> For the complete documentation index, see [llms.txt](https://docs.everesteer.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.everesteer.ai/data.md).

# Data

The served dataset is **Tenzing**. One obfuscated feature set with rank-normalised targets, split three ways. Features are cross-sectionally ranked, quintile-binned, and renamed. Raw institutional data is never exposed through the API or the files.

Each row is keyed by `exped_id` (an expedition: one cross-section). Instrument identifiers are obfuscated and unique per instrument per exped, so you cannot track the same name across expeds. Join on the `id` column of the split you downloaded. Do not hardcode an instrument id.

{% hint style="info" %}
Dataset scale is not published. Do not expect row counts, instrument counts, feature counts, or file sizes on these pages. Read the live schema from `eiq_features.json` or `get_dataset_schema`.
{% endhint %}

<table data-view="cards"><thead><tr><th></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><strong>Splits &#x26; obfuscation</strong></td><td>Train, validation, live, and which one you predict on.</td><td></td></tr><tr><td><strong>Datasets</strong></td><td>What you can download, and how fresh it is.</td><td></td></tr><tr><td><strong>All dataset files</strong></td><td>Every downloadable artifact in the Tenzing tree.</td><td></td></tr><tr><td><strong>Feature groups</strong></td><td>How the feature space is organised.</td><td></td></tr><tr><td><strong>Column definitions</strong></td><td>Schema for Tenzing. Read the live list from `eiq_features.json`.</td><td></td></tr></tbody></table>


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