根据名称列表更改 pandas 列中的文本
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【中文标题】根据名称列表更改 pandas 列中的文本【英文标题】:Alter text in pandas column based on names list 【发布时间】:2019-12-05 17:01:04 【问题描述】:背景
我有以下示例df
import pandas as pd
Names = [list(['Jon', 'Mith', 'jon', 'John']),
list(['Mark', 'Marky', 'marcs']),
list(['Bob', 'bobby', 'Bobs'])]
df = pd.DataFrame('Text' : ['Jon J Mmith is Here and jon John from ',
'When he came Mark was Marky but not marcs so',
'I like Bob and bobby and also Bobs diner '],
'P_ID': [1,2,3],
'P_Name' : Names
)
#rearrange columns
df = df[['Text', 'P_ID', 'P_Name']]
df
Text P_ID P_Name
0 Jon J Mmith is Here and jon John from 1 [Jon, Smith, jon, John]
1 When he came Mark was Marky but not marcs 2 [Mark, Marky, marcs]
2 I like Bob and bobby and also Bobs diner 3 [Bob, bobby, Bobs]
此df
是此处Alter text in pandas column based on names 中的“旧问题”的变体。我的新df
和“新问题”的唯一区别是P_Name
列中名称的格式,如下所示:
#old names from old question
array(['Mmith, Jon J', 'Hider, Mary', 'Doe, Jane Ann', 'Tucker, Tom'], dtype=object)
#new names from new question
array([list(['Jon', 'Smith', 'jon', 'John']),
list(['Mark', 'Marky', 'marcs']), list(['Bob', 'bobby', 'Bobs'])], dtype=object)
目标
在Text
列中,将**BLOCK**
添加到与P_Name
中找到的值相对应的值(例如[Jon, Mmith, jon, John]
)
问题
当我使用取自Alter text in pandas column based on names的“老问题”中的解决方案时
df['Text'].replace(df['P_Name'].str.split(', *').apply(lambda l: ' '.join(l[::-1])),'**BLOCK**',regex=True)
我收到以下错误:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-79-895f7ea46849> in <module>()
----> 1 df['Text'].replace(df['P_Name'].str.split(', *').apply(lambda l: ' '.join(l[::-1])),'**BLOCK**',regex=True)
/usr/local/Cellar/python3/3.6.1/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/pandas/core/series.py in apply(self, func, convert_dtype, args, **kwds)
2353 else:
2354 values = self.asobject
-> 2355 mapped = lib.map_infer(values, f, convert=convert_dtype)
2356
2357 if len(mapped) and isinstance(mapped[0], Series):
pandas/_libs/src/inference.pyx in pandas._libs.lib.map_infer (pandas/_libs/lib.c:66645)()
<ipython-input-79-895f7ea46849> in <lambda>(l)
----> 1 df['Text'].replace(df['P_Name'].str.split(', *').apply(lambda l: ' '.join(l[::-1])),'**BLOCK**',regex=True)
TypeError: 'float' object is not subscriptable
期望的结果
我想要以下,类似于“老问题”Alter text in pandas column based on names中的答案
Text P_ID P_Name
0 **BLOCK** J **BLOCK** is Here and **BLOCK** **BLOCK** from 1 [Jon, Smith, jon, John]
1 When he came **BLOCK** was **BLOCK** but not **BLOCK** 2 [Mark, Marky, marcs]
2 I like **BLOCK** and **BLOCK** and also **BLOCK** diner 3 [Bob, bobby, Bobs]
问题
鉴于我的 P_Name
列现在包含列表列表,我该如何实现我想要的结果?
【问题讨论】:
【参考方案1】:IIUC,你需要series.replace
,它以列表为参数:
to_replace :str、regex、list、dict、Series、int、float 或 None
df=df.assign(Text=df.Text.replace(df.P_Name,'**BLOCK**',regex=True))
【讨论】:
@ER_18df['new']=df.Text.replace(df.P_Name,'**PHI**',regex=True)
完美!谢谢你:)以上是关于根据名称列表更改 pandas 列中的文本的主要内容,如果未能解决你的问题,请参考以下文章
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