I shared lab ID because I saw someone else solved their error this way
I didn’t see any errors from unit test. I didn’t know there is errors produced by autograder. @Mubsi , thanks for pointing it out. I went back and here is what I found
Function "df_train_unskewed.std" in Code Cell UNQ_C1 does not contain the minumum number of expected arguments. We expected 1 arguments.
Code Cell UNQ_C1: Function 'make_standard_normal' is correct.
Code Cell UNQ_C2: Function 'lr_model' is correct.
Code Cell UNQ_C3: Function 'cindex' is correct.
Code Cell UNQ_C4: Function 'add_interactions' is correct.
If you see many functions being marked as incorrect, try to trace back your steps & identify if there is an incorrect function that is being used in other steps.
This dependency may be the cause of the errors.
This error seems to be complaining about df_train_unskewed.std. In my code, this is how I invoked it df_train_unskewed.std(). Based on pandas manual, the default for std without any arguments is calculating std on the columns, which is what we want here. So it should work without setting any argument explicitly. Did I do anything wrong?
And this is the output from my unit test, which again showed pass
Tmp Train:
field1 field2
0 1 4
1 2 5
2 10 11
Tmp Test:
field1 field2
0 1 4
1 3 6
2 10 11
Tmp Train After Standard Normal:
field1 field2
0 -0.845330 -0.774414
1 -0.258557 -0.354556
2 1.103887 1.128970
Tmp Test After Standard Normal:
field1 field2
0 -0.845330 -0.774414
1 0.084683 -0.011508
2 1.103887 1.128970
Training set transformed field1 has mean -7.401486830834377e-17 and standard deviation 1.0000
Test set transformed, field1 has mean 0.11441332564321975 and standard deviation 0.9749
Skew of training set field1 before transformation: 1.6523167403329906
Skew of training set field1 after transformation: 1.0857243344604632
Skew of test set field1 before transformation: 1.3896361387064917
Skew of test set field1 after transformation: 0.13709698849045696
All tests passed.