Matplotlib — Data Visualization

# Description

Data visualization project with matplotlib and seaborn using simulated retail store data (MarketPro, 810 transactions). Learn the 8 essential chart types for Data Science: line charts for time trends, bar charts for comparisons, histograms + KDE for distributions, boxplots for outliers, scatter plots for relationships, heatmaps for correlations, pairplots for complete EDA, and multi-chart dashboards. Includes color theory, annotations, and data storytelling concepts.

$ ./deploy.sh $ git clone

# Key features

$ Line charts with moving averages for time trends

$ Bar charts and grouped bars for categorical comparisons

$ Histograms with KDE for distribution analysis

$ Boxplots for automatic outlier detection

$ Scatter plots with regression lines for variable relationships

$ Correlation heatmaps and pairplots for complete EDA

$ Multi-chart dashboards with subplots

# Gallery

Desktop view

Mobile view

# Technologies used

Python matplotlib seaborn pandas numpy