data_count
Calculate non-null element counts for each column in a dataset. Use the MCP Data Wrangler server tool to streamline data preprocessing and ensure accurate data analysis.
Instructions
Number of non-null elements for each column
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| input_data_file_path | No | Path to the input data file |
Implementation Reference
- The asynchronous handler function for the 'data_count' tool that loads the input data, computes the count of non-null values per column, formats it as a dictionary, and returns it as JSON text content.
async def handle_data_count( arguments: dict[str, Any], ) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]: data_count_input = DataCountInputSchema.from_args(arguments) count_df = data_count_input.df.count() # Convert the DataFrame to a dictionary format count_dict = { "description": "Number of non-null elements for each column", "counts": {col: int(val) for col, val in zip(count_df.columns, count_df.row(0))}, } return [ types.TextContent( type="text", text=json.dumps(count_dict), ) ] - Pydantic input schema class for the 'data_count' tool, including methods to define the JSON schema, load data from file path in arguments, and validate/parse input.
class DataCountInputSchema(Data): model_config = ConfigDict( validate_assignment=True, frozen=True, extra="forbid", arbitrary_types_allowed=True, ) @staticmethod def input_schema() -> dict: return { "type": "object", "properties": { "input_data_file_path": { "type": "string", "description": "Path to the input data file", }, }, } @staticmethod def from_schema(input_data_file_path: str) -> "DataCountInputSchema": data = Data.from_file(input_data_file_path) return DataCountInputSchema(df=data.df) @staticmethod def from_args(arguments: dict[str, Any]) -> "DataCountInputSchema": input_data_file_path = arguments["input_data_file_path"] return DataCountInputSchema.from_schema(input_data_file_path=input_data_file_path) - src/mcp_server_data_wrangler/tools/tools.py:87-91 (registration)Tool object registration for 'data_count' in MCPServerDataWrangler.tools() method, defining the tool's name, description, and input schema for MCP server listing.
types.Tool( name=MCPServerDataWrangler.data_count.value[0], description=MCPServerDataWrangler.data_count.value[1], inputSchema=DataCountInputSchema.input_schema(), ), - src/mcp_server_data_wrangler/tools/tools.py:156-156 (registration)Dispatch mapping in MCPServerDataWrangler.tool_to_handler() dictionary that associates the 'data_count' tool name with its handler function.
MCPServerDataWrangler.data_count.value[0]: handle_data_count,