Formation 90 min read Data Visualization

📦 Interactive Charts with Plotly

Python & Data Science Chapter : Data Visualization Sub-chapter : Interactive Plotly

Learning objectives

🎯 Objectives:\n
1Create interactive charts\n2. Add interactions\n3. Create dashboards\n4. Export charts

Introduction

📖 Plotly allows creating interactive charts for the web.

Theoretical content

Plotly:\n
PYTHON
\nimport plotly.express as px\nfig = px.line(df, x="date", y="value")\nfig.show()\n

Practical examples

💻 Example: Interactive dashboard\n
PYTHON
\nimport plotly.express as px\npx.line(df, x="month", y="sales").show()\n

Best practices

1Use plotly.express for simple syntax\n✅ 2. Use update_layout for customization\n✅ 3. Add titles and labels\n✅ 4. Export to HTML with fig.write_html()

Common pitfalls

Forgetting to install plotly\n
pip install plotly

Summary

plotly.express: simple interface\n✅ fig.show(): display\n✅ update_layout(): customization\n✅ write_html(): export\n✅ Interactive charts (zoom, hover)

Additional resources

📚 plotly.com/python/getting-started