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Clean LinkedIn Jobs results into a CSV, one row per role

The step after LinkedIn Jobs Scraper: one row per job title and company (the same role posted in several cities counts once), highest pay first, salary, level and applicants in their own columns, without the long description fields, saved as a CSV. The sample is 20 Stripe jobs; pick your own run's dataset instead.

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Dataset Transformer: Filter, Dedupe, JSON to CSV
Dataset Transformer: Filter, Dedupe, JSON to CSVhumble-echidna/dataset-transform
Job title
Company
Location
Level
+8 fields
Text
Number
Boolean
List
Object

Input

Apify dataset:i6v4vd3tDeSAUFuog
Remove duplicates by:title+1
Sort by:salaryMax desc
Fields to keep (and rename):title+11
Also save as a file:csv

Output fields

Job title
Company
Location
Level
Type
Salary from
Salary to
Currency
Per
Posted
Applicants
Job

How it works

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The Dataset Transformer: Filter, Dedupe, JSON to CSV Actor is ready to run with the inputs already set for "Clean LinkedIn Jobs results into a CSV, one row per role". Sign up or log in and you'll land in Apify Console with a copy of this exact task.

Start the "Clean LinkedIn Jobs results into a CSV, one row per role" task

The Dataset Transformer: Filter, Dedupe, JSON to CSV Actor will start running based on the input automatically. You can also change all the input fields, like apify dataset, remove duplicates by, and more, to match your specific use case.

Receive the "Clean LinkedIn Jobs results into a CSV, one row per role" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as job title, company, location, and more.

Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Clean LinkedIn Jobs results into a CSV, one row per role" task via API.

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