零和一间preT列二进制和存储作为一个整数列 [英] Interpret columns of zeros and ones as binary and store as an integer column

问题描述

我的零和一的数据帧。我想对待每列如果值是一个整数的二进制重新presentation。是什么让这个转换最简单的方法？

I have a dataframe of zeros and ones. I want to treat each column as if its values were a binary representation of an integer. What is easiest way to make this conversion?

我想这样的：

df = pd.DataFrame([[1, 0, 1], [1, 1, 0], [0, 1, 1], [0, 0, 1]])

print df

   0  1  2
0  1  0  1
1  1  1  0
2  0  1  1
3  0  0  1

转换为：

0    12
1     6
2    11
dtype: int64

尽可能有效地

推荐答案

类似的解决方案，但更多更快的：

Similar solution, but more faster:

print (df.T.dot(1 << np.arange(df.shape[0] - 1, -1, -1)))
0    12
1     6
2    11
dtype: int64

时序

In [81]: %timeit df.apply(lambda col: int(''.join(str(v) for v in col), 2))
The slowest run took 5.66 times longer than the fastest. This could mean that an intermediate result is being cached.
1000 loops, best of 3: 264 µs per loop

In [82]: %timeit (df.T*(1 << np.arange(df.shape[0]-1, -1, -1))).sum(axis=1)
1000 loops, best of 3: 492 µs per loop

In [83]: %timeit (df.T.dot(1 << np.arange(df.shape[0] - 1, -1, -1)))
The slowest run took 6.14 times longer than the fastest. This could mean that an intermediate result is being cached.
1000 loops, best of 3: 204 µs per loop

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