Convert a series of arrays to a single list

Question

I need to convert series which has array within array to a list. This is the series:

    0
0   [[136.26198653744652]]
1   [[595.1701354429704]]
2   [[106.31607570796812]]
3   [[579.6333400908089]]
4   [[402.1731384585597]]
5   [[380.381375557186]]
type(b1)
Out[130]: pandas.core.series.Series

b1[1]
Out[131]: array([[595.1701354429704]], dtype=object) 

I have tried tolist(),.values or to_numpy() etc. Nothing worked except the following

b1.explode().explode().tolist()

This is what I got. [136.26198653744652, 595.1701354429704, 106.31607570796812, 579.6333400908089, 402.1731384585597, 380.381375557186]

To my understanding here explode does unboxing/unlisting like thing. I'm looking for some better solution here which helps to change the type of every element of a series and produce the result of b1.explode().explode().tolist().

Answer 1

Use 2 times flatten lists in Series :

L = [z for x in b1 for y in x for z in y]
print (L)
[136.26198653744652, 595.1701354429704, 106.31607570796812,
 579.6333400908089, 402.1731384585597, 380.381375557186]

Answer 2

an alternative, using chain from itertools

data ={ 0 : [[[136.26198653744652]],   [[595.1701354429704]],   [[106.31607570796812]],   [[579.6333400908089]],   [[402.1731384585597]],   [[380.381375557186]]]}

df = pd.DataFrame(data)

from itertools import chain
combine = chain.from_iterable

list(combine(combine(df[0])))

[136.26198653744652,
 595.1701354429704,
 106.31607570796812,
 579.6333400908089,
 402.1731384585597,
 380.381375557186]