pandas：仅当另一列中的值匹配时才计算行之间的重叠词

Question

我有一个如下所示的数据框，但有很多行：

import pandas as pd

data = {'intent':  ['order_food', 'order_food','order_taxi','order_call','order_call','order_taxi'],
'Sent': ['i need hamburger','she wants sushi','i need a cab','call me at 6','she called me','i would like a new taxi' ],
'key_words': [['need','hamburger'], ['want','sushi'],['need','cab'],['call','6'],['call'],['new','taxi']]}

df = pd.DataFrame (data, columns = ['intent','Sent','key_words'])

我使用下面的代码（不是我的解决方案）计算了 jaccard 相似度：

def lexical_overlap(doc1, doc2): 
    words_doc1 = set(doc1) 
    words_doc2 = set(doc2)

    intersection = words_doc1.intersection(words_doc2)


    return intersection

并修改了给出的代码以比较每行可能的两行之间的重叠词并从中创建一个数据框：

overlapping_word_list=[]

for val in list(combinations(range(len(data_new)), 2)):
     overlapping_word_list.append(f"the shared keywords between {data_new.iloc[val[0],0]} and {data_new.iloc[val[1],0]} sentences are: {lexical_overlap(data_new.iloc[val[0],1],data_new.iloc[val[1],1])}")
#creating an overlap dataframe
banking_overlapping_words_per_sent = DataFrame(overlapping_word_list,columns=['overlapping_list'])

因为我的数据集很大，当我运行这段代码比较所有行时，它需要很长时间。所以我只想比较具有相同意图的句子，而不比较具有不同意图的句子。我不确定如何继续这样做

Answer 1

IIUC 你只需要遍历 intent 列中的唯一值，然后使用 loc 只获取与之对应的行。如果你有超过两行，你仍然需要使用 combinations 来获得相似意图之间的唯一 combinations。

from itertools import combinations

for intent in df.intent.unique():
    # loc returns a DataFrame but we need just the column
    rows = df.loc[df.intent == intent, ["Sent"]].Sent.to_list()
    combos = combinations(rows, 2)
    for combo in combos:
        x, y = rows
        overlap = lexical_overlap(x, y)
        print(f"Overlap for ({x}) and ({y}) is {overlap}")

#  Overlap for (i need hamburger) and (she wants sushi) is 46.666666666666664
#  Overlap for (i need a cab) and (i would like a new taxi) is 40.0
#  Overlap for (call me at 6) and (she called me) is 54.54545454545454

Answer 2

好的，所以我想出了如何根据@gold_cy的回答在评论中提到我想要的输出：

for intent in df.intent.unique():
# loc returns a DataFrame but we need just the column
   rows = df.loc[df.intent == intent,['intent','key_words','Sent']].values.tolist()
   combos = combinations(rows, 2)
   for combo in combos:
       x, y = rows
       overlap = lexical_overlap(x[1], y[1])
       print(f"Overlap of intent ({x[0]}) for ({x[2]}) and ({y[2]}) is {overlap}")

pandas：仅当另一列中的值匹配时才计算行之间的重叠词

pandas: calculate overlapping words between rows only if values in another column match

python

string-comparison

pandas

sentence-similarity