如何修復For循環以從DataFrame返回某個字符？

Question

我已經導入了一個excel文件，並將其放入DataFrame中，然后遍歷“標題”列以吐出帶有某些關鍵字的標題。 我的標題列表為“ match_titles”。 我現在想做的是創建一個For循環，以返回match_titles中每個標題的“ titles”之前的列。”我不確定代碼為什么不起作用，任何幫助將不勝感激。

import pandas as pd

data = pd.read_excel(r'C:\Users\bryanmccormack\Downloads\asin_list.xlsx')
df = pd.DataFrame(data, columns=['Track','Asin','Title'])

excludes = ["Chainsaw", "Diaper pail", "Leaf Blower"]
my_excludes = [set(key_word.lower().split()) for key_word in excludes]
match_titles = [e for e in df.Title if 
any(keywords.issubset(e.lower().split()) for keywords in my_excludes)]

a = []
for i in match_titles:
    a.append(df['Asin'])
print(a)

Answer 1

在您的for循環中，您將未過濾的列df['Asin']追加到列表a次數是match_titles中的值的match_titles 。 但是沒有對df任何過濾。

一種解決方案是在match_values列中創建一列，然后在對該match_values列進行過濾后，您可以返回Asin列：

# make a function to perform your match analysis.
def is_match(title, excludes=["Chainsaw", "Diaper pail", "Leaf Blower"]):
    my_excludes = [set(key_word.lower().split()) for key_word in excludes]
    if any(keywords.issubset(title.lower().split()) for keywords in my_excludes):
        return True
    return False

# Make a new boolean column for the matches.  This applies your
# function to each value in df['Title'] and puts the output in
# the new column.
df['match_titles'] = df['Title'].apply(is_match)

# Filter the df to only matches and return the column you want.
# Because the match_titles column is boolean it can be used as
# an index.
result = df[df['match_titles']]['Asin']