使用numpy.loadtxt()将文本文件加载为字符串 [英] Load text file as strings using numpy.loadtxt()

问题描述

我想加载一个大文本文件(大约1GB，具有3 * 10 ^ 6行和10-100列)，作为包含字符串的2D np数组.但是，似乎numpy.loadtxt()仅将浮点数作为默认值.是否可以为整个数组指定其他数据类型?我已经尝试过以下方法，但是没有运气:

I would like to load a big text file (around 1 GB with 3*10^6 rows and 10 - 100 columns) as a 2D np-array containing strings. However, it seems like numpy.loadtxt() only takes floats as default. Is it possible to specify another data type for the entire array? I've tried the following without luck:

loadedData = np.loadtxt(address, dtype=np.str)

我收到以下错误消息:

/Library/Python/2.7/site-packages/numpy-1.8.0.dev_20224ea_20121123-py2.7-macosx-10.8-x86_64.egg/numpy/lib/npyio.pyc in loadtxt(fname, dtype, comments, delimiter, converters, skiprows, usecols, unpack, ndmin)
    833             fh.close()
    834
--> 835     X = np.array(X, dtype)
    836     # Multicolumn data are returned with shape (1, N, M), i.e.
    837     # (1, 1, M) for a single row - remove the singleton dimension there

ValueError: cannot set an array element with a sequence

有什么想法吗? (我事先不知道文件中的确切列数.)

Any ideas? (I don't know the exact number of columns in my file on beforehand.)

推荐答案

使用使用文件col.txt:

foo bar
cat dog
man wine

这给出了:

[['foo' 'bar']
 ['cat' 'dog']
 ['man' 'wine']]

如果您希望每一行具有相同的列数，请阅读第一行并设置属性filling_values来修复所有丢失的行.

If you expect that each row has the same number of columns, read the first row and set the attribute filling_values to fix any missing rows.

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