Python & Matplotlib: Creating Box Plots, Scatter Plots, Heatmaps, & Pie Charts
Matplotlib 3.3.3 | Intermediate
- 11 videos | 1h 28m 44s
- Includes Assessment
- Earns a Badge
Matplotlib can be used to create box-and-whisker plots to display statistics. These dense visualizations pack much information into a compact form, including the median, 25th and 75th percentiles, interquartile range, and outliers. In this course, you'll learn how to work with all aspects of box-and-whisker plots, such as the use of confidence-interval notches, mean markers, and fill color. You'll also build grouped box-and-whisker plots. Next, you'll create scatter plots and heatmaps, powerful tools in exploratory data analysis. You'll build standard scatter plots before customizing various aspects of their appearance. You'll then examine the ideal uses of scatter plots and correlation heatmaps. You'll move on to visualizing composition, first using pie charts, building charts that explode out specific slices. Lastly, you'll build treemaps to visualize data with multiple levels of hierarchy.
WHAT YOU WILL LEARN
discover the key concepts covered in this courseuse Matplotlib to create box-and-whisker plots to display various statistics, such as the median, upper and lower quartiles and outliersuse Matplotlib to create filled box-and-whisker plotsuse Matplotlib to visualize the relationship between two continuous variables using scatter plotsuse Matplotlib to use correlation heatmaps to visually represent covariate relationshipsuse Matplotlib to create a heatmap that visualizes correlations and has labels for each correlation
use Matplotlib to visualize how individual proportions add up to a whole using pie chartsuse Matplotlib to create exploded pie charts and treemapsillustrate how autocorrelation and cross-correlation can be used to identify recurring patterns in data through Matplotlibuse Matplotlib to visualize compositions over a period of time using area charts and changes over time using stem plotssummarize the key concepts covered in this course
IN THIS COURSE
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Course Infogram: Advanced Features