# 划分区间 # 训练集历史区间、中间区间、标签区间 train_history_field = off_train[off_train['date_received'].isin(pd.date_range('2016/3/2', periods=60))] # [20160302,20160501) train_middle_field = off_train[off_train['date'].isin(pd.date_range('2016/5/1', periods=15))] # [20160501,20160516) train_label_field = off_train[off_train['date_received'].isin(pd.date_range('2016/5/16', periods=31))] # [20160516,20160616) # 验证集历史区间、中间区间、标签区间 validate_history_field = off_train[off_train['date_received'].isin(pd.date_range('2016/1/16', periods=60))] # [20160116,20160316) validate_middle_field = off_train[off_train['date'].isin(pd.date_range('2016/3/16', periods=15))] # [20160316,20160331) validate_label_field = off_train[off_train['date_received'].isin(pd.date_range('2016/3/31', periods=31))] # [20160331,20160501) # 测试集历史区间、中间区间、标签区间 test_history_field = off_train[off_train['date_received'].isin(pd.date_range('2016/4/17', periods=60))] # [20160417,20160616) test_middle_field = off_train[off_train['date'].isin(pd.date_range('2016/6/16', periods=15))] # [20160616,20160701) test_label_field = off_test.copy() # [20160701,20160801)将其改为一个函数

可以将这段代码封装成一个函数，以便在需要时可以直接调用。以下是一个可能的实现：

import pandas as pd

def split_dataset(off_train, off_test):
    # 划分区间
    # 训练集历史区间、中间区间、标签区间
    train_history_field = off_train[off_train['date_received'].isin(pd.date_range('2016/3/2', periods=60))]  # [20160302,20160501)
    train_middle_field = off_train[off_train['date'].isin(pd.date_range('2016/5/1', periods=15))]  # [20160501,20160516)
    train_label_field = off_train[off_train['date_received'].isin(pd.date_range('2016/5/16', periods=31))]  # [20160516,20160616)
    # 验证集历史区间、中间区间、标签区间
    validate_history_field = off_train[off_train['date_received'].isin(pd.date_range('2016/1/16', periods=60))]  # [20160116,20160316)
    validate_middle_field = off_train[off_train['date'].isin(pd.date_range('2016/3/16', periods=15))]  # [20160316,20160331)
    validate_label_field = off_train[off_train['date_received'].isin(pd.date_range('2016/3/31', periods=31))]  # [20160331,20160501)
    # 测试集历史区间、中间区间、标签区间
    test_history_field = off_train[off_train['date_received'].isin(pd.date_range('2016/4/17', periods=60))]  # [20160417,20160616)
    test_middle_field = off_train[off_train['date'].isin(pd.date_range('2016/6/16', periods=15))]  # [20160616,20160701)
    test_label_field = off_test.copy()  # [20160701,20160801)
    
    return (train_history_field, train_middle_field, train_label_field,
            validate_history_field, validate_middle_field, validate_label_field,
            test_history_field, test_middle_field, test_label_field)

调用该函数时，需要传入 `off_train` 和 `off_test` 两个数据集作为参数，函数将返回九个数据集，分别对应训练集、验证集和测试集的历史区间、中间区间和标签区间。