我正在尝试处理保存为CSV的数据,该数据可能在未知数量的列(最多约30个)中缺失值。我试图使用genfromtxt
的filling_missing
参数将这些缺失值设置为'0'。下面是numpy的1.6.2 ActiveState的ActivePython的运行2.7的32位在Win 7NumPy genfromtxt:正确使用filling_missing
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
而且结果的最小工作示例:
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的用户指南我希望filling_values=0
和filling_values={None:0}
工作,但他们没有,并分别发生错误。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字的列,因此我正在寻找像用户指南提示那样自动设置填充值的方式。
我想我可以提前计数列,并创建一个字典作为值同时传递给filling_values,但有没有更好的方法?
存在一个bug报告:http://projects.scipy.org/numpy/ticket/1722 – Holger 2013-02-28 20:56:25
谢谢,我添加了评论问题上GitHub的bug跟踪系统。 https://github.com/numpy/numpy/issues/2317 – Thav 2013-02-28 23:24:43
这个bug现在已经在numpy的开发版本中修复了:https://github.com/numpy/numpy/pull/4968 – 2014-08-16 10:27:41