numpy.nansum#

numpy.nansum(a,axis=None,dtype=None,out=None,keepdims=<novalue>,initial=<novalue>,where=<novalue>)[source]#

Return the sum of array elements over a given axis treating Not aNumbers (NaNs) as zero.

In NumPy versions <= 1.9.0 Nan is returned for slices that are all-NaN orempty. In later versions zero is returned.

Parameters:
aarray_like

Array containing numbers whose sum is desired. Ifa is not anarray, a conversion is attempted.

axis{int, tuple of int, None}, optional

Axis or axes along which the sum is computed. The default is to compute thesum of the flattened array.

dtypedata-type, optional

The type of the returned array and of the accumulator in which theelements are summed. By default, the dtype ofa is used. Anexception is whena has an integer type with less precision thanthe platform (u)intp. In that case, the default will be either(u)int32 or (u)int64 depending on whether the platform is 32 or 64bits. For inexact inputs, dtype must be inexact.

outndarray, optional

Alternate output array in which to place the result. The defaultisNone. If provided, it must have the same shape as theexpected output, but the type will be cast if necessary. SeeOutput type determination for more details. The casting of NaN to integercan yield unexpected results.

keepdimsbool, optional

If this is set to True, the axes which are reduced are leftin the result as dimensions with size one. With this option,the result will broadcast correctly against the originala.

If the value is anything but the default, thenkeepdims will be passed through to themean orsum methodsof sub-classes ofndarray. If the sub-classes methodsdoes not implementkeepdims any exceptions will be raised.

initialscalar, optional

Starting value for the sum. Seereduce for details.

New in version 1.22.0.

wherearray_like of bool, optional

Elements to include in the sum. Seereduce for details.

New in version 1.22.0.

Returns:
nansumndarray.

A new array holding the result is returned unlessout isspecified, in which it is returned. The result has the samesize asa, and the same shape asa ifaxis is not Noneora is a 1-d array.

See also

numpy.sum

Sum across array propagating NaNs.

isnan

Show which elements are NaN.

isfinite

Show which elements are not NaN or +/-inf.

Notes

If both positive and negative infinity are present, the sum will be NotA Number (NaN).

Examples

>>>importnumpyasnp>>>np.nansum(1)1>>>np.nansum([1])1>>>np.nansum([1,np.nan])1.0>>>a=np.array([[1,1],[1,np.nan]])>>>np.nansum(a)3.0>>>np.nansum(a,axis=0)array([2.,  1.])>>>np.nansum([1,np.nan,np.inf])inf>>>np.nansum([1,np.nan,-np.inf])-inf>>>fromnumpy.testingimportsuppress_warnings>>>withnp.errstate(invalid="ignore"):...np.nansum([1,np.nan,np.inf,-np.inf])# both +/- infinity presentnp.float64(nan)
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