Iterating through rows, checking if the rows contains a specific value, returning T or F

Question

def delinquent(data):
#loops through each time of the mortgage performance review
for time in len(data.index)):
    data.index[data.columns == "1"]

Pre Warning I'm very much a beginner at pandas and dataFrames

I'm trying to see if a loan at any point in its progression went delinquent. I have created a df of each loan as a row (29962), and each column (26) is a specific time (month_year) when the loan status was reviewed. If the loan was reported as delinquent, in any month_year column, the value for that loan in that specific column would be "1".

In the code above I tried to use an a for loop iterate through the rows checking the values of each column for "1". I want the code to return True or False, then if possible make a new column Labeled "delinquent" shows whether or not (T/F) a loan ever went delinquent. I'd like to add that new column back to my original dataFrame (called nsmo) so I can look at the accuracy of credit scores (at the origination of the loan) in predicting whether or not a loan will go delinquent.

Thank you, apologies for the burden of my question.

I'm using py 3 and pandas

Can you provide some sample input and the corresponding output? See minimal reproducible example, How to Ask, help center. — AMC

Code Different Code Different · Accepted Answer · 2020-04-27T23:57:36

Try this:

df['delinquent'] = df.eq('1').any(axis=1)

But be careful with your datatypes. The string '1' sounds like it should be the number 1, or better yet, True and False.

Iterating through rows, checking if the rows contains a specific value, returning T or F

1 Answers