这里有一种方法，使用我在评论中提到的技术：

import pandas as pd
data = [
    ['apple, banana, strawberry'],
    ['apple'],
    ['strawberry, apple']
]

df = pd.DataFrame(data, columns=['Fruits'])
print(df)

columns = set()
for row in df['Fruits'].to_list():
    columns |= set( row.split(', ') )

rows = []
for row in df['Fruits'].to_list():
    rows.append( [int(c in row) for c in columns] )

columns = list(columns)
df = pd.DataFrame(rows, columns=columns)
print(df)

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输出量：

Fruits
0  apple, banana, strawberry
1                      apple
2          strawberry, apple
   apple  banana  strawberry
0      1       1           1
1      1       0           0
2      1       0           1

型

你可以这样做

dummy_df = df["Fruits"].str.get_dummies(", ")

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产出

apple banana strawberry
0     1      1          1
1     1      0          0
2     1      0          1

型

在pandas上使用get_dummies函数为每行中的多个条目创建虚拟列，所以基本上通过分隔符（逗号）将条目拆分为fruits列，然后应用到get_dummies，这样我们就可以了：

import pandas as pd

# Create the sample dataframe
df = pd.DataFrame({'Fruits': ['apple, banana, strawberry', 'apple', 'strawberry, apple']})

# Split the entries in the 'Fruits' column by comma and apply get_dummies
dummies = df['Fruits'].str.split(', ', expand=True).stack().str.get_dummies().sum(level=0)

# Join the dummies dataframe with the original dataframe
result = df.join(dummies)

print(result)

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希望有用，谢谢，

您也可以在标准库的帮助下这样做，以获得整洁漂亮的代码。

from itertools import chain

def create_dummy(df: pd.DataFrame) -> pd.DataFrame:
    # Get list of all unique fruits
    fruits_series = df["Fruits"].str.split(", ")
    unique_fruits = set(chain.from_iterable(fruits_series))

    # Create dummy DataFrame
    tdf = pd.DataFrame(0,
                       columns=list(unique_fruits),
                       index=df.index,
                       dtype=pd.UInt8Dtype)

    # Update labels
    for ind, targets in zip(df.index, fruits_series):
        tdf.loc[ind, targets] = 1

    return tdf

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用途：

df = pd.DataFrame(["apple, orange, grape", 
                   "apple", 
                   "banana, strawberry"], columns=["Fruits"])
print(create_dummy(df))

型
输出量：

grape  strawberry  orange apple banana
 0      1           0       1     1      0
 1      0           0       0     1      0
 2      0           1       0     0      1

型
在python==3.10.8和pandas==1.5.2上测试。