multiple series appended in a list using df.iterrows. How do I convert it into a dataframe?

I would like to know how to covert multiple series objects in list into a dataframe.

import pandas as pd

data = {
  "firstname": ["Sally", "Mary", "John"],
  "age": [50, 40, 30],
  "lastname" : ["a1", "b1", "c1"],
}

df = pd.DataFrame(data)

tmp_list = list()

for idx, row in df.iterrows():
    tmp_list.append(row)

My tmp_list looks like this.

[firstname    Sally
 age             50
 lastname        a1
 Name: 0, dtype: object,
 firstname    Mary
 age            40
 lastname       b1
 Name: 1, dtype: object,
 firstname    John
 age            30
 lastname       c1
 Name: 2, dtype: object]

How could I convert the multiple series objects in tmp_list into a dataframe like df?

df

  firstname  age lastname
0     Sally   50       a1
1      Mary   40       b1
2      John   30       c1

>Solution :

Use concat then use transpose:

out=pd.concat(tmp_list,axis=1).T
'''
    firstname   age lastname
0   Sally       50  a1
1   Mary        40  b1
2   John        30  c1

'''