fill_column_nulls
Replace missing values in a data column with a specified value to handle null or NaN entries during data preparation.
Instructions
Fill null/NaN values in a specific column with a specified value.
Returns: ColumnOperationResult with fill details
Examples: # Fill missing names with "Unknown" fill_column_nulls(ctx, "name", "Unknown")
# Fill missing ages with 0
fill_column_nulls(ctx, "age", 0)
# Fill missing status with default
fill_column_nulls(ctx, "status", "pending")
# Fill missing scores with -1
fill_column_nulls(ctx, "score", -1)Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| column | Yes | Column name to fill null values in | |
| value | Yes | Value to use for filling null/NaN values |
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 |