---
title: "Research Environment"
description: "Learn how to create and conduct research with jupyter notebook in QuantConnect."
canonical: https://www.quantconnect.com/docs/v2/research-environment
markdown: https://www.quantconnect.com/docs/v2/research-environment.md
language: python
source: https://github.com/QuantConnect/Documentation/tree/master/04%20Research%20Environment
modified: 2026-11-01
index: https://www.quantconnect.com/llms.txt
---

# Research Environment

[Documentation](https://www.quantconnect.com/docs/v2.md) > Research Environment

> Code examples are shown in Python. Append `?lang=csharp` to this URL for the C# version of this page.

![](https://cdn.quantconnect.com/i/tu/docs-research-icon.svg)

### Research Environment

### Powerful notebooks attached to our massive data repository

### 400TB of Financial and Alt Data, Dig In

Our data repository is preformatted and ready to go. Skip expensive and tedious data processing and get to work.

[Get Started](https://www.quantconnect.com/docs/v2/research-environment/key-concepts/getting-started.md) [Download PDF](https://cdn.quantconnect.com/docs/i/Quantconnect-Research-Environment-Python.pdf)

![Research Environment](https://cdn.quantconnect.com/i/tu/header-img-research.webp)

#### IN THIS SECTION

[Getting Started](https://www.quantconnect.com/docs/v2/research-environment/key-concepts/getting-started.md) [Research Engine](https://www.quantconnect.com/docs/v2/research-environment/key-concepts/research-engine.md) [Requesting Historical Data](https://www.quantconnect.com/docs/v2/research-environment/datasets/key-concepts.md) [Machine Learning](https://www.quantconnect.com/docs/v2/research-environment/machine-learning/key-concepts.md)

---

- [Key Concepts](https://www.quantconnect.com/docs/v2/research-environment/key-concepts/getting-started.md): Learn the key concepts before starting your research
- [Initialization](https://www.quantconnect.com/docs/v2/research-environment/initialization.md): The starting point of all notebooks
- [Datasets](https://www.quantconnect.com/docs/v2/research-environment/datasets/key-concepts.md): Request historical data
- [Charting](https://www.quantconnect.com/docs/v2/research-environment/charting.md): Visualize data with charting libraries supported by Jupyter
- [Indicators](https://www.quantconnect.com/docs/v2/research-environment/indicators.md): LEAN provides more than 100 pre-built technical indicators and candlestick patterns
- [Object Store](https://www.quantconnect.com/docs/v2/research-environment/object-store.md): File system that you can use in your notebook to save, read, and delete data
- [Machine Learning](https://www.quantconnect.com/docs/v2/research-environment/machine-learning/key-concepts.md): Use machine learning to test your hypothesis
- [Debugging](https://www.quantconnect.com/docs/v2/research-environment/debugging.md): Detect and fix coding errors in your notebooks
- [Meta Analysis](https://www.quantconnect.com/docs/v2/research-environment/meta-analysis/key-concepts.md): Learn how to analyze backtest, optimization, and live trading results.
- [Applying Research](https://www.quantconnect.com/docs/v2/research-environment/applying-research/key-concepts.md): Collection of tutorials written by the QuantConnect team and community members.

## Pages in This Section

- [Key Concepts](https://www.quantconnect.com/docs/v2/research-environment/key-concepts/getting-started.md): Learn how to create and conduct research with jupyter notebook in QuantConnect.
- [Initialization](https://www.quantconnect.com/docs/v2/research-environment/initialization.md): Learn how to set the notebook dates, add data subscriptions, and set the time zone in the research environment in QuantConnect.
- [Datasets](https://www.quantconnect.com/docs/v2/research-environment/datasets/key-concepts.md): Learn data available in the research environment in QuantConnect, and how to request and handle them.
- [Charting](https://www.quantconnect.com/docs/v2/research-environment/charting.md): Learn how to chart data in the research environment in QuantConnect with supported libraries.
- [Universes](https://www.quantconnect.com/docs/v2/research-environment/universes.md): Universe selection is the process of selecting a basket of assets to research. Dynamic universe selection decreases selection bias in your analysis.
- [Indicators](https://www.quantconnect.com/docs/v2/research-environment/indicators.md): Learn how to create, update, and read different types of indicators in the research environment in QuantConnect.
- [Object Store](https://www.quantconnect.com/docs/v2/research-environment/object-store.md): Learn how to access object store in the research environment in QuantConnect, and save/load items from it.
- [Machine Learning](https://www.quantconnect.com/docs/v2/research-environment/machine-learning/key-concepts.md)
- [Debugging](https://www.quantconnect.com/docs/v2/research-environment/debugging.md): The debugger enables you to slow down the code execution, step through the program line-by-line, and inspect the variables to understand the notebook state.
- [Meta Analysis](https://www.quantconnect.com/docs/v2/research-environment/meta-analysis/key-concepts.md)
- [Applying Research](https://www.quantconnect.com/docs/v2/research-environment/applying-research/key-concepts.md): Some example tutorials on how to conduct a research and apply the result into backtesting/live trading.