我假设原始 Dataframe 上的索引是唯一的，如果不是，在下面的代码段之前运行df = df.reset_index()：

columns = ["phones", "emails"]

# Explode each column individually, but instead of using `explode`, we will
# use`stack` to give us a second index level
exploded = [
    df[col].str.split(",", expand=True).stack().rename(col)
    for col in columns
]

# Align the exploded columns
exploded = pd.concat(exploded, axis=1).droplevel(-1)

# Merge it with the original data frame
result = pd.concat([df.drop(columns=columns), exploded], axis=1)

我在哪里读到的。如果我找到链接，我会上传的。

import itertools
import pandas as pd
import numpy as np
from pandas import DataFrame as df


df = pd.DataFrame({"x":[1,3,7],"y":["A","B","C"], 
                   "z":["p1,p2,p3","p4","p5,p6"],"package_code":["111,222,333","444","555,666"]})

print(df)
"""
   x  y         z package_code
0  1  A  p1,p2,p3  111,222,333
1  3  B        p4          444
2  7  C     p5,p6      555,666

"""
aa = (
    df.set_index(['x','y'])
    .apply(lambda col : pd.Series(col).str.split(','))
    .explode(['z','package_code'])
    .reset_index()
    .reindex(df.columns,axis=1)
    )
print(aa)

"""
   x  y   z package_code
0  1  A  p1          111
1  1  A  p2          222
2  1  A  p3          333
3  3  B  p4          444
4  7  C  p5          555
5  7  C  p6          666
"""