我正在尝试处理保存到 CSV 的数据，这些数据可能在未知数量的列（最多约 30 个）中缺少值。我正在尝试使用genfromtxt'filling_missing参数将这些缺失值设置为 '0'。这是在 Win 7 上的 ActiveState ActivePython 2.7 32 位中运行的 numpy 1.6.2 的最小工作示例。
import numpy
text = "a,b,c,d\n1,2,3,4\n5,,7,8"
a = numpy.genfromtxt('test.txt',delimiter=',',names=True)
b = open('test.txt','w')
b.write(text)
b.close()
a = numpy.genfromtxt('test.txt',delimiter=',',names=True)
print "plain",a
a = numpy.genfromtxt('test.txt',delimiter=',',names=True,filling_values=0)
print "filling_values=0",a
a = numpy.genfromtxt('test.txt',delimiter=',',names=True,filling_values={1:0})
print "filling_values={1:0}",a
a = numpy.genfromtxt('test.txt',delimiter=',',names=True,filling_values={0:0})
print "filling_values={0:0}",a
a = numpy.genfromtxt('test.txt',delimiter=',',names=True,filling_values={None:0})
print "filling_values={None:0}",a
结果：
plain [(1.0, 2.0, 3.0, 4.0) (5.0, nan, 7.0, 8.0)]
filling_values=0 [(1.0, 2.0, 3.0, 4.0) (5.0, nan, 7.0, 8.0)]
filling_values={1:0} [(1.0, 2.0, 3.0, 4.0) (5.0, 0.0, 7.0, 8.0)]
filling_values={0:0} [(1.0, 2.0, 3.0, 4.0) (5.0, nan, 7.0, 8.0)]
Traceback (most recent call last):
File "C:\Users\tolivo.EE\Documents\active\eng\python\sizer\testGenfromtxt.py", line 20, in <module>
a = numpy.genfromtxt('test.txt',delimiter=',',names=True,filling_values={None:0})
File "C:\Users\tolivo.EE\AppData\Roaming\Python\Python27\site-packages\numpy\lib\npyio.py", line 1451, in genfromtxt
filling_values[key] = val
TypeError: list indices must be integers, not NoneType
从 NumPy 用户指南中，我希望filling_values=0并且filling_values={None:0}可以工作，但他们没有，并且分别抛出错误。当您指定正确的列 ( filling_values={1:0}) 时，它将起作用，但由于在用户选择之前我有大量未知数的列，我正在寻找自动设置填充值的方法，就像用户指南提示的那样。
I imagine I can probably count the columns in advance and create a dict to pass as the value to filling_values in the meantime, but is there a better way?