How can I create advanced visualizations using Plotly in Jupyter?

How can I create advanced visualizations using Plotly in Jupyter?

You can create advanced visualizations in Jupyter using Plotly by leveraging its interactive features and customization options. Would you like a specific example?

Yes, can you show me how to create a 3D scatter plot?

Sure! You can use the plotly.express library. Here's a simple example:

import plotly.express as px
import pandas as pd

# Sample data
df = pd.DataFrame({
    'x': [1, 2, 3, 4, 5],
    'y': [5, 4, 3, 2, 1],
    'z': [2, 3, 4, 5, 6]
})

# Create 3D scatter plot
fig = px.scatter_3d(df, x='x', y='y', z='z')
fig.show()

This will create an interactive 3D scatter plot. Would you like to customize it further?

How can I add labels and change the color of the points?

You can add labels and change the color of the points by modifying the scatter_3d function. Here's how:

fig = px.scatter_3d(df, x='x', y='y', z='z',
                     labels={'x': 'X Axis', 'y': 'Y Axis', 'z': 'Z Axis'},
                     color='z',
                     color_continuous_scale='Viridis')
fig.show()

This will label the axes and color the points based on their z-values. Would you like to explore more features?