genfromtxt()中的NumPy dtype问题，以字节字符串形式读取字符串 [英] NumPy dtype issues in genfromtxt(), reads string in as bytestring

问题描述

我想将标准ascii csv文件读入numpy，该文件由浮点数和字符串组成.

I want to read in a standard-ascii csv file into numpy, which consists of floats and strings.

例如，

ZINC00043096,C.3,C1,-0.1540,methyl
ZINC00043096,C.3,C2,0.0638,methylene
ZINC00043096,C.3,C4,0.0669,methylene
ZINC00090377,C.3,C7,0.2070,methylene
...

无论我尝试什么，生成的数组看起来像

Whatever I tried, the resulting array would look like

例如

all_data = np.genfromtxt(csv_file, dtype=None, delimiter=',')


[(b'ZINC00043096', b'C.3', b'C1', -0.154, b'methyl')
 (b'ZINC00043096', b'C.3', b'C2', 0.0638, b'methylene')
 (b'ZINC00043096', b'C.3', b'C4', 0.0669, b'methylene')

但是，我想保存一个字节-字符串转换步骤，并且想知道如何将字符串列作为常规字符串直接读取.

However, I want to save a step for the byte-string conversion and was wondering how I can read in the string columns as regular string directly.

我尝试了numpy.genfromtxt()文档中的几项内容，例如dtype='S,S,S,f,S'或dtype='a25,a25,a25,f,a25'，但实际上没有任何帮助.

I tried several things from the numpy.genfromtxt() documentation, e.g., dtype='S,S,S,f,S' or dtype='a25,a25,a25,f,a25', but nothing really helped here.

恐怕，但是我想我只是不了解dtype转换的真正工作原理……如果您能在这里给我一些提示，那就太好了！

I am afraid, but I think I just don't understand how the dtype conversion really works...Would be nice if you can give me some hint here!

谢谢

推荐答案

在Python2.7中

In Python2.7

array([('ZINC00043096', 'C.3', 'C1', -0.154, 'methyl'),
       ('ZINC00043096', 'C.3', 'C2', 0.0638, 'methylene'),
       ('ZINC00043096', 'C.3', 'C4', 0.0669, 'methylene'),
       ('ZINC00090377', 'C.3', 'C7', 0.207, 'methylene')], 
      dtype=[('f0', 'S12'), ('f1', 'S3'), ('f2', 'S2'), ('f3', '<f8'), ('f4', 'S9')])

在Python3中

array([(b'ZINC00043096', b'C.3', b'C1', -0.154, b'methyl'),
       (b'ZINC00043096', b'C.3', b'C2', 0.0638, b'methylene'),
       (b'ZINC00043096', b'C.3', b'C4', 0.0669, b'methylene'),
       (b'ZINC00090377', b'C.3', b'C7', 0.207, b'methylene')], 
      dtype=[('f0', 'S12'), ('f1', 'S3'), ('f2', 'S2'), ('f3', '<f8'), ('f4', 'S9')])

Python3中的'regular'字符串是unicode.但是您的文本文件具有字节字符串. all_data在两种情况下都是相同的(136个字节)，但是Python3显示字节字符串的方式是b'C.3'，而不仅仅是'C.3'.

The 'regular' strings in Python3 are unicode. But your text file has byte strings. all_data is the same in both cases (136 bytes), but Python3's way of displaying a byte string is b'C.3', not just 'C.3'.

您打算对这些字符串进行哪些类型的操作? 'ZIN' in all_data['f0'][1]适用于2.7版本，但是在3中必须使用b'ZIN' in all_data['f0'][1].

What kinds of operations do you plan on doing with these strings? 'ZIN' in all_data['f0'][1] works with the 2.7 version, but in 3 you have to use b'ZIN' in all_data['f0'][1].

在numpy中变量/未知长度字符串/unicode dtype 提醒我可以在dtype中指定unicode字符串类型.但是，如果您事先不知道字符串的长度，这将变得更加复杂.

Variable/unknown length string/unicode dtype in numpy reminds me that you can specify a unicode string type in the dtype. However this becomes more complicated if you don't know the lengths of the strings beforehand.

alttype = np.dtype([('f0', 'U12'), ('f1', 'U3'), ('f2', 'U2'), ('f3', '<f8'), ('f4', 'U9')])
all_data_u = np.genfromtxt(csv_file, dtype=alttype, delimiter=',')

生产

array([('ZINC00043096', 'C.3', 'C1', -0.154, 'methyl'),
       ('ZINC00043096', 'C.3', 'C2', 0.0638, 'methylene'),
       ('ZINC00043096', 'C.3', 'C4', 0.0669, 'methylene'),
       ('ZINC00090377', 'C.3', 'C7', 0.207, 'methylene')], 
      dtype=[('f0', '<U12'), ('f1', '<U3'), ('f2', '<U2'), ('f3', '<f8'), ('f4', '<U9')])

在Python2.7中，all_data_u显示为

In Python2.7 all_data_u displays as

(u'ZINC00043096', u'C.3', u'C1', -0.154, u'methyl')

all_data_u是448个字节，因为numpy为每个unicode字符分配4个字节.每个U4项目的长度为16个字节.

all_data_u is 448 bytes, because numpy allocates 4 bytes for each unicode character. Each U4 item is 16 bytes long.

1.14版中的更改: https://docs.scipy.org/doc/numpy/release.html#encoding-argument-for-text-io-functions

Changes in v 1.14: https://docs.scipy.org/doc/numpy/release.html#encoding-argument-for-text-io-functions

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