Python 比较列中的日期时间和 NaT

Question

I have a date frame like that has a submit and resolved date

  Incident ID   Submit_Date  Resolved_Date 
   INC001.       2021-02-25  2021-03-02     
   INC002        2021-02-27  2021-03-01    
   INC003        2021-02-27  NaT          
   INC004        2021-04-01  NaT  

I have a function to count the tickets if they meet a certain criteria but with the NaT's it won't read them with the comparison

part of the function I am having problems is like this The function it is looking if the rows resolved date is empty and the other tickets resolved date is empty then summing it for a count in a new column

 result = list()
  for row in df.iterrows():
     cur_data = row[1]
     result.append(((cur_data['Resolved_Date'] is pd.NaT) & (df['Resolved_Date'] is pd.NaT))).sum())

 df['Count'] = result  

I want the result to look like this

  Incident ID Submit_Date  Resolved_Date  Count
   INC001        2021-02-25  2021-03-02     0
   INC002        2021-02-27  2021-03-01     0
   INC003        2021-02-27  NaT            2 # counting itself and the other NA resolved date
   INC004        2021-04-01  NaT            2 # counting itself and the other NA resolved date

Right now it is ignoring the NaTs

Answer 1

If you are looking to get total count of NaT in Resolved_Date column and put it in a new column against NaT values of Resolved_Date then this should work.

Code

NaT_check = df['Resolved_Date'].isna()
df['Count'] = np.where(NaT_check, NaT_check.sum(),0)
df

Output

    Incident ID Submit_Date Resolved_Date   Count
0   INC001  2021-02-25  2021-03-02          0
1   INC002  2021-02-27  2021-03-01          0
2   INC003  2021-02-27  NaT                 2
3   INC004  2021-04-01  NaT                 2