You will get clean, deduplicate, and standardize your messy CSV data with Python
Project details
You will receive clean, consistent, and analysis-ready CSV data processed with Python. I will inspect your files, remove duplicate records, standardize column names and value formats, address missing or inconsistent data according to your rules, and validate the final output. Every package includes the cleaned CSV files and a concise summary of the changes made. The Advanced package also includes a reusable Python cleanup script, helping you repeat the workflow on future data.
Data Tool
PythonWhat's included
| Service Tiers |
Starter
$15
|
Standard
$30
|
Advanced
$60
|
|---|---|---|---|
| Delivery Time | 2 days | 2 days | 3 days |
Number of Revisions | 1 | 1 | 1 |
Number of Pages Mined/Scraped | 0 | 0 | 0 |
Number of Sources Mined/Scraped | 0 | 0 | 0 |
Frequently asked questions
About Dashan
Python CSV Data Cleaning & Automation | Deduplication, Normalization
Beijing, China - 3:40 pm local time
I can:
• remove duplicate rows
• standardize column names, dates, whitespace, and formats
• identify missing values and data-quality issues
• combine or restructure CSV exports
• automate repeatable cleanup tasks with a reusable Python script
• provide a clean output file, summary report, and clear setup notes
I work best on focused, well-defined tasks. Before starting, I confirm the file structure, desired output, and edge cases so the scope stays clear. If your data problem is more complex, I will say so honestly and suggest a practical milestone.
Send a sample file with sensitive data removed, plus a short description of the result you need.
Steps for completing your project
After purchasing the project, send requirements so Dashan can start the project.
Delivery time starts when Dashan receives requirements from you.
Dashan works on your project following the steps below.
Revisions may occur after the delivery date.
Clean and normalize your CSV data
I will inspect the files, remove duplicates, standardize formats and column names, handle missing values as agreed, validate the output, and deliver the cleaned CSV files with a concise summary.