This repository focuses on data visualization and data preprocessing, essential steps in data analysis and machine learning. We explore various techniques to clean, transform, and visualize data effectively to extract meaningful insights.
- Handling missing values
- Encoding categorical variables
- Feature scaling
- Other data-cleaning techniques
- Graphical representations of the dataset using different visualization techniques such as:
- Histograms
- Bar charts
- Scatter plots
- And more
- Understanding data trends, patterns, and relationships through visualization.
- Python
- Pandas
- Matplotlib
- Seaborn
- NumPy