update_column
Modify or transform data in a specific column using operations like replace, extract, or split. Simplify CSV data editing with precise column-level updates.
Instructions
Update values in a specific column with simple operations like replace, extract, split, etc.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| column | Yes | ||
| operation | Yes | ||
| pattern | No | ||
| replacement | No | ||
| session_id | Yes | ||
| value | No |
Implementation Reference
- Core handler function implementing the update_column tool logic. Performs various string and value transformations on a specified column using pandas methods (replace, extract, split, strip, upper, lower, fill). Records the operation and returns update summary.async def update_column( session_id: str, column: str, operation: str, value: Optional[Any] = None, pattern: Optional[str] = None, replacement: Optional[str] = None, ctx: Context = None ) -> Dict[str, Any]: """ Update values in a specific column with simple operations. Args: session_id: Session identifier column: Column name to update operation: Operation type - 'replace', 'extract', 'split', 'strip', 'upper', 'lower', 'fill' value: Value for certain operations (e.g., fill value) pattern: Pattern for replace/extract operations (regex supported) replacement: Replacement string for replace operation ctx: FastMCP context Returns: Dict with success status and update info """ try: manager = get_session_manager() session = manager.get_session(session_id) if not session or session.df is None: return {"success": False, "error": "Invalid session or no data loaded"} df = session.df if column not in df.columns: return {"success": False, "error": f"Column '{column}' not found"} original_values_sample = df[column].head(5).tolist() if operation == "replace": if pattern is None or replacement is None: return {"success": False, "error": "Pattern and replacement required for replace operation"} session.df[column] = df[column].astype(str).str.replace(pattern, replacement, regex=True) elif operation == "extract": if pattern is None: return {"success": False, "error": "Pattern required for extract operation"} session.df[column] = df[column].astype(str).str.extract(pattern, expand=False) elif operation == "split": if pattern is None: pattern = " " if value is not None and isinstance(value, int): # Extract specific part after split session.df[column] = df[column].astype(str).str.split(pattern).str[value] else: # Just do the split, take first part session.df[column] = df[column].astype(str).str.split(pattern).str[0] elif operation == "strip": session.df[column] = df[column].astype(str).str.strip() elif operation == "upper": session.df[column] = df[column].astype(str).str.upper() elif operation == "lower": session.df[column] = df[column].astype(str).str.lower() elif operation == "fill": if value is None: return {"success": False, "error": "Value required for fill operation"} session.df[column] = df[column].fillna(value) else: return {"success": False, "error": f"Unknown operation: {operation}"} updated_values_sample = session.df[column].head(5).tolist() session.record_operation(OperationType.UPDATE_COLUMN, { "column": column, "operation": operation, "pattern": pattern, "replacement": replacement, "value": str(value) if value is not None else None }) return { "success": True, "column": column, "operation": operation, "original_sample": original_values_sample, "updated_sample": updated_values_sample, "rows_updated": len(session.df) } except Exception as e: logger.error(f"Error updating column: {str(e)}") return {"success": False, "error": str(e)}
- src/csv_editor/server.py:290-302 (registration)MCP tool registration for update_column using @mcp.tool decorator. This thin wrapper delegates to the implementation in transformations.py.@mcp.tool async def update_column( session_id: str, column: str, operation: str, value: Optional[Any] = None, pattern: Optional[str] = None, replacement: Optional[str] = None, ctx: Context = None ) -> Dict[str, Any]: """Update values in a specific column with simple operations like replace, extract, split, etc.""" return await _update_column(session_id, column, operation, value, pattern, replacement, ctx)
- Enum value OperationType.UPDATE_COLUMN used to categorize and record update_column operations in session history.UPDATE_COLUMN = "update_column"