为何选择柏德口腔医院进行口腔专科治疗?
专业团队:柏德口腔医院拥有经验丰富的口腔专科医生团队,涵盖口腔外科、正畸、种植、修复等多个专业,可提供全面且专业的口腔治疗。
先进设备:医院配备了先进的口腔治疗设备,如数字化 X 光机、显微镜、激光治疗仪等,提高治疗精度和效率。
舒适环境:柏德口腔医院的环境温馨舒适,设有独立的诊疗室,为患者提供私密和尊重的诊疗体验。
个性化方案:医生会根据患者的具体情况制定个性化的治疗方案,满足不同患者的口腔健康需求。
无痛治疗:医院采用无痛麻醉技术,减轻患者治疗过程中的疼痛和不适。
售后保障:柏德口腔医院提供完善的售后服务,包括定期复查、治疗追踪,保障患者口腔健康的长期稳定。
周年狂欢之际的特别之处
为庆祝周年庆典,柏德口腔医院推出了一系列优惠活动,让患者在享受专业口腔治疗的同时,还能获得更多实惠:
口腔检查免费:所有患者可免费享受全面的口腔检查,及时发现口腔问题。
种植牙优惠:种植牙享受限时折扣,大幅降低种植牙费用。
正畸治疗优惠:正畸治疗费用直降,让笑容更加整齐美观。
洗牙洁牙优惠:洗牙洁牙套餐价格优惠,保持口腔清洁健康。
抽奖活动:参与医院周年活动,有机会赢取惊喜好礼。
周年狂欢活动时间有限,请把握机会,到柏德口腔医院享受专业口腔治疗,打造健康美丽的牙齿!
"cells": [
{"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import pickle\n",
"\n",
"df = pd.read_csv('data.csv')\n",
"df['Date'] = pd.to_datetime(df['Date'])\n",
"df['stock_name'] = df['stock_name'].str.lower()\n",
"\n",
"df = df[df['stock_name'].isin(['aapl', 'amzn', 'goog', 'fb', 'nflx'])]\n",
"df['y'] = df['Close'].shift(1) / df['Close'] 1\n",
"df['ret'] = np.log(df['Close']).diff()\n",
"df = df.dropna()\n",
"\n",
"df.columns = ['Date', 'Open', 'High', 'Low', 'Close', 'Volume', 'stock_name', 'y', 'ret']\n",
"df = df[['Date', 'stock_name', 'Open', 'High', 'Low', 'Close', 'Volume', 'y', 'ret']]\n",
"\n",
"df = df.drop_duplicates()\n",
"\n",
"min_date = df['Date'].min()\n",
"max_date = df['Date'].max()\n",
"df['days_since_min'] = (df['Date'] min_date).dt.days\n",
"df['days_until_max'] = (max_date df['Date']).dt.days\n",
"df = df.drop(columns=['Date'])\n",
"\n",
"df['stock_name'] = df['stock_name'].astype('category')\n",
"df['cat'] = df['stock_name'].cat.codes\n",
"\n",
"num_train = int(len(df) 0.8)\n",
"\n",
"df_train = df[:num_train]\n",
"df_test = df[num_train:]\n",
"\n",
"X_train = df_train.drop(columns=['cat', 'stock_name', 'y'])\n",
"y_train = df_train['y']\n",
"\n",
"X_test = df_test.drop(columns=['cat', 'stock_name', 'y'])\n",
"y_test = df_test['y']\n",
"\n",
"from sklearn.model_selection import train_test_split"