Python 关联规则挖掘：分析韩国自行车租赁数据

import csv
import pyfpgrowth

transactions = []
with open('D://R//韩国自行车租用数据4.csv', 'r') as f:
    reader = csv.reader(f)
    for row in reader:
        transactions.append(row)

patterns = pyfpgrowth.find_frequent_patterns(transactions, 3)
rules = pyfpgrowth.generate_association_rules(patterns, 0.7)
print(patterns)
print(rules)	

{('Holiday', 'No'): 24, ('Autumn', 'Holiday', 'No'): 24, ('Holiday', 'No', 'low'): 24, ('Autumn', 'Holiday', 'No', 'low'): 24, ('No', 'Spring'): 48, ('No', 'No Holiday', 'Spring'): 48, ('No', 'Spring', 'low'): 48, ('No', 'No Holiday', 'Spring', 'low'): 48, ('Autumn', 'No'): 247, ('Autumn', 'No', 'No Holiday'): 223, ('Autumn', 'No', 'low'): 247, ('Autumn', 'No', 'No Holiday', 'low'): 223, ('No', 'No Holiday'): 271, ('No', 'No Holiday', 'low'): 271, ('No', 'low'): 295, ('Holiday', 'Summer', 'high'): 22, ('Holiday', 'Summer', 'Yes', 'high'): 22, ('Holiday', 'Summer', 'mid'): 24, ('Holiday', 'Summer', 'Yes', 'mid'): 24, ('Holiday', 'Summer', 'Yes'): 48, ('Holiday', 'Spring', 'high'): 20, ('Holiday', 'Spring', 'Yes', 'high'): 20, ('Holiday', 'Spring', 'mid'): 24, ('Holiday', 'Spring', 'Yes', 'mid'): 24, ('Holiday', 'Spring', 'low'): 28, ('Holiday', 'Spring', 'Yes', 'low'): 28, ('Holiday', 'Spring', 'Yes'): 72, ('Holiday', 'high'): 87, ('Holiday', 'Yes', 'high'): 87, ('Autumn', 'Holiday', 'high'): 45, ('Autumn', 'Holiday', 'Yes', 'high'): 45, ('Autumn', 'Holiday', 'low'): 37, ('Autumn', 'Holiday', 'Yes', 'low'): 13, ('Autumn', 'Holiday', 'mid'): 38, ('Autumn', 'Holiday', 'Yes', 'mid'): 38, ('Autumn', 'Holiday', 'Yes'): 96, ('Holiday', 'mid'): 128, ('Holiday', 'Winter', 'mid'): 42, ('Holiday', 'Yes', 'mid'): 128, ('Holiday', 'Winter', 'Yes', 'mid'): 42, ('Holiday', 'Winter'): 192, ('Holiday', 'Winter', 'low'): 150, ('Holiday', 'Winter', 'Yes'): 192, ('Holiday', 'Winter', 'Yes', 'low'): 150, ('Holiday', 'low'): 217, ('Holiday', 'Yes', 'low'): 193, ('Holiday', 'Yes'): 408, ('Winter', 'mid'): 862, ('Winter', 'Yes', 'mid'): 862, ('No Holiday', 'Winter', 'mid'): 820, ('No Holiday', 'Winter', 'Yes', 'mid'): 820, ('Winter', 