Python-Projects

Self-explanatory folder structure showcasing the EDA process with visualizations using Python libraries.

Project Structure

• Collect Data: Jupyter notebooks demonstrating data collection techniques.

  • Web scraping using BeautifulSoup
  • API calls with Requests library
  • Data presentation using Pandas

• Clean Data: Jupyter notebooks showing data cleaning processes.

  • Using Pandas & Numpy to clean datasets from CSV files
  • Well-documented with formatted output

• EDA: Exploratory Data Analysis notebooks.

  • Statistical insights on Black Friday Sales & Hotel Booking Demand data
  • Visualizations: Bar charts, Histograms, Box Plots, HeatMaps
  • Libraries used: Pandas, Numpy, Seaborn, Matplotlib, Plotly

• ETL: Extract, Transform, Load projects.

  • ** NEW !!**: Personal Finance Tracker
    • CSV data management for financial transactions
    • User input handling with validation
    • Date range filtering and financial summary generation
    • Data visualization of income and expenses over time
    • Demonstrates ETL processes in a practical application

Tools and Libraries

• Anaconda
• Jupyter Notebook
• Python libraries: BeautifulSoup, Requests, Pandas, Numpy, Seaborn, Matplotlib, Plotly

Notable Projects

EDA - Hotel Booking Demand

View Notebook
(Plotly figures may not display in local notebook)

Skills Demonstrated

• Data collection and web scraping
• Data cleaning and preprocessing
• Exploratory data analysis
• Data visualization
• ETL processes
• Object-Oriented Programming
• Command-line interface design
• File I/O operations
• Error handling and input validation