nanprod(a, axis=None, dtype=None, out=None, keepdims=<no value>, initial=<no value>, where=<no value>)
One is returned for slices that are all-NaN or empty.
Array containing numbers whose product is desired. If a is not an array, a conversion is attempted.
Axis or axes along which the product is computed. The default is to compute the product of the flattened array.
The type of the returned array and of the accumulator in which the elements are summed. By default, the dtype of a is used. An exception is when a has an integer type with less precision than the platform (u)intp. In that case, the default will be either (u)int32 or (u)int64 depending on whether the platform is 32 or 64 bits. For inexact inputs, dtype must be inexact.
Alternate output array in which to place the result. The default is None
. If provided, it must have the same shape as the expected output, but the type will be cast if necessary. See ufuncs-output-type
for more details. The casting of NaN to integer can yield unexpected results.
If True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the original :None:None:`arr`.
The starting value for this product. See :None:None:`~numpy.ufunc.reduce` for details.
Elements to include in the product. See :None:None:`~numpy.ufunc.reduce` for details.
A new array holding the result is returned unless :None:None:`out` is specified, in which case it is returned.
Return the product of array elements over a given axis treating Not a Numbers (NaNs) as ones.
isnan
Show which elements are NaN.
numpy.prod
Product across array propagating NaNs.
>>> np.nanprod(1) 1
>>> np.nanprod([1]) 1
>>> np.nanprod([1, np.nan]) 1.0
>>> a = np.array([[1, 2], [3, np.nan]])
... np.nanprod(a) 6.0
>>> np.nanprod(a, axis=0) array([3., 2.])See :
The following pages refer to to this document either explicitly or contain code examples using this.
numpy.lib.nanfunctions
dask.array.reductions.nanprod
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