Advanced Visualizations & Dashboards: Visualization Using R

Data Visualization
  • 11 Videos | 39m 11s
  • Includes Assessment
  • Earns a Badge
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Discover how to build advanced charts by using Python and Jupyter Notebook for data science in this course, which explores R and ggplot2 visualization capabilities and how to build charts and graphs with these tools. Key concepts in this course include different types of charts that can be implemented and their relevance in data visualization; how to create a stacked bar plot; how to create Matplotlib animations; and how to use NumPy and Plotly to create interactive 3D plots in Jupyter Notebook. Learners are shown the graphical capabilities of R from the perspective of data visualization; how to build heat maps and scatter plots using R; and how to implement correlogram and build area charts using R. Next, you will explore ggplot2 capabilities from the perspective of data visualization; learn how to build and customize graphs by using ggplot2 in R; and how to create heat maps, a representation of data in form of a map or diagram. Finally, learn to create scatter plots and create area charts with R.

WHAT YOU WILL LEARN

  • list the different types of charts that can be implemented and their relevance in data visualization
    demonstrate how to create a stacked bar plot
    create Matplotlib animations
    use NumPy and Plotly to create interactive 3D plots in Jupyter Notebook
    list graphical capabilities of R from the perspective of data visualization
  • build heat maps and scatter plots using R
    implement correlogram and build area charts using R
    recognize ggplot2 capabilities from the perspective of data visualization
    build and customize graphs using ggplot2 in R
    create heat maps using R, create scatter plots using R, and create area charts using R

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 40s
    UP NEXT
  • Playable
    2. 
    Chart Types
    4m 24s
  • Locked
    3. 
    Stacked Bar Plot
    1m 59s
  • Locked
    4. 
    Animate Plots with Matplotlib
    4m 45s
  • Locked
    5. 
    Plotting in Jupyter Notebook
    2m 47s
  • Locked
    6. 
    Graphics in R
    2m 44s
  • Locked
    7. 
    Heat Map and Scatter Plot in R
    2m 56s
  • Locked
    8. 
    Correlogram and Area Chart in R
    4m 38s
  • Locked
    9. 
    ggplot2 Capabilities
    3m 13s
  • Locked
    10. 
    Customize ggplot2 Graphs
    3m 41s
  • Locked
    11. 
    Exercise: Creating Heat Maps and Scatter Plots
    1m 54s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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