Python:函数返回的值未在 Pandas 数据框中更新

Question

我有一个 fruits带列的数据框:(Name, Color)和一个 sentence带列的数据框:(Sentence) .
水果数据框

          Name   Color
0        Apple     Red
1        Mango  Yellow
2       Grapes   Green
3   Strawberry    Pink

句子数据框

                      Sentence
0  I like Apple, Mango, Grapes
1            I like ripe Mango
2             Grapes are juicy
3           Oranges are citric

我需要将水果数据帧的每一行与句子数据帧的每一行进行比较，如果水果名称在句子中完全如此，则在句子中的水果名称之前连接它的颜色。
这就是我使用 dataframe.apply() 所做的:

import pandas as pd
import regex as re

# create fruit dataframe 
fruit_data = [['Apple', 'Red'], ['Mango', 'Yellow'], ['Grapes', 'Green']] 
fruit_df = pd.DataFrame(fruit_data, columns = ['Name', 'Color']) 
print(fruit_df)

# create sentence dataframe 
sentence = ['I like Apple, Mango, Grapes', 'I like ripe Mango', 'Grapes are juicy'] 
sentence_df = pd.DataFrame(sentence, columns = ['Sentence']) 
print(sentence_df)


def search(desc, name, color):

    if re.findall(r"\b" + name + r"\b", desc):
             
            # for loop is used because fruit can appear more than once in sentence
            all_indexes = []
            for match in re.finditer(r"\b" + name + r"\b", desc):
                     all_indexes.append(match.start())
            
            arr = list(desc)
            for idx in sorted(all_indexes, reverse=True):
                       arr.insert(idx, color + " ")

            new_desc = ''.join(arr)
            return new_desc 

def compare(name, color):
    sentence_df['Result'] = sentence_df['Sentence'].apply(lambda x: search(x, name, color))
    

fruit_df.apply(lambda x: compare(x['Name'], x['Color']), axis=1)
print ("The final result is: ")
print(sentence_df['Result'])

我得到的结果是:

                      Sentence     Result
0  I like Apple, Mango, Grapes       None
1            I like ripe Mango       None
2             Grapes are juicy       None
3           Oranges are citric       None

预期结果:

                      Sentence                                        Result
0  I like Apple, Mango, Grapes  I like Red Apple, Yellow Mango, Green Grapes
1            I like ripe Mango                      I like ripe Yellow Mango
2             Grapes are juicy                        Green Grapes are juicy
3           Oranges are citric       

我也尝试遍历 fruits_df使用 itertuples()但结果还是一样

for row in fruit_df.itertuples():
   result = sentence_df['Sentence'].apply(lambda x: search(x, getattr(row, 'Name'), getattr(row, 'Color')))
   print(result)

我不明白为什么 search 返回的值函数未存储在新列中。这是正确的方法还是我错过了什么？

Answer 1

问题是你打电话compare每行 Fruit但在每次通过时使用相同的输入。
我刚刚添加了一些调试打印到 compare函数来了解发生了什么:

def compare(name, color):
    print(name, color)
    sentence_df['Result'] = sentence_df['Sentence'].apply(lambda x: search(x, name, color))
    print(sentence_df['Result'])

并得到:

Apple Red
0    I like Red Apple, Mango, Grapes
1                               None
2                               None
Name: Result, dtype: object
Mango Yellow
0    I like Apple, Yellow Mango, Grapes
1              I like ripe Yellow Mango
2                                  None
Name: Result, dtype: object
Grapes Green
0    I like Apple, Mango, Green Grapes
1                                 None
2               Green Grapes are juicy
Name: Result, dtype: object

因此，当水果存在时，您成功添加了颜色，但如果不存在则返回 None，并且每次通过时都从原始列开始，因此只保留最后一个。
怎么修:

先添加一个缺失的return desc在搜索中，避免 None结果

 def search(desc, name, color):

     if re.findall(r"\b" + name + r"\b", desc):
             ...                 
             new_desc = ''.join(arr)
             return new_desc
     return desc

初始化 df['Result']在应用比较之前，并将其用作其输入:

 def compare(name, color):
     sentence_df['Result'] = sentence_df['Result'].apply(lambda x: search(x, name, color))

 sentence_df['Result'] = sentence_df['Sentence']
 fruit_df.apply(lambda x: compare(x['Name'], x['Color']), axis=1)

最终达到预期:

The final result is: 
0    I like Red Apple, Yellow Mango, Green Grapes
1                        I like ripe Yellow Mango
2                          Green Grapes are juicy
Name: Result, dtype: object