Data Modifiers
Update CSV Column
Overview:
The Update CSV Column block allows users to efficiently modify an existing CSV file by either updating a designated column with new data or adding a new column altogether.
Inputs & Outputs
| I/O | Feature | Type | Simple Explanation |
|---|---|---|---|
| input | csv_file_name | file | The target CSV file that needs modification, which must be in .csv format. |
| input | column_index | number | Identifies the position of the column to update (0 for the first column). |
| input | has_headers | boolean | Indicates whether the first row contains headers, helping determine how to process incoming data. |
| input | is_new_column | boolean | Specifies if the designated column for updating is newly created or has existed previously. |
| input | column_contents | string[] | New values that will populate into the specified column; each entry aligns with a row in the original CSV. |
| output | updated_csv_file_name | file | The resultant new CSV file name generated after incorporating updates or new columns. |
Use Cases
Here’s how this block can streamline various tasks:
- Merging New Data: Suppose you’ve collected additional metrics from an ongoing project and need to integrate these into your existing dataset—this block facilitates seamless merging without losing any previous information.
- Correcting Errors: If you discover discrepancies within your dataset due to incorrect entries, this tool allows easy corrections by replacing erroneous values in designated columns effectively.
- Adding Calculated Fields: When analyzing sales data over different periods, you might want to add a calculated “growth rate” field based on other figures—this block enables creating dynamic fields directly linked to your underlying data.
In essence, any scenario requiring updates or enhancements within a CSV can be efficiently handled using the Update CSV Column block!