Building Data Visualization Tools

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Description

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About this course: The data science revolution has produced reams of new data from a wide variety of new sources. These new datasets are being used to answer new questions in way never before conceived. Visualization remains one of the most powerful ways draw conclusions from data, but the influx of new data types requires the development of new visualization techniques and building blocks. This course provides you with the skills for creating those new visualization building blocks. We focus on the ggplot2 framework and describe how to use and extend the system to suit the specific needs of your organization or team. Upon completing this course, learners will be able to build the tools…

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When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: The data science revolution has produced reams of new data from a wide variety of new sources. These new datasets are being used to answer new questions in way never before conceived. Visualization remains one of the most powerful ways draw conclusions from data, but the influx of new data types requires the development of new visualization techniques and building blocks. This course provides you with the skills for creating those new visualization building blocks. We focus on the ggplot2 framework and describe how to use and extend the system to suit the specific needs of your organization or team. Upon completing this course, learners will be able to build the tools needed to visualize a wide variety of data types and will have the fundamentals needed to address new data types as they come about.

Created by:  Johns Hopkins University
  • Taught by:  Roger D. Peng, PhD, Associate Professor, Biostatistics

    Bloomberg School of Public Health
  • Taught by:  Brooke Anderson, Assistant Professor, Environmental & Radiological Health Sciences

    Colorado State University
Basic Info Course 4 of 5 in the Mastering Software Development in R Specialization Level Intermediate Commitment 4 weeks, 2 hours per week Language English How To Pass Pass all graded assignments to complete the course. User Ratings 4.0 stars Average User Rating 4.0See what learners said Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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Johns Hopkins University The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.

Syllabus


WEEK 1


Welcome to Building Data Visualization Tools
Before we get started, we'll take a quick overview of the course.


1 video, 2 readings expand


  1. Video: Welcome to Building Data Visualization Tools
  2. Reading: Textbook: Mastering Software Development in R
  3. Reading: Syllabus


Plotting with ggplot2
Now, we'll dive into creating and customizing ggplot2 plots.


13 readings expand


  1. Reading: Introduction
  2. Reading: Initializing a ggplot object
  3. Reading: Plot aesthetics
  4. Reading: Creating a basic ggplot plot
  5. Reading: Geoms
  6. Reading: Using multiple geoms
  7. Reading: Constant aesthetics
  8. Reading: Example plots
  9. Reading: Extensions of ggplot2
  10. Reading: Introduction
  11. Reading: Guidelines for good plots
  12. Reading: Scales and color
  13. Reading: To find out more

Graded: Plotting with ggplot2

WEEK 2


Mapping and interactive plots
Mapping is a critical part of many data visualizations. During this module, we'll teach you how to create simple and dynamic maps with ggplot2 and ggmap, how to overlay data, and how to create chloropleth maps of US counties.


9 readings expand


  1. Reading: Introduction
  2. Reading: Basics of Mapping
  3. Reading: ggmap, Google Maps API
  4. Reading: Mapping US counties and states
  5. Reading: advanced mapping– Spatial objects
  6. Reading: Where to find more on mapping with R
  7. Reading: Overview of htmlWidgets
  8. Reading: plotly package
  9. Reading: Creating your own widget

Graded: Mapping and interactive plots

WEEK 3


The grid Package
The grid package in R implements the primitive graphical functions that underly the ggplot2 plotting system. In this module, you'll learn how to work with grid to build graphics.


7 readings expand


  1. Reading: Introduction
  2. Reading: Overview of grid graphics
  3. Reading: Grobs
  4. Reading: Viewports
  5. Reading: Grid graphics coordinate systems
  6. Reading: The gridExtra package
  7. Reading: Where to find more about grid graphics

Graded: Basics of grid graphics

WEEK 4


Building New Graphical Elements
Building and modifying a theme in ggplot2 is a key feature of the ggplot2 package and system for building data graphics. In this final module, you'll learn to build a new theme and modifying existing themes with new features.


12 readings expand


  1. Reading: Introduction
  2. Reading: Why Build a New Theme?
  3. Reading: Default Theme
  4. Reading: Building a New Theme
  5. Reading: Summary
  6. Reading: Introduction
  7. Reading: Building a Geom
  8. Reading: Example: An Automatic Transparency Geom
  9. Reading: Building a Stat
  10. Reading: Example: Normal Confidence Intervals
  11. Reading: Combining Geoms and Stats
  12. Reading: Summary

Graded: Build a New Geom
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There are no frequently asked questions yet. Send an Email to info@springest.com