You will get a clean, normalized & validated CSV/Excel dataset (ready for analysis)

Santiago F.Status: Offline
Santiago F.
Rising Talent

Let a pro handle the details

Buy Data Entry & Cleaning services from Santiago, priced and ready to go.
Santiago F.Status: Offline
Santiago F.
Rising Talent

Let a pro handle the details

Buy Data Entry & Cleaning services from Santiago, priced and ready to go.

Project details

I will clean, normalize, and validate messy CSV/Excel files so you can load them into dashboards, databases, or scripts without errors.

What you get:
• Cleaned CSV/XLSX outputs (consistent headers, dates, numbers, blanks handled)
• Robust fixes for common real-world issues: delimiter mismatches, mixed date formats, currency/decimal commas, missing/invalid values
• A clear log/report of what was changed (Starter: quick log; Standard: QC summary; Advanced: detailed QA + custom rules)

How I work:
1. Quick review + confirm your expected output format
2. Clean + normalize your data
3. QC checks + deliver cleaned files + included report/log
4. Apply included revisions (if any)

Large datasets are supported via workload add-ons (based on single file size or total batch size). Upload your files (or a sample) and tell me your preferred output format.
Data Tool
Python
What's included
Service Tiers Starter
$20
Standard
$50
Advanced
$120
Delivery Time 1 day 2 days 4 days
Number of Revisions
123
Number of Pages Mined/Scraped
000
Number of Sources Mined/Scraped
000
Optional add-ons You can add these on the next page.
Fast Delivery
+$20 - $60
Additional Revision
+$10
Large workload: file size (100–300MB) OR total input size (300MB - 1GB) (+ 1 Day)
+$30
Extra-large workload: file size(300-700MB) OR total input is 1-3GB (+ 2 Days)
+$70
Massive workload: file size(700MB–1.5GB) OR total input 3-6GB (+ 3 Days)
+$150

Frequently asked questions

Santiago F.Status: Offline

About Santiago

Santiago F.Status: Offline
Python Bug Fixing & Automation | QA (pytest) | CSV/ETL Parsing
Cali, Colombia - 8:10 pm local time
I help clients fix bugs fast and make code reliable. I specialize in Python scripting/automation, debugging, and QA with reproducible fixes (pytest/unit tests). I also handle messy data issues—CSV/ETL parsing, inconsistent formats, missing values—and turn them into clean, working pipelines.
What you get when working with me:
- Root-cause analysis + clean fix (PR-ready)
- Tests added/updated (pytest) to prevent regressions
- Clear notes + Git commits so it’s easy to maintain
If you have a broken script, failing tests, or a data pipeline that crashes on real-world input, send me the error/logs and I’ll propose a fast fix with tests and a clear ETA.

Steps for completing your project

After purchasing the project, send requirements so Santiago can start the project.

Delivery time starts when Santiago receives requirements from you.

Santiago works on your project following the steps below.

Revisions may occur after the delivery date.

Review files + confirm output

I review your files and confirm the target output (format, dates, decimals, delimiter) and any rules you provided.

Clean + normalize data

I clean and normalize headers, missing values, dates, and numbers/currency, then generate the cleaned output files.

Review the work, release payment, and leave feedback to Santiago.