genfromtext值错误:得到n列而不是1列

Question

我使用numpy。genfromtxt从csv文件中导入数据列作为变量两次(每列对应不同的变量x和y)。我得到一个值错误:(得到3列而不是1)即使我指定使用哪一列。代码如下:

import numpy as np
file = 'E:/TPA/AOM_8.csv'
file = os.path.normpath(file)
x = np.genfromtxt(file, delimiter=',', usecols=1, skip_header=9)
print(x)
y = np.genfromtxt(file, delimiter=',', usecols=3, skip_header=9)
print(y)  

奇怪的是，代码在打印'x'时没有问题，但在打印'y'时却有问题。如果我把y改成

y = np.genfromtxt(file, delimiter=',', usecols=2, skip_header=9)

那么就可以了

文件示例如下:

ASCII data file created with TiePie Multi Channel software. www.tiepie.com.
2021-08-27 18:25:57 437m


Sample number,Relative time,Data collector1,Data collector2
,s,V,V
0,0,4.0176473,6.1250002
1,1E-5,4.0078434,6.0784316
2,2E-5,4.001961,6.1274512
3,3E-5,4.029412,6.0980394
4,4E-5,4.0333336,6.1274512
5,5E-5,4.0009806,6.1446081
6,6E-5,4.0205885,6.1274512
7,7E-5,4.0098042,6.1299022
8,8E-5,4.0058826,6.1078434
9,9E-5,4.0098042,6.154412
10,0.0001,4.0225493,6.1053924
11,0.00011,4.0323532,6.0588237
12,0.00012,4.0147061,6.1421571

Answer 1

我没有问题:

In [710]: txt='''ASCII data file created with TiePie Multi Channel software. www
...: .tiepie.com.
...: 2021-08-27 18:25:57 437m
...: 
...: 
...: 
...: 
...: 
...: Sample number,Relative time,Data collector1,Data collector2
...:  ,s,V,V
...: 0,0,4.0176473,6.1250002
...: 1,1E-5,4.0078434,6.0784316
...: 2,2E-5,4.001961,6.1274512
...: 3,3E-5,4.029412,6.0980394
...: 4,4E-5,4.0333336,6.1274512
...: 5,5E-5,4.0009806,6.1446081
...: 6,6E-5,4.0205885,6.1274512
...: 7,7E-5,4.0098042,6.1299022
...: 8,8E-5,4.0058826,6.1078434
...: 9,9E-5,4.0098042,6.154412
...: 10,0.0001,4.0225493,6.1053924
...: 11,0.00011,4.0323532,6.0588237
...: 12,0.00012,4.0147061,6.1421571'''
In [711]: txt=txt.splitlines()
In [712]: len(txt)
Out[712]: 22

all of it:

In [713]: data = np.genfromtxt(txt, delimiter=',', skip_header=9)
In [714]: data
Out[714]: 
array([[0.0000000e+00, 0.0000000e+00, 4.0176473e+00, 6.1250002e+00],
[1.0000000e+00, 1.0000000e-05, 4.0078434e+00, 6.0784316e+00],
[2.0000000e+00, 2.0000000e-05, 4.0019610e+00, 6.1274512e+00],
[3.0000000e+00, 3.0000000e-05, 4.0294120e+00, 6.0980394e+00],
[4.0000000e+00, 4.0000000e-05, 4.0333336e+00, 6.1274512e+00],
[5.0000000e+00, 5.0000000e-05, 4.0009806e+00, 6.1446081e+00],
[6.0000000e+00, 6.0000000e-05, 4.0205885e+00, 6.1274512e+00],
[7.0000000e+00, 7.0000000e-05, 4.0098042e+00, 6.1299022e+00],
[8.0000000e+00, 8.0000000e-05, 4.0058826e+00, 6.1078434e+00],
[9.0000000e+00, 9.0000000e-05, 4.0098042e+00, 6.1544120e+00],
[1.0000000e+01, 1.0000000e-04, 4.0225493e+00, 6.1053924e+00],
[1.1000000e+01, 1.1000000e-04, 4.0323532e+00, 6.0588237e+00],
[1.2000000e+01, 1.2000000e-04, 4.0147061e+00, 6.1421571e+00]])

单一列:

In [715]: x = np.genfromtxt(txt, delimiter=',', skip_header=9,usecols=1)
In [716]: x
Out[716]: 
array([0.0e+00, 1.0e-05, 2.0e-05, 3.0e-05, 4.0e-05, 5.0e-05, 6.0e-05,
7.0e-05, 8.0e-05, 9.0e-05, 1.0e-04, 1.1e-04, 1.2e-04])
In [717]: x = np.genfromtxt(txt, delimiter=',', skip_header=9,usecols=2)
In [718]: x = np.genfromtxt(txt, delimiter=',', skip_header=9,usecols=3)
In [719]: x
Out[719]: 
array([6.1250002, 6.0784316, 6.1274512, 6.0980394, 6.1274512, 6.1446081,
6.1274512, 6.1299022, 6.1078434, 6.154412 , 6.1053924, 6.0588237,
6.1421571])