이상향

데이터 출처(월드컵 출전선수 골기록 데이터) : https://www.kaggle.com/darinhawley/fifa-world-cup-goalscorers-19302018 FIFA World Cup Goalscorers 1930-2018 List of all FIFA World Cup goalscoreres 1930-2018 www.kaggle.com 데이터 URL : https://raw.githubusercontent.com/Datamanim/datarepo/main/worldcup/worldcupgoals.csv import pandas as pd df = pd.read_csv('https://raw.githubusercontent.com/Datamanim/datarepo/main/worldcu..

데이터 출처(유튜브 공범컨텐츠 동영상 데이터) : https://www.kaggle.com/kukuroo3/youtube-episodic-contents-kr youtube ep contents statistics(interval 10min) monitoring Mafia GAME(daily update) www.kaggle.com 데이터 URL : dataurl1 (비디오 정보) = https://raw.githubusercontent.com/Datamanim/datarepo/main/youtube/videoInfo.csv dataurl2 (참가자 채널 정보) = https://raw.githubusercontent.com/Datamanim/datarepo/main/youtube/channelInfo...

데이터 출처(유튜브 데일리 인기동영상) : https://www.kaggle.com/rsrishav/youtube-trending-video-dataset?select=KR_youtube_trending_data.csv YouTube Trending Video Dataset (updated daily) YouTube Trending Video data-set which gets updated daily. www.kaggle.com 데이터 URL : https://raw.githubusercontent.com/Datamanim/datarepo/main/youtube/youtube.csv import pandas as pd df = pd.read_csv("https://raw.githubusercontent..

# pandas 문법으로 풀이 import pandas as pd a = pd.read_csv('data/mtcars.csv', index_col=0) # Min Max Scale은 (X-min) / (max-min) qsec_max = a['qsec'].max() qsec_min = a['qsec'].min() a['minmax_scaled_qsec'] = (a['qsec'] - qsec_min) / (qsec_max - qsec_min) over_0_5 = a[a['minmax_scaled_qsec'] > 0.5] nrows = over_0_5.shape[0] print(f'Pandas 문법 사용 했을 때 0.5보다 큰 레코드 수는 {nrows}') # sklearn의 MinMaxScaler 사용 i..