使用genfromtxt分割数据 [英] using genfromtxt to split data

问题描述

使用Python，我正在使用genfromtxt(来自numpy)将文本文件读入数组:

With Python, I am using genfromtxt (from numpy) to read in a text file into an array:

y = np.genfromtxt("1400list.txt", dtype=[('mystring','S20'),('myfloat','float')])

这行得通，但是似乎没有将我的2列读入2D数组中.我得到了:

Which works okay, except it doesn't seem to read my 2 columns into a 2D array. I am getting:

[('string001', 123.0),('string002', 456.0),('string002', 789.0)]

但是我认为想:

[['string001', 123.0],['string002', 456.0],['string002', 789.0]]

我基本上希望每条信息都是一个单独的元素，然后可以对其进行操作.

I basically want each piece of information as a separate element that I can then manipulate.

推荐答案

genfromtxt返回的内容称为结构化数组.它给出一个一维元组数组，每个元组都具有您指定的dtype.

What genfromtxt returns is called a structured array. It gives a 1d array of tuples, each tuple has the dtype that you specified.

一旦您学会了如何使用它们，它们实际上将非常有用.您不能使用带有浮点数和字符串的2d数组，但是可以使用结构化数组！

These are actually very useful once you learn how to use them. You cannot have a 2d array with floats and strings, but with a structured array, you can!

例如:

import numpy as np
from StringIO import StringIO
s = """string001 123
       string002 456
       string002 789"""
f = StringIO(s)
y = np.genfromtxt(f, dtype=[('mystring', 'S20'), ('myfloat', float)])

到目前为止，您所拥有的是什么.现在，您可以按照以下方式访问y.您可以使用字段名称将一列作为一维数组:

Which is what you have so far. Now you can access y in the following fashion. You can use a field name to get a column as a 1d array:

>>> y['mystring']
array(['string001', 'string002', 'string002'], 
  dtype='|S20')

>>> y['myfloat']
array([ 123.,  456.,  789.])

请注意，由于dtype参数，y['myfloat']给出了float，即使在文件中它们是int.

Note that y['myfloat'] gives floats because of the dtype argument, even though in the file they are ints.

或者，您可以使用整数以给定的dtype将行作为tuple:

Or, you can use an integer to get a row as a tuple with the given dtype:

>>> y[1]
('string002', 456.0)

如果您要对这样的数据结构进行大量处理，则可能需要研究 pandas

If you are doing a lot of manipulation of data structures like this, you might want to look into pandas

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