# Box Plot

A **Box Plot** (also known as a **Whisker Plot**) is a statistical chart that displays the distribution of a dataset based on five key summary metrics:

* **Minimum (Min)**
* **First Quartile (Q1)**
* **Median (Q2)**
* **Third Quartile (Q3)**
* **Maximum (Max)**

The chart also highlights **outliers** beyond the whiskers, making it an effective tool for identifying variability, spread, and anomalies within the data.

For example, a Box Plot can show the **distribution of exam scores across different student groups**, helping identify performance ranges and extreme values.

### Best Situations to Use

Use a Box Plot chart when you want to:

* **Show distributions of numeric data** across one or more categories.
* **Compare multiple groups** (e.g., Male vs. Female scores, Region A vs. Region B).
* **Identify variability** within groups, including outliers.
* **Highlight skewness** or spread in data values.

### Variations

* **Letter-Value Plots**: An extension of the standard Box Plot that uses multiple nested boxes to enclose progressively larger portions of the dataset. Useful for very large datasets.
* **Violin Plots**: Combines Box Plot with a density curve to provide richer insights into the distribution shape.

### Properties of the Box Plot Chart

#### General

* **Component Name**: Unique identifier for the chart.
* **Left / Top**: Position of the chart on the canvas.
* **Height / Width**: Chart dimensions.
* **Initial Visibility**: Toggle chart visibility on first render.
* **Max Button**: Enable a maximize option.
* **Fill Colors**: Configure fill colors for box areas.
* **Stroke Color**: Define outline/border color for elements.

#### Background

* **Gradient Rotation**: Adjust background gradient angle.
* **Opacity**: Control transparency.
* **Gradient**: Select gradient type and direction.
* **Border / Border Color / Border Radius**: Configure chart border style, color, and corner curvature.
* **Shadow / Shadow Color / Transparency**: Add drop shadow with custom settings.

#### Tooltip

* **Show Tool Tip**: Enable or disable tooltips.
* **Configuration**:
  * Background Color
  * Opacity
  * Border Color
  * Font Size
  * Box Width
  * Precision (decimal places for values)

#### Title & Sub-Title

* **Show Title Box**: Toggle visibility of title container.
* **Title Settings**: Font, size, style, weight, family, alignment, decoration.
* **Title Bar Height**: Adjust height.
* **Description**: Add explanatory text.
* **Dataset Description**: Option to populate from mapped dataset.
* **Sub-Title**: Similar customization for sub-title text.

#### Axis Configuration

**X-Axis**

* Show / Hide axis line.
* Axis Line Color.
* Label settings: font color, size, weight, family, style, decoration, rotation, tilt.
* Axis description text.
* Category Tick Marks & Marker Color.
* Show Dataset Description.

**Y-Axis**

* Similar settings as X-axis: line visibility, label configuration, description, dataset description.

#### Legend

* **Show Legend**: Toggle legend visibility.
* **Font Properties**: Customize color, size, weight, family, style, and decoration.
* **Hide on Load**: Optionally hide legend at chart load.

#### Formatter

* **Unit**: Define measurement unit.
* **Precision**: Decimal places for numeric values.
* **Currency**: Format numbers as currency with appropriate symbol.
* **Position**: Place currency/unit before or after values.
* **Number Formatter**: Choose International or Indian numeric format.

#### Axis Setup

* **Auto Axis Setup**: Automatically adjust axis ranges.
* **Base Zero**: Start axis at zero for consistency.
* **Min / Max Value**: Set custom axis ranges.
* **Reference Lines**: Add horizontal/vertical/zero marker lines.
* **Zero Marker Color**: Customize baseline marker color.
* **Opacity**: Adjust transparency for markers/axes.

#### Export Options

* **Context Menu**: Enable export via right-click.
* **Supported Formats**: Excel (.xlsx), CSV (.csv), JPEG (.jpg), PNG (.png), PPTX (.pptx), PDF (.pdf).
* **Print Option**: Directly print chart.
* **Export Metadata**: Add custom heading, subheading, filename.
* **Global Export Type**: Choose default export style (Screenshot or Tabular).

### Dataset Properties

When configuring a Box Plot:

* **Category**: e.g., Gender.
* **Subcategory**: e.g., Grade.
* **Metrics**: Map numerical values such as Min, Max, Q1, Median, Q3.

Additional support for:

* **Outlier Properties**: Configure visual style for outliers.

### Example

Using the sample dataset:

* **Category**: Gender
* **Subcategory**: Grade
* **Values**: Map Min → Min field, Max → Max field, and Quartiles → Q1, Median, Q3 fields.

This produces a Box Plot highlighting score distributions for different categories, including outliers.

{% file src="/files/VlK6uTFg5DVgqmegsFHU" %}


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