데이터 엔지니어

Programming Language/Python

[Kaggle] London Bike Sharing Dataset 딥러닝 모델 만들어보기

https://www.kaggle.com/datasets/hmavrodiev/london-bike-sharing-dataset London bike sharing dataset Historical data for bike sharing in London 'Powered by TfL Open Data' www.kaggle.com import numpy as np import pandas as pd import os for dirname, _, filenames in os.walk('/kaggle/input'): for filename in filenames: print(os.path.join(dirname, filename)) import matplotlib.pyplot as plt import seabo..

Programming Language/Python

[Kaggle] London Bike Sharing Dataset 데이터 전처리 해보기

https://www.kaggle.com/datasets/hmavrodiev/london-bike-sharing-dataset London bike sharing dataset Historical data for bike sharing in London 'Powered by TfL Open Data' www.kaggle.com import numpy as np import pandas as pd import os for dirname, _, filenames in os.walk('/kaggle/input'): for filename in filenames: print(os.path.join(dirname, filename)) import matplotlib.pyplot as plt import seabo..

Programming Language/Python

[Python] 데이터프레임의 구조, 타입, 컬럼 확인하는 방법

df = pd.read_csv('/kaggle/input/london-bike-sharing-dataset/london_merged.csv') df.head() print('\n', df.shape) print('\n', df.dtypes) print('\n', df.columns)

Programming Language/Python

[Python] read_csv의 parse_dates 옵션 사용해보기

기본형 df = pd.read_csv('/kaggle/input/london-bike-sharing-dataset/london_merged.csv') df.head() 데이터의 구조, 타입, 컬럼 확인하기 print('\n', df.shape) print('\n', df.dtypes) print('\n', df.columns) timestamp가 object 형인 것을 확인할 수 있다. 다음은 parse_dates 를 사용해보자. df = pd.read_csv('/kaggle/input/london-bike-sharing-dataset/london_merged.csv', parse_dates = ['timestamp']) # df = pd.read_c..

Data Engineering/Airflow

[Airflow] Bash Operator로 간단한 echo DAG 만들어보기

3_bash_operator_echo.py from airflow import DAG from airflow.operators.bash_operator import BashOperator from datetime import datetime default_args = { 'owner' : 'ParkGyeongTae' } dag = DAG ( dag_id = '3_bash_operator_echo', start_date = datetime(2022, 5, 4), schedule_interval = '* * * * *', catchup = False, tags = ['test'], description = 'Bash Operator Sample', default_args = default_args ) ech..

Data Engineering/Airflow

[Airflow] Bash Operator로 간단한 Sleep Dag 만들어보기

2_bash_operator.py from airflow import DAG from airflow.operators.bash_operator import BashOperator from datetime import datetime default_args = { 'owner' : 'ParkGyeongTae' } dag = DAG ( dag_id = '2_bash_operator', start_date = datetime(2022, 5, 4), schedule_interval = '* * * * *', catchup = False, tags = ['test'], description = 'Bash Operator Sample', default_args = default_args ) sleep_1 = Bas..

Data Engineering/Airflow

[Airflow] Python Operator로 간단한 Dag 만들어보기

1_python_operator.py from airflow import DAG from airflow.operators.python_operator import PythonOperator from datetime import datetime default_args = { 'owner' : 'ParkGyeongTae' } dag = DAG ( dag_id = '1_python_operator', start_date = datetime(2022, 5, 4), schedule_interval = '* * * * *', catchup = False, tags = ['test'], description = 'Python Operator Sample', default_args = default_args ) def..

Programming Language/Python

[Kaggle] London bike sharing dataset 그래프 그려보기

https://www.kaggle.com/datasets/hmavrodiev/london-bike-sharing-dataset London bike sharing dataset Historical data for bike sharing in London 'Powered by TfL Open Data' www.kaggle.com import numpy as np import pandas as pd import os for dirname, _, filenames in os.walk('/kaggle/input'): for filename in filenames: print(os.path.join(dirname, filename)) import matplotlib.pyplot as plt import seabo..

Programming Language/Python

[Kaggle] London bike sharing dataset 데이터 살펴보기

https://www.kaggle.com/datasets/hmavrodiev/london-bike-sharing-dataset London bike sharing dataset Historical data for bike sharing in London 'Powered by TfL Open Data' www.kaggle.com import numpy as np import pandas as pd import os for dirname, _, filenames in os.walk('/kaggle/input'): for filename in filenames: print(os.path.join(dirname, filename)) import matplotlib.pyplot as plt import seabo..

Programming Language/Python

[Python] RL, 강화학습 Frozen-Lake Dummy Q-Learning 실행하는 방법

https://github.com/ParkGyeongTae/dqn-atari-breakout/tree/main/3_frozenlake_v0 GitHub - ParkGyeongTae/dqn-atari-breakout Contribute to ParkGyeongTae/dqn-atari-breakout development by creating an account on GitHub. github.com ### Step 1) 아나콘다 가상환경 만들기 conda create -n py37 python=3.7 ### Step 2) 가상환경 접속 conda activate py37 ### Step 3) 라이브러리 설치 pip install gym==0.23.1 pip install pygame==2.1.2 pip i..

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