Task 1 – Data Cleaning: Customer Personality Analysis

Dataset Used

Customer Personality Analysis from Kaggle
Original File: marketing_campaign.csv

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🛠 Tools Used

• Python 3.12
• Pandas
• Jupyter Notebook / VS Code

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Cleaning Steps Performed

1. Loaded dataset using read_csv() with tab separator (\t)
2. Cleaned column names:
   • Lowercased
   • Removed spaces and replaced with underscores
3. Handled missing values:
   • Filled missing income values with the column mean
4. Removed duplicate rows
5. Standardized text fields (education, marital_status)
   • Converted to lowercase, removed extra spaces
6. Converted dt_customer column to datetime format
7. Fixed data types:
   • income as float
   • year_birth as int
8. Saved cleaned data as cleaned_customer_data.csv

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Output Files

• cleaned_customer_data.csv – Cleaned dataset
• Task1.ipynb – Python code
• README.md – This summary document

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##Submission Project for Data Analyst Internship – Task 1