Data Notebooks: Jupyter for Markets
Announcing our new interactive data notebooks — a Jupyter-style environment built specifically for prediction market analysis and backtesting. Pre-connected to live odds data. Write Python, query markets, visualize results.
Today we're launching EVSignals Data Notebooks — a Jupyter-style interactive computing environment built specifically for prediction market analysis.
What are Data Notebooks?
Think of them as Jupyter notebooks, but pre-connected to live and historical prediction market data. No environment setup, no API key management, no dependency installation. Open a notebook and start querying markets immediately.
Every notebook comes with:
- Python & SQL support — Write analysis in whichever language you prefer
- Pre-loaded market data — Live odds from 500+ sources, available via
import evsignals - Built-in visualization — Market-specific charting for probability timelines, odds distributions, and cross-platform comparisons
- Backtesting utilities — Test strategies against historical settlement data with one function call
- Collaboration — Share notebooks with your team or publish them publicly
Example: Finding +EV in 5 lines
from evsignals import scanner
# Find all markets where cross-platform spread > 5%
opportunities = scanner.find(
min_spread=0.05,
min_volume=10000,
platforms=["kalshi", "polymarket"]
)
opportunities.head(10)
Pricing
Data Notebooks are included in all EVSignals plans, including the free trial. Starter plans include 50 compute hours/month; Pro and Enterprise plans include unlimited compute.
Start your free trial to try notebooks today.