conn_str = pyodbc.connect('DRIVER={ODBC Driver 17 for SQL Server}; SERVER=<server>; DATABASE=tpcxbb_1gb; UID=<username>; PWD=<password>') input_query = '''SELECT ss_customer_sk AS customer, ROUND(COALESCE(return
Ski rental (linear regression) 1 - Introduction 2 - Prepare data 3 - Train model 4 - Deploy model Categorize customers (k-means clustering) NYC taxi tips (classification) Create a Python model using revoscalepy R Sample data Concepts How-to guides Reference Resources 下载PDF Learn...
prepare_data(box_data_edu)) box_epx_edu.set_global_opts( title_opts=opts.TitleOpts( title='不同学历、工作年限与薪资水平的关系' ,subtitle='数据取自:和鲸社区' ,pos_left='center' ), legend_opts=opts.LegendOpts( pos_right='1%' ,legend_icon='circle' ,item_width=10 ), yaxis_opts=...
midwest=pd.read_csv("https://raw.githubusercontent.com/selva86/datasets/master/midwest_filter.csv")# Prepare Data # Createasmany colorsasthere are unique midwest['category']categories=np.unique(midwest['category'])colors=[plt.cm.tab10(i/float(len(categories)-1))foriinrange(len(categories))...
import matplotlib.patches as mpatches # Prepare Data df_raw = pd.read_csv("./datasets/mpg_ggplot2.csv") cyl_colors = {4: 'tab:red', 5: 'tab:green', 6: 'tab:blue', 8: 'tab:orange'} df_raw['cyl_color'] = df_raw.cyl.map(cyl_colors) # Mean and Median city mileage by ma...
m.prepare_data()# Perform matching m.match(caliper=None,replace=False)# Evaluate matches via chi-square test m.evaluate() 这里的K=3,代表会找出三个候选集,之前案例二中是一个。 数据集的样子: 那么此时:case是干预treatment; 这个公式,"CASE ~ AGE + TOTAL_YRS"就是计算倾向性得分的时候会使用到的...
# Prepare datadf['year'] = [d.year for d in df.date]df['month'] = [d.strftime('%b') for d in df.date]years = df['year'].unique() # Draw Plotfig, axes = plt.subplots(1, 2, figsize=(20,7), dpi= 80)sns.boxplo...
# prepare data X = series.values X = X.astype('float32') train_size = int(len(X) * 0.50) train, test = X[0:train_size], X[train_size:] # walk-foward validation history = [x for x in train] predictions = list() for i in range(len(test)): ...
# Import Datadf = pd.read_csv('https://raw.githubusercontent.com/selva86/datasets/master/a10.csv', parse_dates=['date'], index_col='date')df.reset_index(inplace=True) # Prepare datadf['year'] = [d.year for d in df.date]df['month'] = [d.strftime('%b') for d in df.dat...
tpc_prepare() N 内核不支持显式prepare transaction。 tpc_commit([xid]) Y - tpc_rollback([xid]) Y - tpc_recover() Y - closed Y - cancel() Y - reset() N 不支持DISCARD ALL。 dsn Y - Transaction control methods and attributes. ...