sort_data
Sort data files by specific columns to organize information for analysis. Specify ascending or descending order and optionally save sorted results.
Instructions
Sort data by a specific column.
Args: file_path: Path to the data file column: Column name to sort by descending: Sort in descending order (default: False) output_path: Optional path to save sorted data
Returns: Information about the sorted data
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes | ||
| column | Yes | ||
| descending | No | ||
| output_path | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Implementation Reference
- src/visidata_mcp/server.py:491-552 (handler)The sort_data tool implementation registered with @mcp.tool() decorator. This function loads data using pandas, sorts it by a specified column in ascending or descending order, optionally saves the sorted data to an output file, and returns sorting information as JSON.
@mcp.tool() def sort_data(file_path: str, column: str, descending: bool = False, output_path: Optional[str] = None) -> str: """ Sort data by a specific column. Args: file_path: Path to the data file column: Column name to sort by descending: Sort in descending order (default: False) output_path: Optional path to save sorted data Returns: Information about the sorted data """ try: import pandas as pd from pathlib import Path file_extension = Path(file_path).suffix.lower() # Load with pandas if file_extension == '.csv': df = pd.read_csv(file_path) elif file_extension == '.json': df = pd.read_json(file_path) elif file_extension in ['.xlsx', '.xls']: df = pd.read_excel(file_path) elif file_extension == '.tsv': df = pd.read_csv(file_path, sep='\t') else: df = pd.read_csv(file_path) if column not in df.columns: return f"Error: Column '{column}' not found. Available columns: {list(df.columns)}" # Sort the data sorted_df = df.sort_values(by=column, ascending=not descending) result = { "sorted_by": column, "descending": descending, "total_rows": len(sorted_df) } # If output path is specified, save sorted data if output_path: output_extension = Path(output_path).suffix.lower() if output_extension == '.csv': sorted_df.to_csv(output_path, index=False) elif output_extension == '.json': sorted_df.to_json(output_path, orient='records', indent=2) elif output_extension in ['.xlsx', '.xls']: sorted_df.to_excel(output_path, index=False) else: # Default to CSV sorted_df.to_csv(output_path, index=False) result["saved_to"] = output_path return json.dumps(result, indent=2) except Exception as e: return f"Error sorting data: {str(e)}\n{traceback.format_exc()}"