Rename Dataset Fields

Name: Rename Dataset Fields
Author: lukaskrivka

by lukaskrivka

Quickly rename columns in any Apify dataset with a simple mapping. Clean and standardize your data for analysis or integration without manual hassle.

71 runs

14 users

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Opens on Apify.com

About Rename Dataset Fields

Ever exported a dataset only to realize the column names are a cryptic mess? Maybe you're pulling data from an API that uses inconsistent naming, or you're trying to merge two datasets where one calls it "price" and the other "cost." Manually renaming fields is a tedious chore that eats into your actual work. That's where this actor comes in. It does one job and does it well: it renames the fields in your Apify datasets. You just provide a simple mapping—like `old_name: new_name`—and it handles the rest. It's perfect for cleaning data before analysis, standardizing outputs from different scrapers, or preparing datasets for a database that has specific column requirements. I use it as a quick cleanup step in my automation workflows. Since it's open-source, you can check the code, tweak it if needed, or just run it with confidence knowing exactly what it does. It’s a straightforward fix for a common, annoying problem.

What does this actor do?

Rename Dataset Fields is a web scraping and automation tool available on the Apify platform. It's designed to help you extract data and automate tasks efficiently in the cloud.

Key Features

Cloud-based execution - no local setup required
Scalable infrastructure for large-scale operations
API access for integration with your applications
Built-in proxy rotation and anti-blocking measures
Scheduled runs and webhooks for automation

How to Use

Click "Try This Actor" to open it on Apify
Create a free Apify account if you don't have one
Configure the input parameters as needed
Run the actor and download your results

Documentation

Rename Dataset Fields

An Apify Actor that renames fields (columns) in a dataset. It's primarily used as an integration to automatically process a dataset after another actor's run finishes.

Key Features

Field Renaming: Changes the names of specified fields in a dataset.
Post-Run Integration: Can be set up to run automatically after another actor completes its task.
Simple Mapping: Uses a clear JSON structure to define old and new field names.

How to Use

The actor is typically configured as an integration in another actor's settings. You can set it to run after the main actor finishes, passing the dataset for renaming.

You can also run it manually via API or console by providing a dataset ID and the rename mapping.

Input/Output

Input: The actor requires a renameMapping object in the input JSON.

{
  "renameMapping": {
    "old_field_name_1": "new_field_name_1",
    "old_field_name_2": "new_field_name_2"
  }
}

renameMapping: An object where each key is the current field name and its value is the desired new name.

Output: The actor modifies the dataset in-place. The original dataset will be updated with the new field names. No new dataset is created by default. Ensure you have a backup or are operating on a copy if needed.

Categories: DEVELOPER_TOOLS, INTEGRATIONS, OPEN_SOURCE