Data Analysis Projects

This repository contains various data analysis projects that focus on extracting insights and building models using Python libraries.

Projects Overview:

1. Sales Data Analysis
   Analyzing sales trends over time and exploring relationships between region, powertrain type, and sales.

2. Customer Segmentation
   Identifying different customer segments based on purchasing behavior.

3. Market Trends Visualization
   Visualizing key market trends using advanced charting techniques.

4. Regression Analysis
   Implementing regression models to predict and analyze data trends.

Tools and Libraries:

• Pandas: For data manipulation and cleaning.
• NumPy: For numerical computations and handling arrays.
• Matplotlib: For creating static, animated, and interactive visualizations.
• Seaborn: For statistical data visualization and enhanced plotting.
• SciPy: For scientific and technical computing.
• Statsmodels: For statistical models, regression analysis, and hypothesis testing.
• Scikit-learn: For machine learning algorithms, including regression, classification, and clustering.
• Plotly: For interactive plots and dashboards.
• Jupyter Notebook: For creating and sharing live code documents.
• TensorFlow/Keras: For building and training advanced machine learning models (if applicable).

Contact:

Feel free to reach out via [[email protected]] for any suggestions.