scatter_plot

Visualize data trends by creating scatter plots from SQL query results on CSV or Parquet sources. Use DuckDB SQL syntax to define queries and specify x, y, and optional color dimensions for detailed analysis.

Instructions

Run query against specified source and make a scatter plot using result For both csv and parquet sources, use DuckDB SQL syntax Use 'CSV' as the table name in the SQL query for csv sources. Use 'PARQUET' as the table name in the SQL query for parquet sources.

This will return an image of the plot

Input Schema

Name	Required	Description
`color`	No	Optional; column name from SQL result to use for coloring the points, with color representing another dimension
`query`	Yes	SQL query to run on the data source
`source_id`	Yes	The data source to run the query on
`x`	Yes	Column name from SQL result to use for x-axis
`y`	Yes	Column name from SQL result to use for y-axis

Input Schema (JSON Schema)

{
  "properties": {
    "color": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional; column name from SQL result to use for coloring the points, with color representing another dimension",
      "title": "Color"
    },
    "query": {
      "description": "SQL query to run on the data source",
      "title": "Query",
      "type": "string"
    },
    "source_id": {
      "description": "The data source to run the query on",
      "title": "Source Id",
      "type": "string"
    },
    "x": {
      "description": "Column name from SQL result to use for x-axis",
      "title": "X",
      "type": "string"
    },
    "y": {
      "description": "Column name from SQL result to use for y-axis",
      "title": "Y",
      "type": "string"
    }
  },
  "required": [
    "source_id",
    "query",
    "x",
    "y"
  ],
  "type": "object"
}

Zaturn

scatter_plot

Instructions

Input Schema

Input Schema (JSON Schema)

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