nanmin#
- coo_matrix.nanmin(axis=None, out=None, *, explicit=False)[source]#
- Return the minimum, ignoring any Nans, along an axis. - Return the minimum, ignoring any Nans, of the array/matrix along an axis. By default this takes all elements into account, but with explicit set, only stored elements are considered. - Added in version 1.11.0. - Parameters:
- axis{-2, -1, 0, 1, None} optional
- Axis along which the minimum is computed. The default is to compute the minimum over all elements, returning a scalar (i.e., axis = None). 
- outNone, optional
- This argument is in the signature solely for NumPy compatibility reasons. Do not pass in anything except for the default value, as this argument is not used. 
- explicit{False, True} optional (default: False)
- When set to True, only the stored elements will be considered. If a row/column is empty, the sparse.coo_array returned has no stored element (i.e. an implicit zero) for that row/column. - Added in version 1.15.0. 
 
- Returns:
- amincoo_array or scalar
- Minimum of a. If axis is None, the result is a scalar value. If axis is given, the result is a sparse.coo_array of dimension - a.ndim - 1.
 
 - See also - nanmax
- The maximum value of a sparse array/matrix along a given axis, ignoring NaNs. 
- min
- The minimum value of a sparse array/matrix along a given axis, propagating NaNs. 
- numpy.nanmin
- NumPy’s implementation of ‘nanmin’.