bundles / numpy 2.5.0.dev0+git20251130.2de293a / numpy / unique
_ArrayFunctionDispatcher
numpy:unique
source: /dev/numpy/build-install/usr/lib/python3.14/site-packages/numpy/lib/_arraysetops_impl.py :145
Signature
def unique ( ar , return_index = False , return_inverse = False , return_counts = False , axis = None , * , equal_nan = True , sorted = True ) Summary
Find the unique elements of an array.
Extended Summary
Returns the sorted unique elements of an array. There are three optional outputs in addition to the unique elements:
the indices of the input array that give the unique values
the indices of the unique array that reconstruct the input array
the number of times each unique value comes up in the input array
Parameters
ar: array_likeInput array. Unless
axisis specified, this will be flattened if it is not already 1-D.return_index: bool, optionalIf True, also return the indices of
ar(along the specified axis, if provided, or in the flattened array) that result in the unique array.return_inverse: bool, optionalIf True, also return the indices of the unique array (for the specified axis, if provided) that can be used to reconstruct
ar.return_counts: bool, optionalIf True, also return the number of times each unique item appears in
ar.axis: int or None, optionalThe axis to operate on. If None,
arwill be flattened. If an integer, the subarrays indexed by the given axis will be flattened and treated as the elements of a 1-D array with the dimension of the given axis, see the notes for more details. Object arrays or structured arrays that contain objects are not supported if theaxiskwarg is used. The default is None.equal_nan: bool, optionalIf True, collapses multiple NaN values in the return array into one.
sorted: bool, optionalIf True, the unique elements are sorted. Elements may be sorted in practice even if
sorted=False, but this could change without notice.
Returns
unique: ndarrayThe sorted unique values.
unique_indices: ndarray, optionalThe indices of the first occurrences of the unique values in the original array. Only provided if
return_indexis True.unique_inverse: ndarray, optionalThe indices to reconstruct the original array from the unique array. Only provided if
return_inverseis True.unique_counts: ndarray, optionalThe number of times each of the unique values comes up in the original array. Only provided if
return_countsis True.
Notes
When an axis is specified the subarrays indexed by the axis are sorted. This is done by making the specified axis the first dimension of the array (move the axis to the first dimension to keep the order of the other axes) and then flattening the subarrays in C order. The flattened subarrays are then viewed as a structured type with each element given a label, with the effect that we end up with a 1-D array of structured types that can be treated in the same way as any other 1-D array. The result is that the flattened subarrays are sorted in lexicographic order starting with the first element.
Examples
import numpy as np np.unique([1, 1, 2, 2, 3, 3]) a = np.array([[1, 1], [2, 3]]) np.unique(a)✓
a = np.array([[1, 0, 0], [1, 0, 0], [2, 3, 4]])
✓np.unique(a, axis=0)
✗a = np.array(['a', 'b', 'b', 'c', 'a']) u, indices = np.unique(a, return_index=True) u indices a[indices]✓
a = np.array([1, 2, 6, 4, 2, 3, 2]) u, indices = np.unique(a, return_inverse=True) u indices u[indices]✓
a = np.array([1, 2, 6, 4, 2, 3, 2]) values, counts = np.unique(a, return_counts=True) values counts✓
np.repeat(values, counts)
✗See also
- repeat
Repeat elements of an array.
- sort
Return a sorted copy of an array.
Aliases
-
numpy.unique