69 articles on data visualization — charts, plots, libraries, best practices, and storytelling with data.
Part of the xbe.at knowledge base. ← Back to index
- Matplotlib: key functions, subplots, mosaic layouts, interactive plots
- Seaborn: enhancing visualizations, statistical plots
- Python visualization ecosystem overview
- Bar plots, line charts, scatter plots, hexbin plots
- Heatmaps, box plots (and their limitations)
- Sankey diagrams, treemaps
- Alternatives to cluttered bar plots
- Avoiding misleading visualizations
- Visual encoding fundamentals
- Highlighting key insights, emphasizing details
- Visualizing high-dimensional data: t-SNE, UMAP, PCA scatter plots
- ROC curves, confusion matrices
- Decision tree visualization in scikit-learn
- K-Means clustering animation, DBSCAN visual demo
- Visualizing embeddings and outliers during fine-tuning
- Grad-CAM for CNN explainability
- Differential geometry, Riemannian manifolds
- Partial differential equations, complex analysis
- Markov processes, skewness in distributions
- Avoiding Misleading Data Visualizations
- Visualizing High-Dimensional Data with t-SNE
- Essential Data Visualization Plots for Data Scientists
- Machine Learning Stacking: A Visual Guide
- Visualizing CNN Decision-Making with Grad-CAM