numpy/pandas:如何将一系列由零和一组成的字符串转换为矩阵 [英] numpy/pandas: How to convert a series of strings of zeros and ones into a matrix

问题描述

我有一个以以下格式到达的数据:

I have a data that arrives in this format:

[
  (1, "000010101001010101011101010101110101", "aaa", ... ),
  (0, "111101010100101010101110101010111010", "bb", ... ),
  (0, "100010110100010101001010101011101010", "ccc", ... ),
  (1, "000010101001010101011101010101110101", "ddd", ... ),
  (1, "110100010101001010101011101010111101", "eeee", ... ),
  ...
]

以元组格式，看起来像这样:

In tuple format, it looks like this:

(Y, X, other_info, ... )

最后，我需要使用Y和X训练分类器(例如sklearn.linear_model.logistic.LogisticRegression).

At the end of the day, I need to train a classifier (e.g. sklearn.linear_model.logistic.LogisticRegression) using Y and X.

将一和零的字符串转换为类似np.array的最直接的方法是什么，以便我可以通过分类器运行它?似乎这里应该有一个简单的答案，但我一直没想到/谷歌.

What's the most straightforward way to turn the string of ones and zeros into something like a np.array, so that I can run it through the classifier? Seems like there should be an easy answer here, but I haven't been able to think of/google one.

一些注意事项:

• 我已经在使用numpy/pandas/sklearn，所以这些库中的任何东西都是公平的游戏.
• 对于我正在做的很多事情，将other_info列一起放在DataFrame中很方便
• 字符串很长(〜20,000列)，但总数据帧不是很高(〜500行).

推荐答案

由于您主要要求将一串和零串转换为numpy数组的方法，因此，我将提供以下解决方案:

Since you asked primarily for a way to convert a string of ones and zeros into a numpy array, I'll offer my solution as follows:

d = '0101010000' * 2000 # create a 20,000 long string of 1s and 0s
d_array = np.fromstring(d, 'int8') - 48 # 48 is ascii 0. ascii 1 is 49

就速度而言，这比 @DSM的解决方案更有利:

This compares favourable to @DSM's solution in terms of speed:

In [21]: timeit numpy.fromstring(d, dtype='int8') - 48
10000 loops, best of 3: 35.8 us per loop

In [22]: timeit numpy.fromiter(d, dtype='int', count=20000)
100 loops, best of 3: 8.57 ms per loop

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