Rating 3.3 out of 5 (10 ratings in Udemy)
What you'll learn- Learn to create data visualizations layer by layer with ggplot2
- Learn how to customize the look and feel of plots in R with ggplot2
- Learn how to plot correlations, scatterplots, jitter plots, count charts, bubble plots, and histograms
- Learn to plot diverging bars, lollipop charts, dot plots, and area charts, and visualize deviations
- Visualize data distributions using various ggplot2 plots
- Visualize data composition using waffle …
Rating 3.3 out of 5 (10 ratings in Udemy)
What you'll learn- Learn to create data visualizations layer by layer with ggplot2
- Learn how to customize the look and feel of plots in R with ggplot2
- Learn how to plot correlations, scatterplots, jitter plots, count charts, bubble plots, and histograms
- Learn to plot diverging bars, lollipop charts, dot plots, and area charts, and visualize deviations
- Visualize data distributions using various ggplot2 plots
- Visualize data composition using waffle charts, pie charts, treemaps, and bar charts
- Learn to plot changes in data using time series, stacked area, heat map, and more
DescriptionYou already know the basics of Data Visualizations with R but this isn't enough. You want to be able to create advanced-level Data Visualizations that showcase insights from your datasets.
This course will provide you with a detailed exploration of the latest version of ggplot2, in a step-by-step and engaging manner. Through this course, you will master the advanced concepts of ggplot2 and will be able to tackle any Data Visualization project with ease and with increasing complexity.
By the end of the course, you will have honed your expertise and mastered data visualizations using the full potential of ggplot2.
About the Author
Harish Garg is a Co-Founder and Software professional with more than 18 years of Software Industry experience. He currently runs a software consultancy that specializes in Data Analytics and Data Science domain. He has been programming in Python for more than 12 years now and has been using Python for Data Analytics and Data science for 6 years. He has developed numerous courses in Data Science domain and has also published a book involving Data Science with Python, including Matplotlib.
