如何将一系列数组转换为2D numpy数组

Question

Is there a way to convert a Pandas Series where each row contains an array into a 2D numpy array?

The Series looks like the following below when you display it in Python:

[array([ 58.,  -1.,  -1.,  -1.,  -1.])
 array([ 77.,  95.,  -1.,  -1.,  -1.])]

I would like to get a numpy matrix that looks like this:

[[ 58.,  -1.,  -1.,  -1.,  -1.]
 [ 77.,  95.,  -1.,  -1.,  -1.]]

Is there a simple way to do this? Any help is appreciated!

Answer 1

import pandas as pd
import numpy as np

s = pd.Series([np.array([ 58.,  -1.,  -1.,  -1.,  -1.]),
               np.array([ 77.,  95.,  -1.,  -1.,  -1.])])      

rslt = np.array(s.tolist())


rslt
Out[16]: 
array([[ 58.,  -1.,  -1.,  -1.,  -1.],
       [ 77.,  95.,  -1.,  -1.,  -1.]])

Answer 2

l = [pd.Series([np.array([ 77.,  95.,  -1.,  -1.,  -1.]),np.array([ 58.,  -1.,  -1.,  -1.,  -1.])])]

Answer 3

If:

s = pd.Series([np.array([ 58.,  -1.,  -1.,  -1.,  -1.]),
               np.array([ 77.,  95.,  -1.,  -1.,  -1.])])

Then

s.apply(pd.Series).values