【IWR_231226】Python餐饮业用户流失预测

import random
import string
from datetime import datetime

def generate_random_string(length=3):
    characters = string.ascii_uppercase
    return ''.join(random.choice(characters) for _ in range(length))

def generate_timestamped_string(separator='_'):
    timestamp = datetime.now().strftime('%y%m%d') # %H%M%S
    random_part = generate_random_string(length=3)
    return random_part+separator+timestamp

timestamped_string = generate_timestamped_string()
print('【{0}】'.format(timestamped_string))

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
# 读取数据
users = pd.read_csv('./data/user_loss.csv', encoding='gbk')
info = pd.read_csv('./data/info_new.csv', encoding='utf-8')
print('客户信息表的维数：', users.shape)
print('订单详情表的维数：', info.shape)
客户信息表的维数： (2431, 36)
订单详情表的维数： (6611, 21)
users.head()