```def drag_mis(data):
list = []
for val in data.values:
if np.any(val) == None:
list.append(val)
return list.count(val)```
""" Need a summary report like a file attached in xls format need to automate this boring stuff"""
**
Функция «Выше» поможет нам перетащить значения нан, чтобы получить количество
**
df.groupby(["Operator","Model"],axis=0)[['Jan-17', 'Feb-17', 'Mar-17', 'Apr-17', 'May-17',
'Jun-17', 'Jul-17', 'Aug-17', 'Sep-17', 'Oct-17', 'Nov-17', 'Dec-17',
'Jan-18', 'Feb-18', 'Mar-18', 'Apr-18', 'May-18', 'Jun-18', 'Jul-18',
'Aug-18', 'Sep-18', 'Oct-18', 'Nov-18', 'Dec-18', 'Jan-19', 'Feb-19',
'Mar-19', 'Apr-19', 'May-19', 'Jun-19', 'Jul-19', 'Aug-19', 'Sep-19',
'Oct-19', 'Nov-19', 'Dec-19', 'Jan-20', 'Feb-20', 'Mar-20', 'Apr-20',
'May-20']].apply(drag_mis)
####I want to drag all nan values so that i can make count for summary report in new CSV file
#### The output is as follows:
AAL 737 0
757 0
767 0
777 0
787 0
MD80 0
AAR 747 0
767 0
777 0
ABM 747 0
ACN 737 0
######Please add your ideas,any one,where my function going wrong#######
********tried below code but i need a summary like value_counts,which can not be implemented in dataframe[![enter image description here][1]][1]********
**
df.groupby(["Operator","Model"])[['Jan-17', 'Feb-17', 'Mar-17', 'Apr-17', 'May-17', 'Jun-17', 'Jul-17', 'Aug-17', 'Sep-17', 'Oct-17', 'Nov-17', 'Dec-17', 'Jan-18', 'Feb-18', 'Mar-18', 'Apr-18', 'May-18', 'Jun-18', 'Jul-18', 'Aug-18', 'Sep-18', 'Oct-18', 'Nov-18', 'Dec-18', 'Jan-19', 'Feb-19', 'Mar-19', 'Apr-19', 'May-19', 'Jun-19', 'Jul-19', 'Aug-19', 'Sep-19', 'Oct-19', 'Nov-19', 'Dec-19', 'Jan-20', 'Feb-20', 'Mar-20', 'Apr-20', 'May-20']].apply(lambda x: x.isnull().sum())
**
****** Пожалуйста, посмотрите на этот снимок файла xls `
<[1]: <a href="https://i.stack.imgur.com/E1FTN.jpg" rel="nofollow noreferrer">https://i.stack.imgur.com/E1FTN.jpg> сильный текст