코랩을 통해서 데이터를 다운로드하고, 압축을 푸는 과정까지 진행해보겠습니다.
!mkdir ./kaggle
import json
token = {"username":####,"key":####}
with open('/content/kaggle/kaggle.json', 'w') as file:
json.dump(token, file)
!chmod 600 ./kaggle/kaggle.json
!cp /content/kaggle/kaggle.json ~/.kaggle/kaggle.json
!kaggle config set -n path -v{/content}
from google.colab import drive
drive.mount('/gdrive')
cd ../gdrive/My Drive/Kaggle/WSDM_210815/data
!kaggle competitions download -c kkbox-churn-prediction-challenge
!p7zip -d {/content}/competitions/kkbox-churn-prediction-challenge/user_logs.csv.7z
7z로 압축이 되어있기 때문에 그에 맞는 압축해제를 진행
-d 는 압축 해제 후 파일 삭제 옵션임
!p7zip -d ./kkbox-churn-prediction-challenge/user_logs.csv.7z
!ls ./kkbox-churn-prediction-challenge
!p7zip -d ./kkbox-churn-prediction-challenge/members_v3.csv.7z
!p7zip -d ./kkbox-churn-prediction-challenge/train.csv.7z
!p7zip -d ./kkbox-churn-prediction-challenge/transactions_v2.csv.7z
!p7zip -d ./kkbox-churn-prediction-challenge/sample_submission_v2.csv.7z
!p7zip -d ./kkbox-churn-prediction-challenge/train_v2.csv.7z
!p7zip -d ./kkbox-churn-prediction-challenge/user_logs_v2.csv.7z
!p7zip -d ./kkbox-churn-prediction-challenge/sample_submission_zero.csv.7z
!p7zip -d ./kkbox-churn-prediction-challenge/transactions.csv.7z