'low'): 1298, ('Winter', 'Yes', 'low'): 1298, ('No Holiday', 'Winter', 'low'): 1148, ('No Holiday', 'Winter', 'Yes', 'low'): 1148, ('No Holiday', 'Winter'): 1968, ('No Holiday', 'Winter', 'Yes'): 1968, ('Winter', 'Yes'): 2160, ('Autumn', 'Yes', 'low'): 296, ('Autumn', 'No Holiday', 'Yes', 'low'): 283, ('Autumn', 'No Holiday', 'low'): 506, ('Autumn', 'high'): 792, ('Autumn', 'Yes', 'high'): 792, ('Autumn', 'No Holiday', 'high'): 747, ('Autumn', 'No Holiday', 'Yes', 'high'): 747, ('Autumn', 'mid'): 849, ('Autumn', 'Yes', 'mid'): 849, ('Autumn', 'No Holiday', 'mid'): 811, ('Autumn', 'No Holiday', 'Yes', 'mid'): 811, ('Autumn', 'Yes'): 1937, ('Autumn', 'No Holiday', 'Yes'): 1841, ('Autumn', 'No Holiday'): 2064, ('Spring', 'Yes', 'low'): 572, ('No Holiday', 'Spring', 'Yes', 'low'): 544, ('No Holiday', 'Spring', 'low'): 592, ('Spring', 'high'): 650, ('No Holiday', 'Spring', 'high'): 630, ('Spring', 'Yes', 'high'): 650, ('No Holiday', 'Spring', 'Yes', 'high'): 630, ('Spring', 'mid'): 938, ('Spring', 'Yes', 'mid'): 938, ('No Holiday', 'Spring', 'mid'): 914, ('No Holiday', 'Spring', 'Yes', 'mid'): 914, ('No Holiday', 'Spring'): 2136, ('No Holiday', 'Spring', 'Yes'): 2088, ('Spring', 'Yes'): 2160, ('Summer', 'low'): 229, ('No Holiday', 'Summer', 'low'): 227, ('Summer', 'Yes', 'low'): 229, ('No Holiday', 'Summer', 'Yes', 'low'): 227, ('Summer', 'high'): 978, ('No Holiday', 'Summer', 'high'): 956, ('Summer', 'Yes', 'high'): 978, ('No Holiday', 'Summer', 'Yes', 'high'): 956, ('Summer', 'mid'): 1001, ('No Holiday', 'Summer', 'mid'): 977, ('Summer', 'Yes', 'mid'): 1001, ('No Holiday', 'Summer', 'Yes', 'mid'): 977, ('No Holiday', 'Summer'): 2160, ('No Holiday', 'Summer', 'Yes'): 2160, ('Summer', 'Yes'): 2208, ('high',): 2420, ('No Holiday', 'high'): 2333, ('Yes', 'high'): 2420, ('No Holiday', 'Yes', 'high'): 2333, ('Yes', 'low'): 2395, ('No Holiday', 'Yes', 'low'): 2202, ('No Holiday', 'low'): 2473, ('mid',): 3650, ('Yes', 'mid'): 3650, ('No Holiday', 'mid'): 3522, ('No Holiday', 'Yes', 'mid'): 3522, ('No Holiday',): 8328, ('No Holiday', 'Yes'): 8057, ('Yes',): 8465}

