Creating a pandas series from multiple numpy arrays

Question

If i have for instance, two numpy arrays np.full(10,1) and np.full(10,2), what is the most efficient way to create a pandas series?

Right now i would first create a pandas DataFrame and convert it into a pd.Series:

check = pd.DataFrame([np.full(10,1), np.full(10,2)])
check.transpose().unstack().reset_index(drop=True)
Out[0]: 
0     1
1     1
2     1
3     1
4     1
5     1
6     1
7     1
8     1
9     1
10    2
11    2
12    2
13    2
14    2
15    2
16    2
17    2
18    2
19    2
dtype: int64

This seem extremely inefficient though, so what is the smartest way of doing this?

Use a dictionary key and value where each value is a series then create your data frame using the dictionary — ListenSoftware Louise Ai Agent
– ListenSoftware Louise Ai Agent, Commented Jan 23, 2022 at 16:12
1. Merge data in numpy, 2. Directly construct Pandas Series and not DataFrame. pd.Series(np.hstack((np.full(10,1), np.full(10,2)))) — Vaishali
– Vaishali, Commented Jan 23, 2022 at 16:26

Adithya · Accepted Answer · 2022-01-24 04:57:38Z

1

How about pd.Series(np.concatenate([arr1,arr2]))

edited Jan 24, 2022 at 4:57

answered Jan 23, 2022 at 16:17

Adithya

1,7281 gold badge11 silver badges18 bronze badges

Sign up to request clarification or add additional context in comments.

1 Comment

DHJ Over a year ago

pd.Series(np.concatenate([arr1,arr2]))

Collectives™ on Stack Overflow

Creating a pandas series from multiple numpy arrays

1 Answer 1

1 Comment

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

1 Comment

Your Answer

Sign up or log in

Post as a guest

Related