Convert ndarray from float64 to integer


I've got an ndarray in python with a dtype of float64. I'd like to convert the array to be an array of integers. How should I do this?

int() won't work, as it says it can't convert it to a scalar. Changing the dtype field itself obviously doesn't work, as the actual bytes haven't changed. I can't seem to find anything on Google or in the documentation - what's the best way to do this?

This question is tagged with python numpy scipy

~ Asked on 2012-01-13 18:46:48

The Best Answer is


Use .astype.

>>> a = numpy.array([1, 2, 3, 4], dtype=numpy.float64)
>>> a
array([ 1.,  2.,  3.,  4.])
>>> a.astype(numpy.int64)
array([1, 2, 3, 4])

See the documentation for more options.

~ Answered on 2012-01-13 18:52:11


While astype is probably the "best" option there are several other ways to convert it to an integer array. I'm using this arr in the following examples:

>>> import numpy as np
>>> arr = np.array([1,2,3,4], dtype=float)
>>> arr
array([ 1.,  2.,  3.,  4.])

The int* functions from NumPy

>>> np.int64(arr)
array([1, 2, 3, 4])

>>> np.int_(arr)
array([1, 2, 3, 4])

The NumPy *array functions themselves:

>>> np.array(arr, dtype=int)
array([1, 2, 3, 4])

>>> np.asarray(arr, dtype=int)
array([1, 2, 3, 4])

>>> np.asanyarray(arr, dtype=int)
array([1, 2, 3, 4])

The astype method (that was already mentioned but for completeness sake):

>>> arr.astype(int)
array([1, 2, 3, 4])

Note that passing int as dtype to astype or array will default to a default integer type that depends on your platform. For example on Windows it will be int32, on 64bit Linux with 64bit Python it's int64. If you need a specific integer type and want to avoid the platform "ambiguity" you should use the corresponding NumPy types like np.int32 or np.int64.

~ Answered on 2017-09-24 20:01:25

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