You will get a Python data pipeline that fetches, cleans, and reports automatically
Project details
For data that needs to move and update on a schedule - not just once. I build a Python pipeline that automatically pulls your data (from APIs, files, or the web), cleans and combines it, loads it into a sheet or database, and produces the report or email your team needs - on autopilot.
What's included:
• Scheduled data pipeline (Python / Apps Script)
• Pull from APIs, files, or web sources, then clean & transform (ETL)
• Load into Google Sheets, Excel, or a database
• Automated report or email output
• Validation + error handling so it runs reliably
• Documentation, a short walkthrough video, and editable code
Great for: recurring reporting, consolidating data from multiple sources, Sheets/Excel and database/API sync, and replacing a manual weekly data process.
I work in clear English, fully async, and test against your real data before delivery. Share your sources and the output you need, and I'll scope it precisely first.
What's included:
• Scheduled data pipeline (Python / Apps Script)
• Pull from APIs, files, or web sources, then clean & transform (ETL)
• Load into Google Sheets, Excel, or a database
• Automated report or email output
• Validation + error handling so it runs reliably
• Documentation, a short walkthrough video, and editable code
Great for: recurring reporting, consolidating data from multiple sources, Sheets/Excel and database/API sync, and replacing a manual weekly data process.
I work in clear English, fully async, and test against your real data before delivery. Share your sources and the output you need, and I'll scope it precisely first.
What's included
| Service Tiers |
Starter
$300
|
Standard
$550
|
Advanced
$800
|
|---|---|---|---|
| Delivery Time | 7 days | 10 days | 14 days |
Number of Pages Mined/Scraped | 100 | 500 | 2000 |
Number of Sources Mined/Scraped | 1 | 3 | 5 |
Number of Revisions | 0 | 0 | 0 |
About Sota
Spreadsheet & Data Automation - Python, Apps Script & Excel VBA
Kawasaki, Japan - 6:55 am local time
The problem: the same data exported from different systems never lines up — different column names, delimiters, date formats, currencies, invalid rows, and duplicates. Cleaning it by hand is slow and has to be redone every time.
My approach: one command reads every CSV in a folder regardless of layout, then cleans, validates, de-duplicates, and merges them into a single dataset, converting all amounts to one currency. It's fully auditable: every repaired or rejected row is logged with a reason, so nothing breaks silently.
The result: a formatted Excel workbook with four sheets (Summary, Clean Data, Rejected Rows, Issue Log), plus CSV exports and a run report. In the bundled sample it merges 3 incompatible files (22 rows) into 9 clean rows, flags 10 invalid records, and removes 3 duplicates. Manual equivalent: ~2 hours per batch; this runs in seconds.
Tech: Python (pandas, openpyxl), config-driven, with unit tests. Built with AI assistance under human supervision.
Steps for completing your project
After purchasing the project, send requirements so Sota can start the project.
Delivery time starts when Sota receives requirements from you.
Sota works on your project following the steps below.
Revisions may occur after the delivery date.
Scope & confirm sources
We confirm your data sources, the exact output you need, and the schedule, then lock the deliverable.
Build the pipeline
I develop the fetch, clean, transform, and load steps, then wire up the scheduled run and error handling.