List from Column elements-CodePudding

I want to create a column 'List' for column 'Numbers' such that it gives a list leaving the element of the corresponding row in pandas.

Table:

| Numbers  | List           |
| -------- | -------------- |
| 1        | [2,3,4,1]      |
| 2        | [3,4,1,1]      |
| 3        | [4,1,1,2]      |
| 4        | [1,1,2,3]      |
| 1        | [1,2,3,4]      |

Can anyone help with this, please?

CodePudding user response：

For general solution working with duplicated values first repeat values by numpy.tile and then remove values of diagonal for delete value of row:

df = pd.DataFrame({'Numbers':[1,2,3,4,1]})

A = np.tile(df['Numbers'], len(df)).reshape(-1, len(df))

#https://stackoverflow.com/a/46736275/2901002
df['new'] = A[~np.eye(A.shape[0],dtype=bool)].reshape(A.shape[0],-1).tolist()
print (df)
0        1  [2, 3, 4, 1]
1        2  [1, 3, 4, 1]
2        3  [1, 2, 4, 1]
3        4  [1, 2, 3, 1]
4        1  [1, 2, 3, 4]

CodePudding user response：

Try this:

df = pd.DataFrame({'numbers':range(1, 5)})
df['list'] = df['numbers'].apply(lambda x: [i for i in df['numbers'] if i != x])
df

CodePudding user response：

import pandas as pd

df = pd.DataFrame({'Numbers':[1,2,3,4,5]})

df['List'] = df['Numbers'].apply(
    # for every cell with element x in Numbers return Numbers without the element 
    lambda x: [y for y in df['Numbers'] if not y==x])

which results in:

df
   Numbers          List
0        1  [2, 3, 4, 5]
1        2  [1, 3, 4, 5]
2        3  [1, 2, 4, 5]
3        4  [1, 2, 3, 5]
4        5  [1, 2, 3, 4]

CodePudding user response：

Abhinar Khandelwal. If the task is to get any other number besides the current row value, than my answer can be fixed to the following:

import numpy as np

rng = np.random.default_rng()
numbers = rng.integers(5, size=7)

df = pd.DataFrame({'numbers':numbers})

df['list'] = df.reset_index()['index'].apply(lambda x: df[df.index != x].numbers.values)

df

But this way is much faster https://stackoverflow.com/a/73275614/18965699 :)