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Interactive Data Visualization with rbokeh

Learn rbokeh: a visualization library for interactive web-based plots.

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4 Hours12 Videos47 Exercises3,461 Learners4000 XPInteractive Data Visualization Track

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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.

  1. 1

    rbokeh Introduction

    Free

    In 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.

    Play Chapter Now
    Getting started with rbokeh
    50 xp
    Hello rbokeh!
    100 xp
    Tidyverse Refresher (Filter)
    100 xp
    Tidyverse Refresher (Mutate)
    100 xp
    Constructing rbokeh layers (Part 1)
    50 xp
    Specifying Data in rbokeh Layers (Part 1)
    100 xp
    Specifying Data in rbokeh Layers (Part 2)
    100 xp
    Specifying Data in rbokeh Layers 3
    100 xp
    Constructing rbokeh layers (Part 2)
    50 xp
    One-Layer Plot (Scatter Plot)
    100 xp
    Multi-Layer Plot 1 (Scatter + Line Plot)
    100 xp
    Multi-Layer Plot 2 (Scatter + Line Plot)
    100 xp
  2. 2

    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.

    Play Chapter Now
    Plot and mapped attributes (Part 1)
    50 xp
    Line and Fill Color 1
    50 xp
    Line and Fill Color 2
    100 xp
    Color Palette
    100 xp
    Plot and mapped attributes (Part 2)
    50 xp
    Size & Alpha (Scatter Plot) 1
    100 xp
    Size & Alpha (Scatter Plot) 2
    100 xp
    Line Width
    100 xp
    Hover info and figure options
    50 xp
    Hover Info (Part 1)
    50 xp
    Hover Info (Part 2)
    100 xp
    Figure Options
    100 xp
  3. 3

    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.

    Play Chapter Now
    Data formats
    50 xp
    Wide and Long Data 1
    100 xp
    Wide and long Data 2
    100 xp
    Wide and Long Data 3
    100 xp
    More rbokeh layers
    50 xp
    Scatter Plot + Regression Line (Reshaping Data)
    100 xp
    Scatter Plot + Regression Line (Scatter Plot)
    100 xp
    Scatter Plot + Regression Line (Regression Line)
    100 xp
    Interaction tools
    50 xp
    Toolbar Location
    100 xp
    Interaction Tools (Hide/View)
    100 xp
  4. 4

    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.

    Play Chapter Now
    rbokeh grid plots
    50 xp
    Grid Plots
    100 xp
    Grid Plots (Axes)
    100 xp
    Grid Plot (Layout)
    100 xp
    Facets with grid plots
    50 xp
    Facets 1
    100 xp
    Facets 2
    100 xp
    Facets 3
    100 xp
    rbokeh maps
    50 xp
    Initializing Maps
    100 xp
    Adding Points Layer to Maps
    100 xp
    Multiple Maps in a Grid Plot
    100 xp

In the following tracks

Interactive Data Visualization

Datasets

Human Development Index datasetCorruption Perception Index datasetTuberculosis Cases datasetNew York Citi Bike Trips dataset

Collaborators

dcamposlizDavid CamposshoninouyeShon Inouye

Prerequisites

Introduction to the Tidyverse
Omayma Said Headshot

Omayma Said

Data Scientist

Omayma Said is currently a Data Scientist at Basharsoft. She enjoys working in data-informed environments where good data analysis can drive decisions, support building products, create a value, help in improving the quality of research and more. She has a background in electronics engineering, and holds a master's degree in Systems Engineering and Engineering Management. Her professional experience includes IT management, telecommunications and R&D in research centers, startups and multi-national organizations such as Vodafone, Orange Business Services, Procter & Gamble.
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