[문제 풀이] 특정 단어를 포함하는 열 선택

Quiz
Author

강신성

Published

September 21, 2023

문제

데이터프레임 df의 열이름에 actor라는 단어가 포함된 column만을 선택하는 코드를 작성하라

1. 사전작업

  • 라이브러리 설치
import pandas as pd
import numpy as np
  • 데이터 불러오기 및 확인
df=pd.read_csv('https://raw.githubusercontent.com/PacktPublishing/Pandas-Cookbook/master/data/movie.csv')
df.head()
color director_name num_critic_for_reviews duration director_facebook_likes actor_3_facebook_likes actor_2_name actor_1_facebook_likes gross genres ... num_user_for_reviews language country content_rating budget title_year actor_2_facebook_likes imdb_score aspect_ratio movie_facebook_likes
0 Color James Cameron 723.0 178.0 0.0 855.0 Joel David Moore 1000.0 760505847.0 Action|Adventure|Fantasy|Sci-Fi ... 3054.0 English USA PG-13 237000000.0 2009.0 936.0 7.9 1.78 33000
1 Color Gore Verbinski 302.0 169.0 563.0 1000.0 Orlando Bloom 40000.0 309404152.0 Action|Adventure|Fantasy ... 1238.0 English USA PG-13 300000000.0 2007.0 5000.0 7.1 2.35 0
2 Color Sam Mendes 602.0 148.0 0.0 161.0 Rory Kinnear 11000.0 200074175.0 Action|Adventure|Thriller ... 994.0 English UK PG-13 245000000.0 2015.0 393.0 6.8 2.35 85000
3 Color Christopher Nolan 813.0 164.0 22000.0 23000.0 Christian Bale 27000.0 448130642.0 Action|Thriller ... 2701.0 English USA PG-13 250000000.0 2012.0 23000.0 8.5 2.35 164000
4 NaN Doug Walker NaN NaN 131.0 NaN Rob Walker 131.0 NaN Documentary ... NaN NaN NaN NaN NaN NaN 12.0 7.1 NaN 0

5 rows × 28 columns

df.columns
Index(['color', 'director_name', 'num_critic_for_reviews', 'duration',
       'director_facebook_likes', 'actor_3_facebook_likes', 'actor_2_name',
       'actor_1_facebook_likes', 'gross', 'genres', 'actor_1_name',
       'movie_title', 'num_voted_users', 'cast_total_facebook_likes',
       'actor_3_name', 'facenumber_in_poster', 'plot_keywords',
       'movie_imdb_link', 'num_user_for_reviews', 'language', 'country',
       'content_rating', 'budget', 'title_year', 'actor_2_facebook_likes',
       'imdb_score', 'aspect_ratio', 'movie_facebook_likes'],
      dtype='object')

열 이름에서 단어의 구분이 모두 '_'로 되어있으므로, 열이름에 split()함수를 적용시킬 수 있을 것 같다.

2. 풀이

  • for 문을 이용하여 풀이해보자.
['actor' in i.split('_') for i in df.columns]
[False,
 False,
 False,
 False,
 False,
 True,
 True,
 True,
 False,
 False,
 True,
 False,
 False,
 False,
 True,
 False,
 False,
 False,
 False,
 False,
 False,
 False,
 False,
 False,
 True,
 False,
 False,
 False]

3. 결과

df.loc[:, ['actor' in i.split('_') for i in df.columns]]
actor_3_facebook_likes actor_2_name actor_1_facebook_likes actor_1_name actor_3_name actor_2_facebook_likes
0 855.0 Joel David Moore 1000.0 CCH Pounder Wes Studi 936.0
1 1000.0 Orlando Bloom 40000.0 Johnny Depp Jack Davenport 5000.0
2 161.0 Rory Kinnear 11000.0 Christoph Waltz Stephanie Sigman 393.0
3 23000.0 Christian Bale 27000.0 Tom Hardy Joseph Gordon-Levitt 23000.0
4 NaN Rob Walker 131.0 Doug Walker NaN 12.0
... ... ... ... ... ... ...
4911 318.0 Daphne Zuniga 637.0 Eric Mabius Crystal Lowe 470.0
4912 319.0 Valorie Curry 841.0 Natalie Zea Sam Underwood 593.0
4913 0.0 Maxwell Moody 0.0 Eva Boehnke David Chandler 0.0
4914 489.0 Daniel Henney 946.0 Alan Ruck Eliza Coupe 719.0
4915 16.0 Brian Herzlinger 86.0 John August Jon Gunn 23.0

4916 rows × 6 columns

완료