在列中查找关键字并将这些关键字添加到针对同一行的新列中

Question

我是 python 的新手，这是我第一次 post 堆栈溢出。我有一个关键字列表和一个包含多列的数据框。

我想在特定列中搜索这些关键字，然后写下出现在它旁边的关键字。

这就是我正在做的。 My code

这是我遇到的错误。 The loop with the error

这就是我想要得到的。 Desired output

请帮助找出问题所在或提出更好的解决方法。谢谢！如果有助于使事情变得更简单，请编写下面的代码。

import pandas as pd

keywords = ["hello","hi","greetings","wassup"]

data = ["hello, my name is Harry", "Hi I am John", "Yo! Wassup", "Greetings fellow traveller","Hey im 
Henry", "Hello there General Kenobi"]

df = pd.DataFrame(data,columns = ['strings'])

df['Keywords'] = ""

df2 = pd.DataFrame(data = None, columns = df.columns)

for word in keywords:
     temp = df[df['strings'].str.contains(word,na = False)]
     temp.reset_index(drop = True)
     temp['Keywords'] = word
     df2.append(temp)

错误：

C:\Users\harka\Anaconda3\lib\site-packages\ipykernel_launcher.py:5: SettingWithCopyWarning: 试图在 DataFrame 的切片副本上设置一个值。尝试使用 .loc[row_indexer,col_indexer] = value 代替

查看文档中的注意事项：http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy """

Answer 1

我添加了'Yo'来表明它可以return多个字符串

import pandas as pd

def keyword(row):
  strings = row['strings']
  keywords = ["hello","hi","greetings","wassup",'yo']
  keyword = [key for key in keywords if key.upper() in strings.upper()]
  return keyword

data = ["hello, my name is Harry", "Hi I am John", "Yo! Wassup", "Greetings fellow traveller","Hey im Henry", "Hello there General Kenobi"]

df = pd.DataFrame(data,columns = ['strings'])
df['keyword'] = df.apply(keyword, axis=1)

如果您不喜欢字符串列表 return 那么也许是逗号分隔的字符串？

import pandas as pd

def keyword(row):
  strings = row['strings']
  keywords = ["hello","hi","greetings","wassup",'yo']
  keyword = [key for key in keywords if key.upper() in strings.upper()]
  return ','.join(keyword)

data = ["hello, my name is Harry", "Hi I am John", "Yo! Wassup", "Greetings fellow traveller","Hey im Henry", "Hello there General Kenobi"]

df = pd.DataFrame(data,columns = ['strings'])
df['keyword'] = df.apply(keyword, axis=1)

在列中查找关键字并将这些关键字添加到针对同一行的新列中

Finding keywords in a column and adding those keywords in a new column against the same row

python

contains

append

dataframe