common_words = obama_words.sort('count', ascending=False)['word'][:5] common_words = set(common_words) count = 0 def has_top_words(word_count_vector): # extract the keys of word_count_vector and convert it to a set unique_words = word_count_vector.keys() unique_words = set(unique_words) returnWord = common_words.issubset(unique_words) global count if returnWord == True: count = count + 1 # return True if common_words is a subset of unique_words # return False otherwise return returnWord wiki['has_top_words'] = wiki['word_count'].apply(has_top_words) print(count)上述代码中,函数has_top_words需要用到count这个全局变量,定义在函数之外,函数中使用前,需要在count前加 global。
代码运行后如下: