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Boxplot Chart Node

The Boxplot Chart Node visualizes the distribution of a dataset, showing its minimum, maximum, median, and quartiles, making it ideal for identifying outliers and understanding variability.

Overview​

This node requires the user to select a category column (X axis) and a value column (Y axis). Each box represents the distribution of values within a category.

Key Features​

  • Distribution analysis: Visualize data spread and variability.
  • Outlier detection: Easily identify outliers in the dataset.
  • Customizable orientation: Supports horizontal or vertical layouts.
  • Dashboard ready: Integrates with dashboards for interactive exploration.

Required Data​

  • xColumn: The category column.
  • yColumn: The value column.
  • groupByColumn (optional): For grouped boxplots.
  • log, vertical, whiskerLength: Additional display options.

How it works​

  1. Add the Boxplot Chart Node to your workflow.
  2. Connect your dataset.
  3. Select the category and value columns.
  4. Configure display options as needed.
  5. The node renders a boxplot chart.

Use Cases​

  • Exam scores: Analyze the distribution of scores across different classes.
  • Sales performance: Understand variability in sales across regions.
  • Sensor data: Detect anomalies in sensor readings over time.

Benefits​

  • Detailed distribution analysis for categorical data.
  • Effective outlier detection to improve data quality.
  • Handles large datasets efficiently.