Split a variable with lists as values in different variables in pandas-CodePudding

I am trying to split a variable of a pd dataframe into many. The variable values (row wise) look like this (there are other variables in my df and I want to keep them as they are):

Variable1

[('Max'), ('15'), ('Place'), ('FB'), ('27 Aug 2022')]
[('Mily', ), ('Place'), ('Google'), ('22 Aug 2022')]
[('Mishika'), ('Place', ), ('London'), ('22 Aug 2022')]

Ideally I want to split Variable1 in as many variables as there are in elements in each list row wise. The resulting frame should be like following:

V1      V2    V3     V4               V5
Max     15    Place  FB            27 Aug 2022
Mily    Place Google 22 Aug 2022
Mishika Place London 22 Aug 2022

I know the value types in each variable will be a mess, but that is not an issue for me. I have this as of now:

for l in df['Variable1'].split('\),\s\('):
    df['var_l'] = l

Which is of course not correct.

CodePudding user response：

Considering the given dataframe :

import pandas as pd

df = pd.DataFrame({'Variable1': [["(Max)", "(15)", "(Place)", "(FB)", "(27 Aug 2022)"],
                                ["(Mily, )", "(Place)", "(Google)", "(22 Aug 2022)"],
                                ["(Mishika)", "(Place, )", "(London)", "(22 Aug 2022)"]]})

`>>> print(df)`

You can use

CodePudding user response：

If I understood you, you want something like this, don't you?

import pandas as pd
import numpy as np

variable1 = [('Max'), ('15'), ('Place'), ('FB'), ('27 Aug 2022')]
variable2 = [('Mily'), ('Place'), ('Google'), ('22 Aug 2022')]

var1 = np.array([v for v in variable1 ])
var2 = np.array([v for v in variable2 ])

df = pd.DataFrame([var1])
df2 = pd.DataFrame([var2])

df3 = pd.concat([df, df2], axis=0)

print( df3.head() )

The output is:

     0      1    2            3            4
0   Max     15   Place        FB         27 Aug 2022
0   Mily  Place  Google  22 Aug 2022     NaN