transform_column_case

Change text case in a CSV column to uppercase, lowercase, title case, or capitalize sentences for data standardization and analysis.

Instructions

Transform the case of text in a column.

Returns: ColumnOperationResult with transformation details

Examples: # Convert to uppercase transform_column_case(ctx, "code", "upper")

# Convert names to title case
transform_column_case(ctx, "name", "title")

# Convert to lowercase for comparison
transform_column_case(ctx, "email", "lower")

# Capitalize sentences
transform_column_case(ctx, "description", "capitalize")

Input Schema

TableJSON Schema

Name	Required	Description	Default
`column`	Yes	Column name to transform text case in
`transform`	Yes	Case transformation: upper, lower, title, or capitalize

Implementation Reference

src/databeak/servers/column_text_server.py:342-404 (handler)

The main asynchronous handler function that transforms the case of text in a specified DataFrame column based on the provided transform type (upper, lower, title, capitalize) using pandas string methods. It validates the column exists, applies the transformation in-place, counts changes, and returns a ColumnOperationResult.

async def transform_column_case(
    ctx: Annotated[Context, Field(description="FastMCP context for session access")],
    column: Annotated[str, Field(description="Column name to transform text case in")],
    transform: Annotated[
        Literal["upper", "lower", "title", "capitalize"],
        Field(description="Case transformation: upper, lower, title, or capitalize"),
    ],
) -> ColumnOperationResult:
    """Transform the case of text in a column.

    Returns:
        ColumnOperationResult with transformation details

    Examples:
        # Convert to uppercase
        transform_column_case(ctx, "code", "upper")

        # Convert names to title case
        transform_column_case(ctx, "name", "title")

        # Convert to lowercase for comparison
        transform_column_case(ctx, "email", "lower")

        # Capitalize sentences
        transform_column_case(ctx, "description", "capitalize")

    """
    # 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 case transformation
    str_col = df[column].astype(str)

    if transform == "upper":
        df[column] = str_col.str.upper()
    elif transform == "lower":
        df[column] = str_col.str.lower()
    elif transform == "title":
        df[column] = str_col.str.title()
    elif transform == "capitalize":
        df[column] = str_col.str.capitalize()
    else:
        msg = "transform"
        raise InvalidParameterError(
            msg,
            transform,
            "Supported transforms: upper, lower, title, capitalize",
        )

    # Count changes made
    changes_made = _count_column_changes(original_data, df[column])

    return ColumnOperationResult(
        operation=f"case_{transform}",
        rows_affected=changes_made,
        columns_affected=[column],
    )

src/databeak/servers/column_text_server.py:534-534 (registration)
Registration of the transform_column_case function as a tool named 'transform_column_case' on the FastMCP column_text_server instance.
```
column_text_server.tool(name="transform_column_case")(transform_column_case)
```

src/databeak/servers/column_text_server.py:342-349 (schema)

Pydantic-based input schema defined via Annotated types and Field descriptions for the tool parameters: ctx (Context), column (str), transform (Literal['upper', 'lower', 'title', 'capitalize']). Output is ColumnOperationResult.

async def transform_column_case(
    ctx: Annotated[Context, Field(description="FastMCP context for session access")],
    column: Annotated[str, Field(description="Column name to transform text case in")],
    transform: Annotated[
        Literal["upper", "lower", "title", "capitalize"],
        Field(description="Case transformation: upper, lower, title, or capitalize"),
    ],
) -> ColumnOperationResult:

src/databeak/servers/column_text_server.py:47-60 (helper)

Helper function used by the handler to count the number of rows changed after transformation by comparing original and modified series.

def _count_column_changes(original: pd.Series, modified: pd.Series) -> int:
    """Count number of changes between original and modified column data.

    Args:
        original: Original column data
        modified: Modified column data

    Returns:
        Number of rows that changed

    """
    changed_mask = original.astype(str).fillna("") != modified.astype(str).fillna("")
    return int(changed_mask.sum())

src/databeak/servers/column_text_server.py:32-45 (helper)

Helper function used by the handler to validate that the specified column exists in the DataFrame, raising ColumnNotFoundError if not.

def _validate_column_exists(column: str, df: pd.DataFrame) -> None:
    """Validate that a column exists in the DataFrame.

    Args:
        column: Column name to check
        df: DataFrame to check in

    Raises:
        ColumnNotFoundError: If column doesn't exist

    """
    if column not in df.columns:
        raise ColumnNotFoundError(column, df.columns.tolist())

DataBeak