Stacked Bar Chart With Selection Using Altair in Python

Prerequisite: Altair

In this article, We will see Stacked Bar Chart With Selection with Altair python. It is a declarative and interactive visualization tool for Python, based on Visualization Grammar (VeGa), It is simple, user-friendly, and moreover provides clearly interpretable charts. It supports a wide variety of charts like bar, line, scatter, box, violin, and other charts in an interactive way.  Let's discuss how to create a stacked bar chart with a selection to highlight a particular stack of the bar chart.

Installation

The following command can be used to install Altair and Pandas like any other python library:

pip install altair
pip install pandas
pip install altair_viewer

Functions Used

• The altair.selection_single() specify the type of selection inside the select method. The method takes parameters that are discussed below.

Syntax: altair.selection_single(type, encodings)

• type - string. Determines the default event processing and data query for the selection. Three types single, multi (shift+ click), interval (drag).
• encodings - List of encoding channels. The corresponding data field values must match for a data tuple to fall within the selection.

• The encode() method is used to map columns to visual attributes of the plot. This method takes in parameters of the x and y-axis and other chart attributes. The mark property is what specifies how exactly those attributes should be represented on the plot.

Syntax: alt.Chart(data).mark_bar().encode(x, y, color)

• x -  The x-axis value
• y - The y-axis value
• color - The color of the mark

Implementation

Import the Altair and pandas package. Read the dataset using pandas and specify the type of selection we have used the selection_single() method. Then, pass the dataset to the chart() function and make use of the mark_bar().encode() method to pass the x and y-axis values and append the selection object after passing the parameters to the mark_bar() function.

Example 1:

The dataset used for demonstration purposes can be downloaded from here.

Output:

To see the interactive visualization, run the code and it will automatically redirect you to an interactive webpage.

Example 2:

The pandas DataFrame is used for demonstration purposes.

Output: