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I will automate CSV merging and data cleaning with python
About this Gig
Do you combine new CSV exports and repeat the same checks every week or month?
I will build a reusable Python script for one clearly defined CSV workflow: merge files, clean agreed fields, check required values, and flag duplicates. Run it again when new files arrive using the same agreed structure and rules.
You will receive:
- Python source code for your agreed file format
- A cleaned CSV and separate reports for duplicates and invalid rows
- A processing summary and an example run
- Setup and usage instructions
The starter package covers up to 5 CSV files per run, 25,000 rows combined, one shared column structure, one duplicate key, and up to 3 agreed cleaning or validation rules. Your original files remain unchanged.
Please contact me before ordering with a small anonymized sample and the output you expect. I will confirm the scope and delivery before we start.
One revision covers adjustments to the agreed workflow. New file formats, additional workflows, GUIs, web scraping, API connections, and hosting require a separate scope.
Technology:
Python
FAQ
Is this a one-time cleanup or a reusable script?
You receive both an example of the processed output and a reusable script for the agreed workflow.
Can I run the script again with new files?
Yes, for files using the agreed structure and rules. Instructions are included.
Do I need Python installed?
Yes. This package delivers a Python script for local command-line use. A standalone application is a separate scope.
Can you work with Excel files?
This starter package covers CSV. Please send details for XLSX or other formats before ordering.
What happens when duplicate records disagree?
We agree on a rule first. Conflicts are reported so they can be reviewed; the script will not guess which data is correct.
What counts as a revision?
One round of adjustments to the agreed rules or output. New formats, sources or features need a separate quote.
Can you process private business data?
Start with an anonymized sample. The script runs locally and does not need external services. We agree on how any necessary files will be handled before the order.
