Hi! I’m on the Predict Credit Card Fraud project, and I’m having some issues with step 3:
- We have a lot of information about the
type of transaction we are looking at. Let’s create a new column called
isPayment that assigns a
type is “PAYMENT” or “DEBIT”, and a
The hint is as follows:
You can create a new column for a
pandas DataFrame like this:
df['new_column'] = value
You can filter a DataFrame for specific values like this:
df[df['filter_column'] == value]
if transactions[transactions[‘type’] in (“PAYMENT”, “DEBIT”)]:
transactions[‘isPayment’] = 1
transactions[‘isPayment’] = 0
ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
Am I just supposed to ignore the hint and guess with the DataFrame methods?
@dentarthurdent42 I am assuming you dont still need help with this, but did you get the transactions 1-3 to work with a prediction? I can’t get it working and cant figure out why
This is what I used:
# Create isPayment field
transactions['isPayment'] = 0
transactions['isPayment'][transactions['type'] == 'DEBIT'] = 1
transactions['isPayment'][transactions['type'] == 'PAYMENT'] = 1
# Create isMovement field
transactions['isMovement'] = 0
transactions['isMovement'][transactions['type'] == 'CASH_OUT'] = 1
transactions['isMovement'][transactions['type'] == 'TRANSFER'] = 1
I don’t remember what I did at this point I am so far away from there, like half way through the AI/ML Engineering career path, but I believe I ended up getting it working somehow having it filter through for both at the same time. I think it was using .loc( ). I might go back and check when I have the time so thz for answering.
Also lol at it saying you answered your own question on the first post, got rly confused by that for a second.