Advanced Visualizations & Dashboards: Visualization Using R

Data Visualization    |    Intermediate
  • 11 videos | 34m 41s
  • Includes Assessment
  • Earns a Badge
Rating 4.3 of 12 users Rating 4.3 of 12 users (12)
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

  • 1m 40s
  • 4m 24s
    After completing this video, you will be able to list the different types of charts that can be used and their relevance in data visualization. FREE ACCESS
  • Locked
    3.  Stacked Bar Plot
    1m 59s
    In this video, you will learn how to create a stacked bar graph. FREE ACCESS
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    4.  Animate Plots with Matplotlib
    4m 45s
    This video will teach you how to create Matplotlib animations. FREE ACCESS
  • Locked
    5.  Plotting in Jupyter Notebook
    2m 47s
    During this video, you will learn how to use NumPy and Plotly to create interactive 3D plots in a Jupyter Notebook. FREE ACCESS
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    6.  Graphics in R
    2m 44s
    After completing this video, you will be able to list R's graphical capabilities for data visualization. FREE ACCESS
  • Locked
    7.  Heat Map and Scatter Plot in R
    2m 56s
    During this video, you will learn how to build heat maps and scatter plots using R. FREE ACCESS
  • Locked
    8.  Correlogram and Area Chart in R
    4m 38s
    During this video, you will learn how to implement a correlogram and build area charts using R. FREE ACCESS
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    9.  ggplot2 Capabilities
    3m 13s
    Upon completion of this video, you will be able to recognize the capabilities of ggplot2 from the perspective of data visualization. FREE ACCESS
  • Locked
    10.  Customize ggplot2 Graphs
    3m 41s
    During this video, you will learn how to build and customize graphs using ggplot2 in R. FREE ACCESS
  • Locked
    11.  Exercise: Creating Heat Maps and Scatter Plots
    1m 54s
    In this video, find out how to create heat maps, scatter plots, and area charts using R. FREE ACCESS

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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