<jupyter_start><jupyter_text>![QuantConnect Logo](https://cdn.quantconnect.com/web/i/qc_notebook_logo_rev0.png) Welcome to The QuantConnect Research Page Refer to this page for documentation https://www.quantconnect.com/docsIntroduction-to-Jupyter Contribute to this template file https://github.com/QuantConnect/Lean/blob/master/Jupyter/BasicCSharpQuantBookTemplate.ipynb  QuantBook Basics Start QuantBook- Load "QuantConnect.csx" with all the basic imports- Create a QuantBook instance<jupyter_code>#load "QuantConnect.csx"
var qb = new QuantBook();

// Selecting asset data
var spy = qb.AddEquity("SPY");
var eur = qb.AddForex("EURUSD");
var btc = qb.AddCrypto("BTCUSD");
var fxv = qb.AddData<FxcmVolume>("EURUSD_Vol", Resolution.Hour);<jupyter_output><empty_output><jupyter_text>Historical Data RequestsWe can use the QuantConnect API to make Historical Data Requests. The data will be presented as multi-index pandas.DataFrame where the first index is the Symbol.For more information, please follow the [link](https://www.quantconnect.com/docsHistorical-Data-Historical-Data-Requests).<jupyter_code>// Gets historical data from the subscribed assets, the last 360 datapoints with daily resolution
var h1 = qb.History(qb.Securities.Keys, 360, Resolution.Daily);
Console.WriteLine(string.Join(",", h1.SelectMany(slice => slice.Keys).Distinct()))<jupyter_output><empty_output>
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{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '17812', 'license': 'Apache-2.0', 'n_tokens_mistral': 449, 'n_tokens_neox': 432, 'n_words': 112, 'path': 'Jupyter/BasicCSharpQuantBookTemplate.ipynb', 'repo_name': 'jaderfeijo/Lean', 'size': '1378'}