这很可能不是最有效/最佳的方法，但您可以这样做：

# Create DataFrame from question
df = pd.DataFrame({
    'txt_file': ['business049.txt',
            'business470.txt',
            'business075.txt',
            'business101.txt',
            'business060.txt',
            ],
    'words': [
        ['bmw', 'cash', 'fuel', 'mini', 'product', 'less', 'mini'],
        ['saudi', 'investor', 'pick', 'savoy', 'london', 'famou'],
        ['eu', 'minist', 'mull', 'jet', 'fuel', 'tax', 'european'],
        ['australia', 'rate', 'australia', 'rais', 'benchmark'],
        ['insur', 'boss', 'plead', 'guilti', 'anoth', 'us', 'insur'],
    ]
})

# Get all unique words in a list
word_list = list(set(df['words'].explode()))

# Link txt files to unique words
# Note: list of txt files is one string comma separated to ensure single column in resulting DataFrame
word_dict = {
    unique_word: [', '.join(df[df['words'].apply(lambda list_of_words: unique_word in list_of_words)]['txt_file'])] for unique_word in word_list
}

# Create DataFrame from dictionary (transpose to have words as row index).
words_in_files = pd.DataFrame(word_dict).transpose()

字典word_dict可能正是您所需要的，而不是仅仅为了使用DataFrame而保留DataFrame。如果是这种情况，请从字典创建中删除', '.join()部分，因为dict的值在长度上不相等并不重要。