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.
Advanced Visualizations & Dashboards: Visualization Using R