{('Holiday', 'No'): (('Autumn', 'low'), 1.0), ('Autumn', 'Holiday', 'No'): (('low',), 1.0), ('Holiday', 'No', 'low'): (('Autumn',), 1.0), ('No', 'Spring'): (('No Holiday', 'low'), 1.0), ('No', 'No Holiday', 'Spring'): (('low',), 1.0), ('No', 'Spring', 'low'): (('No Holiday',), 1.0), ('Autumn', 'No'): (('No Holiday', 'low'), 0.902834008097166), ('Autumn', 'No', 'No Holiday'): (('low',), 1.0), ('Autumn', 'No', 'low'): (('No Holiday',), 0.902834008097166), ('No', 'No Holiday'): (('low',), 1.0), ('No', 'low'): (('No Holiday',), 0.9186440677966101), ('Holiday', 'Summer', 'high'): (('Yes',), 1.0), ('Holiday', 'Summer', 'mid'): (('Yes',), 1.0), ('Holiday', 'Spring', 'high'): (('Yes',), 1.0), ('Holiday', 'Spring', 'mid'): (('Yes',), 1.0), ('Holiday', 'Spring', 'low'): (('Yes',), 1.0), ('Holiday', 'high'): (('Yes',), 1.0), ('Autumn', 'Holiday', 'high'): (('Yes',), 1.0), ('Autumn', 'Holiday', 'mid'): (('Yes',), 1.0), ('Holiday', 'mid'): (('Yes',), 1.0), ('Holiday', 'Winter', 'mid'): (('Yes',), 1.0), ('Holiday', 'Winter'): (('Yes',), 1.0), ('Holiday', 'Winter', 'low'): (('Yes',), 1.0), ('Winter', 'mid'): (('No Holiday', 'Yes'), 0.951276102088167), ('No Holiday', 'Winter', 'mid'): (('Yes',), 1.0), ('Winter', 'Yes', 'mid'): (('No Holiday',), 0.951276102088167), ('Winter', 'low'): (('Yes',), 1.0), ('No Holiday', 'Winter', 'low'): (('Yes',), 1.0), ('No Holiday', 'Winter'): (('Yes',), 1.0), ('Winter', 'Yes'): (('No Holiday',), 0.9111111111111111), ('Autumn', 'Yes', 'low'): (('No Holiday',), 0.956081081081081), ('Autumn', 'high'): (('No Holiday', 'Yes'), 0.9431818181818182), ('Autumn', 'No Holiday', 'high'): (('Yes',), 1.0), ('Autumn', 'Yes', 'high'): (('No Holiday',), 0.9431818181818182), ('Autumn', 'mid'): (('No Holiday', 'Yes'), 0.9552414605418139), ('Autumn', 'No Holiday', 'mid'): (('Yes',), 1.0), ('Autumn', 'Yes', 'mid'): (('No Holiday',), 0.9552414605418139), ('Autumn', 'Yes'): (('No Holiday',), 0.9504388229220444), ('No Holiday', 'Spring', 'low'): (('Yes',), 0.918918918918919), ('Spring', 'Yes', 'low'): (('No Holiday',), 0.951048951048951), ('Spring', 'high'): (('No Holiday', 'Yes'), 0.9692307692307692), ('No Holiday', 'Spring', 'high'): (('Yes',), 1.0), ('Spring', 'Yes', 'high'): (('No Holiday',), 0.9692307692307692), ('Spring', 'mid'): (('No Holiday', 'Yes'), 0.9744136460554371), ('No Holiday', 'Spring', 'mid'): (('Yes',), 1.0), ('Spring', 'Yes', 'mid'): (('No Holiday',), 0.9744136460554371), ('No Holiday', 'Spring'): (('Yes',), 0.9775280898876404), ('Spring', 'Yes'): (('No Holiday',), 0.9666666666666667), ('Summer', 'low'): (('No Holiday', 'Yes'), 0.9912663755458515), ('No Holiday', 'Summer', 'low'): (('Yes',), 1.0), ('Summer', 'Yes', 'low'): (('No Holiday',), 0.9912663755458515), ('Summer', 'high'): (('No Holiday', 'Yes'), 0.9775051124744376), ('No Holiday', 'Summer', 'high'): (('Yes',), 1.0), ('Summer', 'Yes', 'high'): (('No Holiday',), 0.9775051124744376), ('Summer', 'mid'): (('No Holiday', 'Yes'), 0.9760239760239761), ('No Holiday', 'Summer', 'mid'): (('Yes',), 1.0), ('Summer', 'Yes', 'mid'): (('No Holiday',), 0.9760239760239761), ('No Holiday', 'Summer'): (('Yes',), 1.0), ('Summer', 'Yes'): (('No Holiday',), 0.9782608695652174), ('high',): (('No Holiday', 'Yes'), 0.9640495867768595), ('No Holiday', 'high'): (('Yes',), 1.0), ('Yes', 'high'): (('No Holiday',), 0.9640495867768595), ('Yes', 'low'): (('No Holiday',), 0.9194154488517745), ('mid',): (('No Holiday', 'Yes'), 0.9649315068493151), ('No Holiday', 'mid'): (('Yes',), 1.0), ('Yes', 'mid'): (('No Holiday',), 0.9649315068493151), ('No Holiday',): (('Yes',), 0.9674591738712777), ('Yes',): (('No Holiday',), 0.951801535735381)}

该数据集中的频繁模式和关联规则可以帮助我们了解租用自行车的状况。例如，从频繁模式中可以看出，租用自行车的高峰期主要集中在冬季和无假期，而秋季和有假期则相对较低；从关联规则中可以看出，租用自行车的人更倾向于选择低温季节和工作日进行租用，而高温季节和休息日则相对较少。这些信息可以为租用自行车的商家提供指导，例如可以在冬季和无假期增加自行车的租用数量，或者在低温季节和工作日提供更多的租用优惠。