将具有 None 值的 python 列表转换为具有 nan 值的 numpy 数组
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Convert python list with None values to numpy array with nan values
提问by Akavall
I am trying to convert a list that contains numeric values and Nonevalues to numpy.array, such that Noneis replaces with numpy.nan.
我正在尝试将包含数值和None值的列表转换为numpy.array，从而None替换为numpy.nan.
For example:
例如：
my_list = [3,5,6,None,6,None]
# My desired result:
my_array = numpy.array([3,5,6,np.nan,6,np.nan])
Naive approach fails:
天真的方法失败：
>>> my_list
[3, 5, 6, None, 6, None]
>>> np.array(my_list)
array([3, 5, 6, None, 6, None], dtype=object) # very limited
>>> _ * 2
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: unsupported operand type(s) for *: 'NoneType' and 'int'
>>> my_array # normal array can handle these operations
array([ 3., 5., 6., nan, 6., nan])
>>> my_array * 2
array([ 6., 10., 12., nan, 12., nan])
What is the best way to solve this problem?
解决这个问题的最佳方法是什么？
采纳答案by Jaime
You simply have to explicitly declare the data type:
您只需显式声明数据类型：
>>> my_list = [3, 5, 6, None, 6, None]
>>> np.array(my_list, dtype=np.float)
array([ 3., 5., 6., nan, 6., nan])
回答by Udo Klein
What about
关于什么
my_array = np.array(map(lambda x: numpy.nan if x==None else x, my_list))
