# Data

Each row of the dataset describes an investment vehicle at a certain date.

Here follows a concise description of the columns of the three files comprising the dataset, `X_train` and `y_train`.

`X_train`:

* `date`: A sequentially increasing integer representing a date. Time between subsequent dates is a constant, denoting an unknown but fixed frequency at which the data is sampled. The initial training dataset is composed of 268 dates. 
* `id`: A unique identifier representing the investment vehicle at a given date. Note that the same asset has a different `id` at each date.
* `0,...,460`: Anonymized features describing an investment vehicle at a given date. Derived from high-quality market data.

`y_train`:

* `date`: Same as in `X_train`.
* `id`: Same as in `X_train`.
* `y`: The target value to predict. It is related to the future performance of the investment vehicle at the given date. The value is normalized between `-1` and `1`.

`X_test`:

* Same structure as `X_train` but comprises only a few dates. This file is used to simulate the submission process locally via `crunch.test()`, or `cruch test`. The aim is to help participants debug their code and have successful submissions. A successful local test usually means no errors during execution on the submission platform.

The dataset is obfuscated.

### Files

* **X\_train.parquet**

<div align="left"><figure><img src="/files/p33CakEpJUQnRmJzPTZB" alt=""><figcaption></figcaption></figure></div>

* **y\_train.parquet**

<div align="left"><figure><img src="/files/C7GUDW7xNF2KneAR0zel" alt="" width="375"><figcaption></figcaption></figure></div>


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.adialab.crunchdao.com/the-tournament/data.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.