Welcome to the advanced Plotly tutorial! Dive deeper into creating sophisticated visualizations with these features:

📊 1. Dynamic Chart Updates

Use plotly.graph_objects to build interactive plots.
Example: 

import plotly.express as px
fig = px.line(df, x='time', y='value', title='Live Data Streaming')
fig.show()
Realtime_Data_Update

🌐 2. Subplots & Layouts

Combine multiple charts in a single figure: 

fig = make_subplots(rows=2, cols=1)
fig.add_trace(go.Scatter(x=[1,2,3], y=[4,5,1]), row=1, col=1)
fig.add_trace(go.Bar(x=[1,2,3], y=[2,3,4]), row=2, col=1)
Subplot_Layouts

🔄 3. Customization & Styling

Enhance your plots with advanced styling options:

  • update_layout() for global theme changes
  • template parameter for pre-defined themes
  • hoverlabel for custom tooltips
Customization_Options

🧠 4. Advanced Interactivity

Add dropdowns, sliders, and range selectors: 

fig.update_layout(updatemenus=[dict(type='dropdown', buttons=[...])])
Interactive_Features

📚 Next Steps

Explore more about Plotly basics at /data_visualization_tutorials/plotly_tutorial or dive into Dash for web apps!