将列表列表转换为字符串pandas dataframe

Question

背景

我有以下玩具df，其包含在列Before和After中的列表，如下所示

import pandas as pd
before = [list(['in', 'the', 'bright', 'blue', 'box']), 
       list(['because','they','go','really','fast']), 
       list(['to','ride','and','have','fun'])]
after = [list(['there', 'are', 'many', 'different']), 
       list(['i','like','a','lot','of', 'sports']), 
       list(['the','middle','east','has','many'])]

df= pd.DataFrame({'Before' : before, 
                   'After' : after,
                  'P_ID': [1,2,3], 
                  'Word' : ['crayons', 'cars', 'camels'],
                  'N_ID' : ['A1', 'A2', 'A3']
                 })

输出

                    After                Before                     N_ID P_ID   Word
0   [in, the, bright, blue, box]        [there, are, many, different]   A1  1   crayons
1   [because, they, go, really, fast]   [i, like, a, lot, of, sports ]  A2  2   cars
2   [to, ride, and, have, fun]        [the, middle, east, has, many]    A3  3   camels

问题

使用以下代码块：

来自Removing commas and unlisting a dataframe的

df.loc[:, ['After', 'Before']] = df[['After', 'Before']].apply(lambda x: x.str[0].str.replace(',', ''))产生以下输出：

接近我想但不完全输出

    After   Before  N_ID  P_ID  Word
0   in      there    A1    1    crayons
1   because  i       A2    2    cars
2   to      the      A3    3    camels

此输出是接近的，但与我要查找的输出不完全相同，因为当我想要的输出看起来像这样时，After和Before列只有一个单词输出（例如there）： / p>

所需的输出

     After                           Before               N_ID  P_ID  Word
0 in the bright blue box        there are many different  A1    1   crayons
1 because they go really fast   i like a lot of sports    A2    2   cars
2 to ride and have fun         the middle east has many   A3    3   camels

问题

如何获取我的所需输出？

Answer 1

agg + join。逗号不在列表中，只是列表__repr__的一部分。

---

str_cols = ['Before', 'After']

d = {k: ' '.join for k in str_cols}

df.agg(d).join(df.drop(str_cols, 1))

                        Before                     After  P_ID     Word N_ID
0       in the bright blue box  there are many different     1  crayons   A1
1  because they go really fast    i like a lot of sports     2     cars   A2
2         to ride and have fun  the middle east has many     3   camels   A3

---

如果您希望就位（更快）：

df[str_cols] = df.agg(d)

Answer 2

applymap

在线

具有预期结果的数据框的新副本

df.assign(**df[['After', 'Before']].applymap(' '.join))

                        Before                     After  P_ID     Word N_ID
0       in the bright blue box  there are many different     1  crayons   A1
1  because they go really fast    i like a lot of sports     2     cars   A2
2         to ride and have fun  the middle east has many     3   camels   A3

就地

更改现有的df

df.update(df[['After', 'Before']].applymap(' '.join))
df

                        Before                     After  P_ID     Word N_ID
0       in the bright blue box  there are many different     1  crayons   A1
1  because they go really fast    i like a lot of sports     2     cars   A2
2         to ride and have fun  the middle east has many     3   camels   A3

---

stack和str.join

我们可以使用类似于上图所示的“在线”和“就地”方式使用此结果。

df[['After', 'Before']].stack().str.join(' ').unstack()

                      After                       Before
0  there are many different       in the bright blue box
1    i like a lot of sports  because they go really fast
2  the middle east has many         to ride and have fun

Answer 3

我们可以指定要转换为字符串的列表，然后在for循环中使用.apply：

lst_cols = ['Before',  'After']

for col in lst_cols:
    df[col] = df[col].apply(' '.join)

                        Before                     After  P_ID     Word N_ID
0       in the bright blue box  there are many different     1  crayons   A1
1  because they go really fast    i like a lot of sports     2     cars   A2
2         to ride and have fun  the middle east has many     3   camels   A3