Aspire Pythonista to Python Master Python Master Track 2: Data Visualization for Web App Using Python
This course will introduce you to a breadth of charts available in Altair and how you can use them to get an all-round understanding of your data. The focus is to get you familiar with the wide variety of graphs that are available. You'll begin by visualizing a distribution of numeric values using box plots and violin charts, each of which has its own strengths and limitations when analyzing distributions. You'll then move on to bar charts to analyze numbers associated with categories in your data. While doing so, you will get to explore a variety of aggregate operations that are available in Altair in order to calculate a sum, mean, median, and so on. You'll then use line charts to visualize the changes in a particular value over a period of time and also its related visual - the area chart. Finally, you'll produce scatter plots to visualize the relationship between a pair of fields in your data. Throughout this course, you'll delve into a number of customizations which are available in Altair for each of the graphs which you plot.
| Objectives |
Python with Altair: Plotting Fundamental Graphs - discover the key concepts covered in this course
- generate a variety of box plots such as plain box plots, box plots with categorical color bars, and box plots with continuous color bars
- define violin plots such as basic violins, trellis violin plots, and violin plots with color scales
- produce basic bar charts such as bar charts with labels and bar charts with the bars sorted in an ascending or descending order
- enhance bar charts by adding rules representing the mean or median of a distribution, conditional formatting, and creating stacked bar charts
- visualize data using line charts and customize various aspects of the chart such as the interpolation and by adding rules to the chart
- perform various customizations on a line chart such as adding a range slider, visualizing multiple variables in a single chart, and adding a new axis for the second column
- recognize the use of area charts as an extension of line charts to sum up all the values in a data set and create an area chart with a gradient in the color of the chart
- create various customized area charts such as area charts with multiple categories, streamgraphs, and trellis area charts
- visualize data and identify the relationships between variables using scatter plots and create a scatter plot where the color of the data points represent a variable
- create various custom scatter plots such as scatter plots where the size of the points represent a variable, scatter plots binned into categories, scatter plots with hollow points, and scatter plots with text labels
- create a scatter plot that is linked to a histogram so that the histogram visualizes all the points in the scatter plot that are selected by a brush
- summarize the key concepts covered in this course
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