将列表列表转换为字符串pandas dataframe [英] turn lists of lists into strings pandas dataframe
问题描述
背景
我有以下玩具df
,该玩具在Before
和After
列中包含列表,如下所示
I have the following toy df
that contains lists in the columns Before
and After
as seen below
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:
df.loc[:, ['After', 'Before']] = df[['After', 'Before']].apply(lambda x: x.str[0].str.replace(',', ''))
会产生以下输出:
对我想但不完全关闭的输出
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
此输出很接近,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
):
This output is close but not quite what I am looking for because After
and Before
columns have only one word outputs (e.g. there
) when my desired output looks as such:
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
如何获取我的期望的输出?
推荐答案
agg
+ join
.逗号不在列表中,只是列表__repr__
的一部分.
agg
+ join
. The commas aren't present in your lists, they are just part of the __repr__
of the list.
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):
If you'd prefer in place (faster):
df[str_cols] = df.agg(d)
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