Data visualization is an integral part of data analysis and presentation. This course will introduce you to creating interesting visualizations of different types of data, ranging from simple univariate and bivariate numerical and categorical data, to more complex multi-variable data. During this course, you will learn to use simple scatter, box, line plots, etc. as well as interactive graphs and maps. Most importantly, the course will teach you the ideal visualization tool to use in different contexts. The course will use the powerful graphic tools of the R programming language.
Manager in L&T financial services
A diligent data scientist, silent visualizer and an enthusiastic programmer with 5+ years of experience in building machine learning models data processing and scripting in different programming languages including R and Python. Pravesh loves to analyze data using different models to furnish valuable insights.
Scatter plots, lines, steps, box plots, adding parameters to the basic plot function- creating legends, adding colors, grid lines, viewing multiple graphs in a single pane, etc.
Bar plots, histograms, pie charts, quintiles, Percentiles, Q-Q plots, function curves
Basic line graphs, scatters, regression lines, balloon plots, etc. with ggplot2
Bar plots, correlation matrix, functions, network graphs
Heat maps, 3-dimensional and animated graphics
Chloreopath maps and creating maps from a shape file
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