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# pandas.arrays.BooleanArray

class pandas.arrays.BooleanArray(values, mask, copy=False)

  Array of boolean (True/False) data with missing values.

  This is a pandas Extension array for boolean data, under the hood represented by 2 numpy arrays: a boolean array with the data and a boolean array with the mask (True indicating missing).

  BooleanArray implements Kleene logic (sometimes called three-value logic) for logical operations. See Kleene logical operations for more.

  To construct a BooleanArray from generic array-like input, use `pandas.array()` specifying `dtype="boolean"` (see examples below).

  Warning

  BooleanArray is considered experimental. The implementation and parts of the API may change without warning.

  Parameters:
    values numpy.ndarray

      A 1-d boolean-dtype array with the data.

    mask numpy.ndarray

      A 1-d boolean-dtype array indicating missing values (True indicates missing).

    copy bool, default False

      Whether to copy the values and mask arrays.

  Attributes

  None |

  Methods

  None |

  Returns:
    BooleanArray

  See also

  `array`

    Create an array from data with the appropriate dtype.

  `BooleanDtype`

    Extension dtype for boolean data.

  `Series`

    One-dimensional ndarray with axis labels (including time series).

  `DataFrame`

    Two-dimensional, size-mutable, potentially heterogeneous tabular data.

  Examples

  Create a BooleanArray with `pandas.array()`:

      >>> pd.array([True, False, None], dtype="boolean")
      <BooleanArray>
      [True, False, <NA>]
      Length: 3, dtype: boolean