How to Split a Pandas Column of Lists into Multiple Columns?-Python Tutorial-php.cn

How to Split a Pandas Column of Lists into Multiple Columns?

Patricia Arquette

Release： 2024-12-19 18:02:10

Original

284 people have browsed it

How to Split a Pandas Column of Lists into Multiple Columns?

Splitting Pandas Column of Lists into Multiple Columns

Problem

Consider a Pandas DataFrame with a column containing lists:

import pandas as pd

df = pd.DataFrame({"teams": [[["SF", "NYG"]] for _ in range(7)]})

       teams
0  [[SF, NYG]]
1  [[SF, NYG]]
2  [[SF, NYG]]
3  [[SF, NYG]]
4  [[SF, NYG]]
5  [[SF, NYG]]
6  [[SF, NYG]]

Copy after login

To transform this column into two individual columns, follow the below steps:

Solution

Create List of Values Using to_list():

import pandas as pd

d1 = {'teams': [['SF', 'NYG'],['SF', 'NYG'],['SF', 'NYG'],
                ['SF', 'NYG'],['SF', 'NYG'],['SF', 'NYG'],['SF', 'NYG']]}
df2 = pd.DataFrame(d1)
print (df2)
       teams
0  [SF, NYG]
1  [SF, NYG]
2  [SF, NYG]
3  [SF, NYG]
4  [SF, NYG]
5  [SF, NYG]
6  [SF, NYG]

Copy after login

Extract Columns Using Assignment:

Assign a new DataFrame with the desired columns:

df2[['team1','team2']] = pd.DataFrame(df2.teams.tolist(), index= df2.index)
print (df2)
       teams team1 team2
0  [SF, NYG]    SF   NYG
1  [SF, NYG]    SF   NYG
2  [SF, NYG]    SF   NYG
3  [SF, NYG]    SF   NYG
4  [SF, NYG]    SF   NYG
5  [SF, NYG]    SF   NYG
6  [SF, NYG]    SF   NYG

Copy after login

Create New DataFrame for Result:

Alternatively, a new DataFrame can be created separately:

df3 = pd.DataFrame(df2['teams'].to_list(), columns=['team1','team2'])
print (df3)
  team1 team2
0    SF   NYG
1    SF   NYG
2    SF   NYG
3    SF   NYG
4    SF   NYG
5    SF   NYG
6    SF   NYG

Copy after login

Note: Using apply(pd.Series) for this operation can be significantly slower than the methods described above.

The above is the detailed content of How to Split a Pandas Column of Lists into Multiple Columns?. For more information, please follow other related articles on the PHP Chinese website!