将多行数据框单元格转换为多行-Python

Question

我正在尝试将pandas数据框中的多行单元格转换为表中的多行

  column1               column2    column3
0        1                    Hi      hello
1        2  some\nTest\nTo\nWork         hi
2        3                  Hiya  somewhere
3        4                             test
4        5               Another       test2
5        6                             test3

鉴于上表，我希望我的输出如下所示：

   column1               column2    column3
0        1                    Hi      hello
1        2                    some    hi
2        2                    Test    hi
3        2                    To      hi
4        2                  work      hi
5        3                  Hiya      somewhere
6        4                             test
7        5                  Another    test2
8        6                             test3

Answer 1

在换行符和“嵌套”上分开：

from itertools import chain

v = df.pop('column2').str.split('\n')  # if this doesn't work, try r'\\n'. 
df = (pd.DataFrame(df.values.repeat(v.str.len(),axis=0), columns=df.columns)
        .assign(column2=list(chain.from_iterable(v)))
        .sort_index(axis=1))

print(df)
  column1 column2    column3
0       1      Hi      hello
1       2    some         hi
2       2    Test         hi
3       2      To         hi
4       2    Work         hi
5       3    Hiya  somewhere

Answer 2

尝试一下：

 df.fillna('').set_index(['column1','column3']).stack().str.split('\n', expand=True).stack().unstack(-2).reset_index(-1, drop=True).reset_index()         
Out[1516]: 
   column1    column3 column2
0        1      hello      Hi
1        2         hi    some
2        2         hi    test
3        2         hi      To
4        2         hi    Work
5        3  somewhere    Hiya

Answer 3

import numpy as np

df[['column1','column3']]=np.repeat(df[['column1','column3']].values(df['column2'].str.split('\n').str.len()),axis=0)
df['column2']=','.join(df['column2'].values.flatten()).split()
print(df)
  column1 column2    column3
0       1      Hi      hello
1       2    some         hi
2       2    Test         hi
3       2      To         hi
4       2    Work         hi
5       3    Hiya  somewhere