python中的apriori算法导致数据集为空

Question

尝试在python上运行市场篮子分析。最后一步是 一个空的数据集，有人能建议为什么以及如何修复它吗

#importing relevant packages
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline

#loading data
dataset=pd.read_excel('http://archive.ics.uci.edu/ml/machine-learning-databases/00352/Online%20Retail.xlsx')

#Data preprocessing
#creating new seperate columns for invoice date and time
dataset['Date'] = pd.to_datetime(dataset['InvoiceDate']).dt.date
dataset['Time'] = pd.to_datetime(dataset['InvoiceDate']).dt.time

#converting InvoiceNo to numeric datatype and to check if there is other value than number 
#it will convert into Nan
dataset['InvoiceNo'] = pd.to_numeric(dataset['InvoiceNo'],errors='coerce')

#removing rows with missing values
dataset=dataset.dropna()

baskets = (dataset.groupby(['InvoiceNo', 'Description'])['Quantity']
          .sum().unstack().reset_index().fillna(0)
          .set_index('InvoiceNo'))
baskets.head()

from mlxtend.frequent_patterns import apriori, association_rules

def hot_encode(x): 
    if(x<= 0): 
        return 0
    if(x>= 1): 
        return 1

baskets_encoded = baskets.applymap(hot_encode) 
baskets = baskets_encoded 
frq_items = apriori(baskets, min_support = 0.05, use_colnames = True)
rules = association_rules(frq_items, metric ="confidence", min_threshold = 0.8) 
rules = rules.sort_values('confidence', ascending =False) 
print(rules.head())

下面是空数据框：

Columns: [antecedents, consequents, antecedent support, consequent support, support, confidence, lift, leverage, conviction]
Index: []

数据应如下例所示：