def add_issue_state(df_tr):

df_status = df_tr.copy(deep=True)  
st_len = df_status.shape[0]
idx = 1
    
while idx<=st_len:
    
    if idx==1:
        prev_issue = False
    else:
        prev_issue = df_status['{}_Issue'.format(tr_col)][idx-2]
        
    flag_critical = np.logical_or(prev_issue, df_status['{}_critical'.format(tr_col)][idx-1])
    issue = np.subtract(flag_critical, df_status['{}_healthy'.format(tr_col)][idx-1], dtype=np.int) > 0
    df_status['{}_Issue'.format(tr_col)].iat[idx-1] = issue      
    idx += 1

return df_status

How to build this with pyspark??

I tried using F.lag function.