CODEWITHSUNDEEP
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Polly
Polly

Reputation: 1097

Python count Null and not Null values in Dataframe

I have a dataframe

Date  Name
1995  Harry
1995  John
1997  NaN
1995  NaN
1998  Nina
1998  NaN
1997  Carrie

I need to count a NaN/(not NaN) values for each Date. So the output should be

Date Nan/NaN+notNaN
1995 1/3
1997 1/2
1998 1/2

I was trying with df.groupby(['Date']).agg({'Name' : 'count'}) but can i do the same with df.groupby(['Date']).agg({'df.Name.isnull()' : 'count'}) or smth like that?

Upvotes: 1

Views: 2233

Answers (1)

Anton Protopopov
Anton Protopopov

Reputation: 31662

What about something like that:

In [52]: df.groupby('Date').agg({'Name': lambda x: x.isnull().sum(), 'Date': 'count'})
Out[52]:
      Name  Date
Date
1995     1     3
1997     1     2
1998     1     2

Or you could do following:

In [60]: df.groupby('Date').agg({'Name': lambda x: x.isnull().sum().astype(str) + '/' + str(x.size)})
Out[60]:
     Name
Date
1995  1/3
1997  1/2
1998  1/2

Or with format: 

In [62]: df.groupby('Date').agg({'Name': lambda x: '{}/{}'.format(x.isnull().sum(), len(x))})
Out[62]:
     Name
Date
1995  1/3
1997  1/2
1998  1/2

Upvotes: 3

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