Practical analysis of user shopping basket prediction based on SVD matrix decomposition

Project video explanation:  Practical analysis of user shopping basket prediction based on SVD matrix decomposition_bilibili_bilibili

Main code:

# 导入需要的库
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from scipy.sparse.linalg import svds
from sklearn.preprocessing import MinMaxScaler

# 读取数据
data = pd.read_csv("shopping_trends.csv")
print(data.head())

# 查看数据维度
print(data.shape)

# 查看数据信息
print(data.info())

print(data.isna().sum())

# 查看重复值
print(data.duplicated().sum())

# 判断使用折扣和使用优惠码的情况是否同时出现
(data['Discount Applied'] == data['Promo Code Used']).all()

# 修改Customer ID格式
data['Customer ID'] = data['Customer ID'].astype(str)

# 删除使用优惠码的那一列