You can use this one:

my_list = map(lambda x: x[0], z_r)
ser = pd.Series(my_list)
In [86]:
ser
Out[86]:
0      0.009093
1      0.023903
2      0.029988

Actually, your question is how to convert to series ^^

You can try of using pandas Dataframe from records

pd.DataFrame.from_records(series.values,index=series.index)

Out:

    0   1   2   3
file1   1   2   3   4
file2   5   6   7   8
file3   9   10  11  12

Using np.squeeze:

ar = np.array([[1,2,3,4]])
s = pd.Series(np.squeeze(ar))
s

Output:

0    1
1    2
2    3
3    4
dtype: int64

IIUC you can use DataFrame constructor and apply join:

import pandas as pd
import numpy as np

arr = np.array([[64, 22,],   [58, 64],   [42, 31]])
print arr
[[64 22]
 [58 64]
 [42 31]]

li = ['one','two','three']
df = pd.DataFrame(arr, dtype='str', index=li)
print df
        0   1
one    64  22
two    58  64
three  42  31

print df.apply(lambda x: ' '.join(x), axis=1)
one      64 22
two      58 64
three    42 31
dtype: object

To get numpy array, you need

Y.values