전체 글 (33) 썸네일형 리스트형 [impala / oracle / presto/spark] Confusing Date SQL Statement Differences 1. impala tx_dt between from_timestamp(date_add(to_timestamp(t1.base_dt, 'yyyyMMdd'),-3),'yyyyMMdd') and t1.base_dt2 a.nbr = cat(b.nbr as string) select substr(to_date(months_add(now(),-1)),1,7) as base_ym base_dt = to_date(now()) base_dt = to_date(date_add(now(),-1)) to_timestamp(tx_tmstmp,'yyyyMMddHHmmss') > date_add(now(), interval -10 minutes) count(case when t1.base_dt = from_timestamp(last.. [ML] XGBClassifier sample code # First XGBoost model for Pima Indians dataset from numpy import loadtxt from xgboost import XGBClassifier from sklearn.model_selection import train_test_split from sklearn.metrics import accuracy_score # load data dataset = loadtxt('pima-indians-diabetes.csv', delimiter=",") # split data into X and y X = dataset[:,0:8] Y = dataset[:,8] # split data into train and test sets seed = 7 test_size = .. [pandas] MinMaxScaling sample code import pandas as pd a = pd.read_csv('data/mtcars.csv', index_col=0) # case1 min_data = a['qsec'].min() max_data = a['qsec'].max() a['qsec2'] = (a['qsec'] - min_data) / (max_data - min_data) result = len(a['qsec2'] > 0.5) print(result) # case2 from sklearn.preprocessing import MinMaxScaler scaler = MinMaxScaler() a['qsec3'] = scaler.fit_transform(a[['qsec']]) result2 = len(a['qsec3']>0.5) print(r.. 이전 1 2 3 4 5 6 ··· 11 다음 목록 더보기