Lux is a Python library designed to automate data visualization within Pandas DataFrames, streamlining the exploratory data analysis (EDA) process. It automatically generates insightful charts like distributions, correlations, and temporal trends upon displaying a DataFrame, reducing the need for manual plotting code. Users can also save visualizations as interactive HTML reports or export individual charts for further customization using tools like Matplotlib, Seaborn, or Altair. While best suited for Jupyter Notebook environments and smaller datasets, Lux aims to accelerate data understanding and hypothesis building, particularly for learners and researchers.
Learn how to connect several essential tools to develop a simple yet intuitive dashboard using Streamlit, Plotly, DuckDB, and Pandas to visualize data from a JSON file.
The article uses a WSJ measles heatmap to illustrate heatmaps' effectiveness in displaying vaccine impacts on infectious diseases. It guides creating custom colormaps with Matplotlib’s LinearSegmentedColormap and pcolormesh function.
