공식문서
예제링크
temp_df['lag_1'] = temp_df.groupby(['id'])[TARGET].transform(lambda x: x.shift(1))
apply 함수 꿀
def test(x):
if x =='저렴한': return 'cheap'
elif x =='예쁜': return 'pretty'
elif x == '아늑한': return 'comport'
elif x == '빈티지': return 'vintage'
elif x == '이국적/이색적': return 'exotic'
elif x == '분위기좋은': return 'good_mood'
elif x == '고급스러운': return 'Luxurious'
elif x == '캐주얼한': return 'casual'
elif x == '깔끔한': return 'clean'
elif x == '조용한': return 'quiet'
elif x == '감성적인': return 'emotional'
elif x == '서민적인': return 'common'
elif x == '시끌벅적한': return 'noisy'
df['feat_eng'] = df['feat10'].apply(test)