Data Visualization Skill

This skill provides capabilities for creating data visualizations.

Quick Start

Using matplotlib for basic charts:

import matplotlib.pyplot as plt

Simple line chart

plt.plot([1, 2, 3, 4], [1, 4, 2, 3]) plt.title("Sample Chart") plt.savefig("chart.png")

Capabilities

Chart Types

• Line charts

• Bar charts

• Pie charts

• Scatter plots

• Histograms

• Box plots

• Heatmaps

Libraries Supported

• Matplotlib (static charts)

• Seaborn (statistical visualizations)

• Plotly (interactive charts)

• Altair (declarative visualization)

Advanced Features

• Multi-axis plots

• Subplots and grids

• Custom themes and styling

• Annotations and labels

• Export to various formats (PNG, SVG, PDF)

Best Practices

• Choose the right chart type for your data

• Use clear labels and titles

• Consider color accessibility

• Keep visualizations simple and focused

• Export at appropriate resolution for intended use