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I will create a small python script for CSV cleanup
Mustafa Kemal
About this gig
Get a reusable local Python script for one agreed CSV structure. The Basic package covers trimming spaces, normalising column names, removing exact duplicate rows and reporting missing required values. Ambiguous data is flagged rather than guessed, and your original file is preserved. Delivery includes Python source code, separate cleaned output, a validation report and a README. Python must be available on the computer where the script will run. Basic: USD 25, 3 days, 1 revision within the agreed rules. Send the schema, approximate row count, encoding, duplicate policy and expected output so the scope can be checked. Private data stays local; do not send sensitive files for external processing. Portfolio examples are synthetic demonstrations, not past client projects. This package covers CSV file processing. Excel macros, website scraping, server installation, ongoing hosting and paid API services are outside this package.
Get to know Mustafa Kemal
Mustafa Kemal
CSV Cleanup and Python File Automation
- FromTurkey
- Member sinceOct 2026
- Avg. response time2 hours
Languages
Turkish, English
I offer small, clearly scoped CSV cleanup and file-processing tools. Deliverables can include a Python script, example output, validation checks and a short README. I preserve source files, apply agreed rules and flag missing or inconsistent values rather than guess. My workflow uses AI-assisted development and local testing, only where the project permits it. Portfolio examples are synthetic demonstrations, not past client projects. I also have experience with Excel tasks and document formatting.
FAQ
Will you change my source file or guess missing values?
The script writes separate outputs and preserves the input. Missing or ambiguous values are reported rather than guessed. One revision covers corrections within the agreed CSV rules. This package does not include website scraping, server installation or Excel macros.
What information do you need before starting?
Provide the schema, row count, encoding, cleanup rules and expected output, using a permitted synthetic or redacted example. Private data is processed locally. Portfolio examples are synthetic demonstrations.
