Create python dataframe based on nested loop

Question

I am a new in Python pandas, so sorry if this question is very easy. I have three lists:

A = ['A','B','C']
M = ['1','2','3']
F = ['plus','minus','square']

I want to make those lists combined and show it in data frame. I have tried to use list.append

new_list = []
for i in A:
    new_list.append(i)
    for j in (M):
        new_list.append(j)
print(new_list)
['A', '1', '2', '3', 'B', '1', '2', '3', 'C', '1', '2', '3']

I confused, how to get the output like this (in dataframe):

You can use pd.DataFrame(list(product(A,M,F)), columns=['A', 'M', 'F']) — Chiheb Nexus
– Chiheb Nexus, Commented Nov 28, 2017 at 6:44
you need to import product from itertools like this way: from itertools import product — Chiheb Nexus
– Chiheb Nexus, Commented Nov 28, 2017 at 6:47

Neil · Accepted Answer · 2017-11-28 06:43:57Z

2

It seems as if you want to create all list of all possible permutations. You can do this with itertools and pandas. Itertools is a native library to python:

import pandas as pd
import itertools

A = ['A','B','C']
M = ['1','2','3']
F = ['plus','minus','square']

df = pd.DataFrame(list(itertools.product(A,M,F)), columns=['A','M','F'])
print(df)

Output:

    A  M       F
0   A  1    plus
1   A  1   minus
2   A  1  square
3   A  2    plus
4   A  2   minus
5   A  2  square
6   A  3    plus
7   A  3   minus
8   A  3  square
9   B  1    plus
10  B  1   minus
11  B  1  square
12  B  2    plus
13  B  2   minus
14  B  2  square
15  B  3    plus
16  B  3   minus
17  B  3  square
18  C  1    plus
19  C  1   minus
20  C  1  square
21  C  2    plus
22  C  2   minus
23  C  2  square
24  C  3    plus
25  C  3   minus
26  C  3  square

answered Nov 28, 2017 at 6:43

Neil

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Comments

fodma1 · Accepted Answer · 2017-11-28 06:45:36Z

1

What you need is a Cartesian product of the three sets:

import pandas as pd
from itertools import product

pd.DataFrame(list(product(A,M,F)), columns=['A', 'M', 'F'])

answered Nov 28, 2017 at 6:45

fodma1

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