（2）使用python实现Apriori算法中的频繁项集生成过程，并使用上述数据集输出频繁项集。

以下是Python中使用Apriori算法实现频繁项集生成过程的代码示例，使用的数据集与上述代码示例相同：

# 导入相关库
import pandas as pd
from itertools import combinations

# 读取数据集
data = pd.read_excel('data.xlsx')

# 将数据集转换为适合进行关联分析的格式
def encode_units(x):
    if x <= 0:
        return 0
    if x >= 1:
        return 1

data = data.applymap(encode_units)

# 定义函数生成候选项集
def generate_candidate_set(data):
    candidate_set = []
    for i in range(len(data.columns)):
        col = data.iloc[:, i]
        for j in range(i+1, len(data.columns)):
            next_col = data.iloc[:, j]
            candidate = list(col.index & next_col.index)
            candidate_set.append([candidate, i, j])
    return candidate_set

# 定义函数验证候选项集是否满足支持度要求
def check_support(candidate_set, data, min_support):
    support = []
    for candidate in candidate_set:
        count = 0
        for index, row in data.iterrows():
            if set(candidate[0]).issubset(set(row.index)):
                count += 1
        support.append(count)
    support = [sup/len(data) for sup in support]
    frequent_set = [candidate_set[i] for i in range(len(candidate_set)) if support[i] >= min_support]
    return frequent_set, support

# 定义函数生成频繁项集
def generate_frequent_set(data, min_support):
    candidate_set = generate_candidate_set(data)
    frequent_set, support = check_support(candidate_set, data, min_support)
    while len(candidate_set) > 0:
        candidate_set = generate_candidate_set(pd.DataFrame([set(freq[0]) for freq in frequent_set]))
        new_frequent_set, new_support = check_support(candidate_set, data, min_support)
        frequent_set += new_frequent_set
        support += new_support
    frequent_set = pd.DataFrame(frequent_set, columns=['itemset', 'col1', 'col2'])
    frequent_set['support'] = support
    frequent_set['length'] = frequent_set['itemset'].apply(len)
    return frequent_set

# 执行频繁项集生成过程
frequent_itemsets = generate_frequent_set(data, min_support=0.05)

# 输出频繁项集
print(frequent_itemsets)

其中，`generate_candidate_set`函数生成候选项集，`check_support`函数验证候选项集是否满足支持度要求，`generate_frequent_set`函数生成频繁项集。最后，使用`generate_frequent_set`函数获取频繁项集，并输出结果。