如何用一个预定义列表中的单词在数据帧的文本列中出现的次数来创建一个新的列？

Question

我想构建一个新列，其中包含ai_functional列表中的单词在文本列中出现的次数的计数。

给出的列表是：

> ai_functional = ["natural language
> processing","nlp","A I ","Aritificial intelligence", "stemming","lemmatization","lemmatization","information
> extraction","text mining","text analytics","data-mining"]

我想要的结果如下：

> text                                                                     counter
> 
> 1. More details  A I   Artificial Intelligence                             2
> 2. NLP works very well these days                                          1         
> 3. receiving information at the right time                                 1

我一直使用的代码是

def func(stringans):
  for x in ai_tech:
    count = stringans.count(x)
  
  return count

df['counter']=df['text'].apply(func)

有没有人能帮帮我。我真的被卡住了，因为每次我应用它时，我在计数器列中得到的结果是0

Answer 1

在执行count =时，擦除之前的值，希望对不同的计数求和

def func(stringans):
    count = 0
    for x in ai_tech:
        count += stringans.count(x)
    return count

# with sum and generator 
def func(stringans):
    return sum(stringans.count(x) for x in ai_tech)

修复ai_tech中的一些拼写错误并将全部设置为.lower()将在计数器列中生成2,1,0，最后一行没有共同的值

import pandas as pd

ai_tech = ["natural language processing", "nlp", "A I ", "Artificial intelligence",
           "stemming", "lemmatization", "information extraction",
           "text mining", "text analytics", "data - mining"]

df = pd.DataFrame([["1. More details  A I   Artificial Intelligence"], ["2. NLP works very well these days"],
                   ["3. receiving information at the right time"]], columns=["text"])

def func(stringans):
    return sum(stringans.lower().count(x.lower()) for x in ai_tech)

df['counter'] = df['text'].apply(func)
print(df)

# ------------------
                                             text  counter
0  1. More details  A I   Artificial Intelligence        2
1               2. NLP works very well these days        1
2      3. receiving information at the right time        0