README.md

metadata

{}

AutoTrain Dataset for project: bam-v2

Dataset Description

This dataset has been automatically processed by AutoTrain for project bam-v2.

Languages

The BCP-47 code for the dataset's language is unk.

Dataset Structure

Data Instances

A sample from this dataset looks as follows:

[
  {
    "feat_unix": 1548158400,
    "feat_date": "2019-01-22 12:00:00",
    "id": "BTC/USD",
    "feat_open": 3543.58,
    "feat_high": 3590.0,
    "feat_low": 3523.1,
    "target": 3557.860107421875,
    "feat_Volume BTC": 3593298.05,
    "feat_Volume USD": 1009.88,
    "feat_Volume U": null,
    "feat_Date": null,
    "feat_Open": null,
    "feat_High": null,
    "feat_Low": null,
    "feat_Adj Close": null,
    "feat_Volume": null
  },
  {
    "feat_unix": 1627473600,
    "feat_date": "2021-07-28 12:00:00",
    "id": "BTC/USD",
    "feat_open": 40786.1,
    "feat_high": 40900.0,
    "feat_low": 39601.35,
    "target": 39708.12109375,
    "feat_Volume BTC": 265.2041301,
    "feat_Volume USD": 10530757.42,
    "feat_Volume U": null,
    "feat_Date": null,
    "feat_Open": null,
    "feat_High": null,
    "feat_Low": null,
    "feat_Adj Close": null,
    "feat_Volume": null
  }
]

Dataset Fields

The dataset has the following fields (also called "features"):

{
  "feat_unix": "Value(dtype='int64', id=None)",
  "feat_date": "Value(dtype='string', id=None)",
  "id": "Value(dtype='string', id=None)",
  "feat_open": "Value(dtype='float64', id=None)",
  "feat_high": "Value(dtype='float64', id=None)",
  "feat_low": "Value(dtype='float64', id=None)",
  "target": "Value(dtype='float32', id=None)",
  "feat_Volume BTC": "Value(dtype='float64', id=None)",
  "feat_Volume USD": "Value(dtype='float64', id=None)",
  "feat_Volume U": "Value(dtype='float64', id=None)",
  "feat_Date": "Value(dtype='string', id=None)",
  "feat_Open": "Value(dtype='float64', id=None)",
  "feat_High": "Value(dtype='float64', id=None)",
  "feat_Low": "Value(dtype='float64', id=None)",
  "feat_Adj Close": "Value(dtype='float64', id=None)",
  "feat_Volume": "Value(dtype='int64', id=None)"
}

Dataset Splits

This dataset is split into a train and validation split. The split sizes are as follow:

Split name	Num samples
train	41362
valid	10349