strip_column
Remove whitespace or specific characters from column values in CSV data to clean and standardize text fields for analysis.
Instructions
Strip whitespace or specified characters from column values.
Returns: ColumnOperationResult with strip details
Examples: # Remove leading/trailing whitespace strip_column(ctx, "name")
# Remove specific characters
strip_column(ctx, "phone", "()")
# Clean currency values
strip_column(ctx, "price", "$,")
# Remove quotes
strip_column(ctx, "quoted_text", "'\"")Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| column | Yes | Column name to strip characters from | |
| chars | No | Characters to strip (None for whitespace, string for specific chars) |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| success | No | Whether operation completed successfully | |
| operation | Yes | Type of operation performed | |
| transform | No | Transform description | |
| part_index | No | Part index for split operations | |
| nulls_filled | No | Number of null values filled | |
| rows_removed | No | Number of rows removed (for remove_duplicates) | |
| rows_affected | Yes | Number of rows affected by operation | |
| values_filled | No | Number of values filled (for fill_missing_values) | |
| updated_sample | No | Sample values after operation | |
| original_sample | No | Sample values before operation | |
| columns_affected | Yes | Names of columns affected |
Implementation Reference
- The handler function that executes the strip_column tool logic: strips leading/trailing whitespace or specified characters from all values in the given column of the session's dataframe, using pandas str.strip(), and returns a ColumnOperationResult with details on changes made.
async def strip_column( ctx: Annotated[Context, Field(description="FastMCP context for session access")], column: Annotated[str, Field(description="Column name to strip characters from")], chars: Annotated[ str | None, Field(description="Characters to strip (None for whitespace, string for specific chars)"), ] = None, ) -> ColumnOperationResult: r"""Strip whitespace or specified characters from column values. Returns: ColumnOperationResult with strip details Examples: # Remove leading/trailing whitespace strip_column(ctx, "name") # Remove specific characters strip_column(ctx, "phone", "()") # Clean currency values strip_column(ctx, "price", "$,") # Remove quotes strip_column(ctx, "quoted_text", "'\"") """ # Get session_id from FastMCP context session_id = ctx.session_id _session, df = get_session_data(session_id) _validate_column_exists(column, df) # Store original for comparison original_data = df[column].copy() # Apply strip operation if chars is None: # Strip whitespace df[column] = df[column].astype(str).str.strip() else: # Strip specified characters df[column] = df[column].astype(str).str.strip(chars) # Count changes made changes_made = _count_column_changes(original_data, df[column]) return ColumnOperationResult( operation=f"strip_{'whitespace' if chars is None else 'chars'}", rows_affected=changes_made, columns_affected=[column], ) - src/databeak/servers/column_text_server.py:535-535 (registration)Registers the strip_column handler as a tool named 'strip_column' on the FastMCP server instance 'column_text_server'.
column_text_server.tool(name="strip_column")(strip_column) - Pydantic-style type annotations with Field descriptions define the input schema for the tool: ctx (Context), column (str), optional chars (str|None). Output is ColumnOperationResult.
async def strip_column( ctx: Annotated[Context, Field(description="FastMCP context for session access")], column: Annotated[str, Field(description="Column name to strip characters from")], chars: Annotated[ str | None, Field(description="Characters to strip (None for whitespace, string for specific chars)"), ] = None, ) -> ColumnOperationResult: