[英]Pandas series to 2d array
因此,我使用了将2d数组放入Pandas系列的答案, 将 2D numpy数组放入pandas系列。 简而言之,它是
a = np.zeros((5,2))
s = pd.Series(list(a))
现在,将熊猫系列转换回2D阵列最便宜的方法是什么? 如果我尝试s.values
,我会获得带有object
s.values
的数组。
到目前为止,我尝试了np.vstack(s.values)
但它当然会复制数据。
我相信你需要:
a = np.array(s.values.tolist())
print (a)
[[ 0. 0.]
[ 0. 0.]
[ 0. 0.]
[ 0. 0.]
[ 0. 0.]]
a = np.zeros((50000,2))
s = pd.Series(list(a))
In [131]: %timeit (np.vstack(s.values))
10 loops, best of 3: 107 ms per loop
In [132]: %timeit (np.array(s.values.tolist()))
10 loops, best of 3: 19.7 ms per loop
In [133]: %timeit (np.array(s.tolist()))
100 loops, best of 3: 19.6 ms per loop
但如果转置差异很小(但缓存 ):
a = np.zeros((2,50000))
s = pd.Series(list(a))
#print (s)
In [159]: %timeit (np.vstack(s.values))
The slowest run took 23.31 times longer than the fastest. This could mean that an intermediate result is being cached.
10000 loops, best of 3: 55.7 µs per loop
In [160]: %timeit (np.array(s.values.tolist()))
The slowest run took 7.20 times longer than the fastest. This could mean that an intermediate result is being cached.
10000 loops, best of 3: 49.8 µs per loop
In [161]: %timeit (np.array(s.tolist()))
The slowest run took 7.31 times longer than the fastest. This could mean that an intermediate result is being cached.
10000 loops, best of 3: 62.6 µs per loop
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