我正在运行 Python 2.6。我有以下示例，我试图连接 csv 文件中的日期和时间字符串列。根据我设置的 dtype（None vs object），我看到了一些我无法解释的行为差异，请参阅帖子末尾的问题 1 和 2。返回的异常描述性不太强，并且 dtype 文档没有提到当 dtype 设置为 object 时预期的任何特定行为。
这是片段：
#! /usr/bin/python
import numpy as np
# simulate a csv file
from StringIO import StringIO
data = StringIO("""
Title
Date,Time,Speed
,,(m/s)
2012-04-01,00:10, 85
2012-04-02,00:20, 86
2012-04-03,00:30, 87
""".strip())
# (Fail) case 1: dtype=None splicing a column fails
next(data) # eat away the title line
header = [item.strip() for item in next(data).split(',')] # get the headers
arr1 = np.genfromtxt(data, dtype=None, delimiter=',',skiprows=1)# skiprows=1 for the row with units
arr1.dtype.names = header # assign the header to names
# so we can do y=arr['Speed']
y1 = arr1['Speed']
# Q1 IndexError: invalid index
#a1 = arr1[:,0]
#print a1
# EDIT1:
print "arr1.shape "
print arr1.shape # (3,)
# Fails as expected TypeError: unsupported operand type(s) for +: 'numpy.ndarray' and 'numpy.ndarray'
# z1 = arr1['Date'] + arr1['Time']
# This can be workaround by specifying dtype=object, which leads to case 2
data.seek(0) # resets
# (Fail) case 2: dtype=object assign header fails
next(data) # eat away the title line
header = [item.strip() for item in next(data).split(',')] # get the headers
arr2 = np.genfromtxt(data, dtype=object, delimiter=',',skiprows=1) # skiprows=1 for the row with units
# Q2 ValueError: there are no fields define
#arr2.dtype.names = header # assign the header to names. so we can use it to do indexing
# ie y=arr['Speed']
# y2 = arr['Date'] + arr['Time'] # column headings were assigned previously by arr.dtype.names = header
data.seek(0) # resets
# (Good) case 3: dtype=object but don't assign headers
next(data) # eat away the title line
header = [item.strip() for item in next(data).split(',')] # get the headers
arr3 = np.genfromtxt(data, dtype=object, delimiter=',',skiprows=1) # skiprows=1 for the row with units
y3 = arr3[:,0] + arr3[:,1] # slice the columns
print y3
# case 4: dtype=None, all data are ints, array dimension 2-D
# simulate a csv file
from StringIO import StringIO
data2 = StringIO("""
Title
Date,Time,Speed
,,(m/s)
45,46,85
12,13,86
50,46,87
""".strip())
next(data2) # eat away the title line
header = [item.strip() for item in next(data2).split(',')] # get the headers
arr4 = np.genfromtxt(data2, dtype=None, delimiter=',',skiprows=1)# skiprows=1 for the row with units
#arr4.dtype.names = header # Value error
print "arr4.shape "
print arr4.shape # (3,3)
data2.seek(0) # resets
问题 1：在评论 Q1 中，当 dtype=None 时，为什么我不能对列进行切片？这可以通过 a) arr1=np-genfromtxt... 像案例 3 一样使用 dtype=object 进行初始化，b) arr1.dtype.names=... 被注释掉以避免案例 2 中的值错误
问题 2：在评论 Q2 中，为什么我不能在 dtype=object 时设置 dtype.names？
编辑1：
添加了一个案例 4，如果模拟 csv 文件中的值都是整数，则显示数组的维度何时为 2-D。可以对列进行切片，但分配 dtype.names 仍然会失败。
将术语“拼接”更新为“切片”。