Categorical Assignments Using Pd.apply Based On Multiple Conditions On Pandas Columns

I have a dataframe that contains Item Id numbers with multiple tasks and completion dates for those tasks. I am trying to assign categories based on task completions or in-completi

Solution 1:

Is there a different approach i should take?

Rafaelc offered the correct answer:

Change row['Task 1 Comp Date'].isnull() for pd.isnull(row['Task 1 Comp Date'])

This remedies the "Trouble With NaNs" diagnostic you reported:

AttributeError: ("'Timestamp' object has no attribute 'notnull'", 'occurred at index 8')

The current question that you asked has been answered. Your "use conditional & for another check" remark suggests that perhaps you would like to post a separate question.

Solution 2:

2 years after this question had been asked, I encountered a similar error. I solved it according to the solution of this question, by checking if it was pd.NaT instead of using isnull() or notnull()

Here is how to change the op's example.

def gating(row):
    if row['Task 1 Comp Date'] is pd.NaT:
        return "Pending Task 1"
    if row['Task 3 Comp Date'] is not pd.NaT:
        return "Complete"