diff --git a/testData/Apriori_mushroom.dat b/input/11.Apriori/mushroom.dat
similarity index 100%
rename from testData/Apriori_mushroom.dat
rename to input/11.Apriori/mushroom.dat
diff --git a/testData/Apriori_recent20bills.txt b/input/11.Apriori/recent20bills.txt
similarity index 100%
rename from testData/Apriori_recent20bills.txt
rename to input/11.Apriori/recent20bills.txt
diff --git a/src/python/11.Apriori/apriori.py b/src/python/11.Apriori/apriori.py
index b4daef2b..1f8e648d 100644
--- a/src/python/11.Apriori/apriori.py
+++ b/src/python/11.Apriori/apriori.py
@@ -239,7 +239,7 @@ def getActionIds():
     votesmart.apikey = 'a7fa40adec6f4a77178799fae4441030'
     actionIdList = []
     billTitleList = []
-    fr = open('testData/Apriori_recent20bills.txt')
+    fr = open('input/11.Apriori/recent20bills.txt')
     for line in fr.readlines():
         billNum = int(line.split('\t')[0])
         try:
@@ -306,7 +306,7 @@ def main():
     # 现在的的测试
     # 1. 加载数据
     dataSet = loadDataSet()
-    print(dataSet)
+    print dataSet
     # 调用 apriori 做购物篮分析
     # 支持度满足阈值的key集合L，和所有元素和支持度的全集suppoerData
     L, supportData = apriori(dataSet, minSupport=0.5)
@@ -331,7 +331,7 @@ def main():
     # # 项目实战
     # # 发现毒蘑菇的相似特性
     # # 得到全集的数据
-    # dataSet = [line.split() for line in open("testData/Apriori_mushroom.dat").readlines()]
+    # dataSet = [line.split() for line in open("input/11.Apriori/mushroom.dat").readlines()]
     # L, supportData = apriori(dataSet, minSupport=0.3)
     # # 2表示毒蘑菇，1表示可食用的蘑菇
     # # 找出关于2的频繁子项出来，就知道如果是毒蘑菇，那么出现频繁的也可能是毒蘑菇