数据指标波动假设检验统计

eda/recommended_indexs/hypothesis_test.py

@@ -196,9 +196,13 @@ def chi_cal(data):
     t1=data.iloc[0]
     t2=data.iloc[1]
     t11_count=t1[0]
+    print("t11:{}".format(t11_count))
     t12_count=t1[1]
+    print("t12:{}".format(t12_count))
     t21_count=t2[0]
+    print("t21:{}".format(t21_count))
     t22_count=t2[1]
+    print("t22:{}".format(t22_count))
 
     ###理论值计算
     temp1=data.loc['共计']
@@ -206,9 +210,13 @@ def chi_cal(data):
     rate2=temp1[1]/temp1[2]
     temp2=data.iloc[2]
     t11_theory=temp2[0]*rate1
+    print("t11_theory:{}".format(t11_theory))
     t12_theory=temp2[1]*rate1
+    print("t12_theory:{}".format(t12_theory))
     t21_theory = temp2[0]*rate2
+    print("t21_theory:{}".format(t21_theory))
     t22_theory = temp2[1]*rate2
+    print("t22_theory:{}".format(t22_theory))
     #计算卡方值
     X=(((t11_count-t11_theory)**2)/t11_theory)+(((t12_count-t12_theory)**2)/t12_theory)+(((t21_count-t21_theory)**2)/t21_theory)+(((t22_count-t22_theory)**2)/t22_theory)
     print("卡方值为：{}".format(X))