对groupby函数应用过滤

import pandas as pd

# 创建示例数据集
data = {
    'Date': ['2023-01-01', '2023-01-02', '2023-02-01', '2023-02-02', '2023-03-01'],
    'Product': ['A', 'B', 'A', 'B', 'A'],
    'Sales': [100, 200, 150, 250, 300]
}

df = pd.DataFrame(data)

# 将日期列转换为 datetime 类型
df['Date'] = pd.to_datetime(df['Date'])

# 按产品和月份分组，并计算每个组的总销售额
df['Month'] = df['Date'].dt.month
grouped = df.groupby(['Product', 'Month'])['Sales'].sum().reset_index()

# 过滤出销售额超过 300 的记录
filtered = grouped[grouped['Sales'] > 300]

print(filtered)

# 确保分组键的数据类型一致
df['Month'] = df['Date'].dt.month.astype(int)

# 检查过滤条件是否正确
filtered = grouped[grouped['Sales'] > 300]