polar_scatter
Create polar scatter plots by querying data sources with SQL. Visualize radial and angular coordinates from query results as scatter points on a polar coordinate system.
Instructions
Run query against specified source and make a polar 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
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| source_id | Yes | The data source to run the query on | |
| query | Yes | SQL query to run on the data source | |
| r | Yes | Column name from SQL result to use as radial coordinate | |
| theta | Yes | Column name from SQL result to use as angular coordinate | |
| color | No | Optional; column name from SQL result to use for coloring the points, with color representing another dimension |
Implementation Reference
- zaturn/tools/visualizations.py:310-342 (handler)Handler function implementing the polar_scatter tool. Runs SQL query on specified data source, generates polar scatter plot using plotly.express.scatter_polar with radial (r) and angular (theta) coordinates, optionally colored by another column, converts to base64 PNG ImageContent or returns error string.
def polar_scatter(self, source_id: Annotated[ str, Field(description='The data source to run the query on') ], query: Annotated[ str, Field(description='SQL query to run on the data source') ], r: Annotated[ str, Field(description='Column name from SQL result to use as radial coordinate') ], theta: Annotated[ str, Field(description='Column name from SQL result to use as angular coordinate') ], color: Annotated[ str | None, Field(description='Optional; column name from SQL result to use for coloring the points, with color representing another dimension') ] = None, ) -> str | ImageContent: """ Run query against specified source and make a polar 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 """ try: df = self._get_df_from_source(source_id, query) fig = px.scatter_polar(df, r=r, theta=theta, color=color) return _fig_to_image(fig) except Exception as e: return str(e) - zaturn/tools/visualizations.py:29-40 (registration)Registration of the polar_scatter tool in the Visualizations class's self.tools list during initialization.
self.tools = [ self.scatter_plot, self.line_plot, self.histogram, self.strip_plot, self.box_plot, self.bar_plot, self.density_heatmap, self.polar_scatter, self.polar_line, ] - zaturn/tools/visualizations.py:13-22 (helper)Helper function to convert a Plotly figure to a base64-encoded PNG ImageContent object, used by polar_scatter and other visualization tools.
def _fig_to_image(fig): fig_encoded = b64encode(fig.to_image(format='png')).decode() img_b64 = "data:image/png;base64," + fig_encoded return ImageContent( type = 'image', data = fig_encoded, mimeType = 'image/png', annotations = None, ) - zaturn/tools/visualizations.py:43-49 (helper)Helper function to retrieve and execute SQL query on the specified data source using query_utils, returning a DataFrame; used by polar_scatter and other tools.
def _get_df_from_source(self, source_id, query): source = self.data_sources.get(source_id) if not source: raise Exception(f"Source {source_id} Not Found") return query_utils.execute_query(source, query)