Interactive Visualizations with Plotly

Interactive Plots with Plotly

Plotly enables hover tooltips, zoom, and export to HTML.

Installing Plotly

pip install plotly

Simple interactive line chart

import plotly.express as px
import pandas as pd

time = pd.date_range('2024-01-01', periods=12, freq='M')
values = np.random.randn(12).cumsum()
fig = px.line(x=time, y=values, title='Interactive Monthly Trend')
fig.show()

Scatter plot with hover data

fig = px.scatter(df, x='Age', y='Salary', color='Department', hover_data=['Name', 'Experience'])
fig.update_traces(marker=dict(size=12, opacity=0.7))
fig.show()

Bar chart with animation (e.g., yearly sales)

sales = pd.read_csv('sales.csv')
fig = px.bar(sales, x='Month', y='Revenue', color='Region', animation_frame='Year')
fig.show()

Exporting to a standalone HTML file

fig.write_html('interactive_plot.html')

When to choose Plotly

• When you need interactive dashboards.
• For sharing visualizations with non‑technical stakeholders.