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scikit-learn 1.3.2
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# `sklearn.datasets`.fetch_covtype

sklearn.datasets.fetch_covtype(*, data_home=None, download_if_missing=True, random_state=None, shuffle=False, return_X_y=False, as_frame=False)

  Load the covertype dataset (classification).

  Download it if necessary.

  Classes | 7
  Samples total | 581012
  Dimensionality | 54
  Features | int

  Read more in the User Guide.

  Parameters:
    data_home str or path-like, default=None

      Specify another download and cache folder for the datasets. By default all scikit-learn data is stored in ‘~/scikit_learn_data’ subfolders.

    download_if_missing bool, default=True

      If False, raise an OSError if the data is not locally available instead of trying to download the data from the source site.

    random_state int, RandomState instance or None, default=None

      Determines random number generation for dataset shuffling. Pass an int for reproducible output across multiple function calls. See Glossary.

    shuffle bool, default=False

      Whether to shuffle dataset.

    return_X_y bool, default=False

      If True, returns `(data.data, data.target)` instead of a Bunch object.

      New in version 0.20.

    as_frame bool, default=False

      If True, the data is a pandas DataFrame including columns with appropriate dtypes (numeric). The target is a pandas DataFrame or Series depending on the number of target columns. If `return_X_y` is True, then (`data`, `target`) will be pandas DataFrames or Series as described below.

      New in version 0.24.

  Returns:
    dataset `Bunch`

      Dictionary-like object, with the following attributes.

      datandarray of shape (581012, 54)

        Each row corresponds to the 54 features in the dataset.

      targetndarray of shape (581012,)

        Each value corresponds to one of the 7 forest covertypes with values ranging between 1 to 7.

      framedataframe of shape (581012, 55)

        Only present when `as_frame=True`. Contains `data` and `target`.

      DESCRstr

        Description of the forest covertype dataset.

      feature_nameslist

        The names of the dataset columns.

      target_names: list

        The names of the target columns.

    (data, target)tuple if `return_X_y` is True

      A tuple of two ndarray. The first containing a 2D array of shape (n_samples, n_features) with each row representing one sample and each column representing the features. The second ndarray of shape (n_samples,) containing the target samples.

      New in version 0.20.

## Examples using `sklearn.datasets.fetch_covtype`

Release Highlights for scikit-learn 0.24

Release Highlights for scikit-learn 0.24

Scalable learning with polynomial kernel approximation

Scalable learning with polynomial kernel approximation

Evaluation of outlier detection estimators

Evaluation of outlier detection estimators