python-data-cleaning-cheatsheet

This project is based on the 11-step data cleaning framework shared by Data Scientist Dawn Choo (ex-Meta, ex-Amazon).
It summarizes essential steps in preparing messy data for impactful analysis.

Steps Covered

0. Import libraries
1. Understand the data structure
2. Explore the dataset
3. Standardize data formats
4. Remove duplicates
5. Handle missing values
6. Standardize string values
7. Filter out bad data
8. Remove outliers
9. Rename columns
10. Save cleaned data

Technologies Used

• Python
• Pandas
• NumPy
• Seaborn

Usage

To run the example and generate the cleaned dataset:

python data_cleaning_cheatsheet.py

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