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中丢失了值(最多约30个).我试图使用genfromtxt's filling_missing参数将这些缺失值设置为'0' .这是在Win 7上运行ActiveState ActivePython 2.7 32位的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
结果如下:
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, …我在Python 2.7中运行Numpy 1.6,并且有一些我从另一个模块获得的一维数组.我想把这些数组并打包成一个结构化数组,这样我就可以按名称索引原始的1D数组.我无法弄清楚如何将1D阵列放入2D阵列并使dtype访问正确的数据.我的MWE如下:
>>> import numpy as np
>>>
>>> x = np.random.randint(10,size=3)
>>> y = np.random.randint(10,size=3)
>>> z = np.random.randint(10,size=3)
>>> x
array([9, 4, 7])
>>> y
array([5, 8, 0])
>>> z
array([2, 3, 6])
>>>
>>> w = np.array([x,y,z])
>>> w.dtype=[('x','i4'),('y','i4'),('z','i4')]
>>> w
array([[(9, 4, 7)],
[(5, 8, 0)],
[(2, 3, 6)]],
dtype=[('x', '<i4'), ('y', '<i4'), ('z', '<i4')])
>>> w['x']
array([[9],
[5],
[2]])
>>>
>>> u = np.vstack((x,y,z))
>>> u.dtype=[('x','i4'),('y','i4'),('z','i4')]
>>> u
array([[(9, 4, 7)],
[(5, 8, 0)], …