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$
USD
I will clean and structure your dataset using python and pandas
Python, AI Developer, Django, Machine Learning, Data Cleaning
AI graduate from IUB with 2+ years
building Python apps, AI/ML models and data pipelines.
✅ Python and Django backend REST APIs and AWS deployment
✅ AI and ML deep learning, NLP, computer vision
✅ D...
About this Gig
Do you have messy, unorganized data that is hard to analyze or use? I will professionally clean, structure and organize your datasets using Python and Pandas delivering analysis-ready data fast.
What I Fix and Improve:
Standardize and rename column headers
Remove duplicate rows and entries
Handle missing and null values (fill or drop)
Fix inconsistent formatting (dates, numbers, text)
Convert and enforce correct data types per column
Remove unwanted characters, spaces and symbols
Merge, split or restructure columns as needed
Validate data against business rules
Organize data for efficient analysis or ML use
File Formats Supported:
CSV | Excel (.xlsx / .xls) | JSON | TSV | Google Sheets export
My Tools:
Python 3 | Pandas | NumPy | OpenPyXL | Matplotlib (for quick data profile reports)
Why Choose Me?
BS in Artificial Intelligence with professional experience processing large-volume datasets. Previously reduced data error rates by 15% in a production environment. I write clean, well-commented scripts so you understand every transformation applied to your data.
What You Get:
Cleaned, structured dataset in your preferred format
Python script used for cleaning
Platform:
Jupyter Notebook
Development technology:
Python
Expertise:
Formatting
•
Fixing
•
Cleaning
•
Data validation
•
Modeling
FAQ
What size datasets can you handle with Python?
Because I use Python and optimized Pandas configurations, I can handle datasets ranging from small spreadsheets to large, multi-gigabyte files with hundreds of thousands of rows that standard Excel struggles to open.
Do I get to keep the automation code?
Yes, absolutely. Every package includes the clean, well-commented Python source code script (.py or .ipynb notebook) used to clean your data, allowing you to easily reuse it for future files
