s)
-
David Campos
-
Shon Inouye
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