为什么 numpy 数组将 int 变成 float [英] Why do numpy array turns int into float

问题描述

我正在尝试用整数填充数组，但似乎 numpy 数组一直在将整数转换为浮点数.为什么会发生这种情况，我该如何阻止?

arr = np.empty(9)arr[3] = 7打印(arr [3])>>>7.0

解决方案

NumPy 数组与 Python 列表不同，只能包含单一类型，(据我所知)在创建时设置.您放入数组的所有内容都会转换为该类型.

默认情况下，数据类型假定为 float.要设置另一种类型，您可以将 dtype 传递给 empty 函数，如下所示:

<预><代码>>>>arr = np.empty(9, dtype=int)>>>arr[3] = 7>>>编曲[3]7

I'm trying to fill an array with integers, but it seems like numpy array keep turning the integers into floats. Why is this happening and how do I stop this?

arr = np.empty(9)
arr[3] = 7
print(arr[3])
>>>7.0

解决方案

NumPy arrays, unlike Python lists, can contain only a single type, which (as far as I know) is set at creation time. Everything you put into the array gets converted to that type.

By default, the data type is assumed to be float. To set another type, you can pass dtype to the empty function like this:

>>> arr = np.empty(9, dtype=int)
>>> arr[3] = 7
>>> arr[3]
7

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