Data Analyst Portfolio Projects

Welcome to my portfolio!
I'm Neslihan, a data analyst passionate about turning data into insights. This repository showcases a collection of hands-on analytics projects using MySQL, Excel, Tableau, and Python, covering data cleaning, exploration, visualization, and storytelling.

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📁 Projects

SQL-Based Projects

1. SQL – Layoffs Data Cleaning

Dataset: Layoffs.csv
Used MySQL to clean a global layoffs dataset:

• Removed duplicates, nulls
• Standardized string formats
• Created clean output tables
  📄 View SQL Script

2. SQL – Layoffs Exploratory Data Analysis (EDA)

Tools: MySQL
Uncovered insights on layoffs by company, region, industry:

• Used CTEs, subqueries, window functions
• Trend analysis by funding stage
  📄 View SQL Script

Dashboarding Projects

3. Excel Dashboard – Bike Sales

Tool: Microsoft Excel
Built an interactive dashboard using:

• Pivot tables & slicers
• Customer segment and sales insights
  📄 View Excel

4. Airbnb Tableau Dashboard

Tool: Tableau
Visualized Seattle Airbnb listings:

• Price heatmaps by ZIP code
• Host ratings vs. price and reviews
• Interactive filters for users
  📄 View on Tableau Public

Python-Based Projects

5. 🎬 Python – Movie Correlation Analysis

Tools: Jupyter Notebook, pandas, seaborn,
Analyzed movie metadata from Kaggle to explore:

• Which features (like budget, company, genre) correlate with gross earnings
• Regression plots and heatmaps
• Categorical encoding and feature engineering
  📄 View project

6. Python – Customer Call List Cleaning

Tools: Jupyter Notebook, pandas
Cleaned and transformed a messy Excel file using pandas:

• Removed duplicates and irrelevant columns
• Cleaned phone numbers and standardized formatting
• Dropped "Do Not Contact" customers
  📄 View project

7. Python – World Population EDA

Tools: Jupyter Notebook, pandas, matplotlib, seaborn
Performed exploratory analysis on world population trends:

• Regional distribution
• Top countries by growth
• Time-based visualizations and statistical summaries
  📄 View project

8. Python – Book Data Web Scraping

Tools: Jupyter Notebook, requests, BeautifulSoup, pandas
Scraped book listings from BooksToScrape.com:

• Collected titles, prices, and star ratings
• Parsed HTML across multiple pages
• Stored results in a pandas DataFrame
  📄 View project

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🛠 Tools & Skills Demonstrated

• Python: pandas, seaborn, matplotlib, BeautifulSoup, requests
• SQL: cleaning, aggregations, joins, window functions
• Excel: dashboarding, pivot tables, slicers
• Tableau: geospatial and categorical dashboards
• Version Control: Git & GitHub