Seaborn Plot

Category: Mega-Polis → Visualisation → Visualisation Data Tools
Node ID: SvMegapolisSeabornPlot
Tooltip: Seaborn Plot
Dependencies: seaborn, matplotlib, pandas

Functionality

Creates a Seaborn-based statistical plot from an input Pandas DataFrame.

The node:

1. Receives a DataFrame and selected feature names.
2. Generates a Seaborn plot (e.g., scatter, line, histogram, boxplot).
3. Displays the plot using Matplotlib.

This node is intended for quick exploratory statistical visualisation inside Mega-Polis workflows.

Inputs

Socket	Type	Description
Dataframe	SvStringsSocket	Input Pandas DataFrame. Must be linked.
X	SvStringsSocket	Column name used for X axis.
Y	SvStringsSocket	Column name used for Y axis (if required by plot type).

Parameters

Name	Type	Default	Description
Plot Type (plottype)	Enum	scatter	Selects which Seaborn plot function is used.
Hue	String	None	Optional grouping column for colour separation.
Style	String	None	Optional grouping column for marker style.
Height	Float	6	Figure height (inches).
Run	Bool	False	When enabled, generates the plot.

Available plot types

• scatter
• line
• hist
• box
• violin
• bar

(Exact list depends on implementation in the node source.)

Outputs

This node has no output sockets.
It generates and displays a Seaborn/Matplotlib plot when Run=True.

Example

Scatter plot of height vs area

1. Load a dataset (e.g., via Read CSV).
2. Connect:
   • Dataframe → Dataframe
   • X → "height"
   • Y → "area"
3. Set:
   • Plot Type → scatter
   • Run → True
4. The node will display a Seaborn scatter plot.

Grouped boxplot

1. X → "landuse"
2. Y → "height"
3. Plot Type → box
4. Optional: Hue → "zone_type"
5. Run → True

Notes

• The node only displays plots when Run is enabled.
• X and Y features must exist in the DataFrame.
• Some plot types require both X and Y; others (e.g., histogram) may require only one.
• Large datasets may slow down rendering.
• Output appears in the Matplotlib display context (not as a Sverchok output object). ```