How to make a group by in Pandas?

I have a DataFrame of this kind:

Id|  Sex | ....
------------------
1 |male  |....
2 |female|....
3 |female|....
4 |male  |....
5 |male  |....

As a result, I want to get something like

Sex   | count
--------------
male  | 3
female| 2

Tried :

df.groupby(['sex']).agg(['mean', 'count'])

But it seems that this is not the case

Author: MaxU, 2018-05-07
Source

1 answers

Source DataFrame:

In [10]: df
Out[10]:
   Id     Sex
0   1    male
1   2  female
2   3  female
3   4    male
4   5    male

Number of occurrences for each value:

In [13]: df['Sex'].value_counts()
Out[13]:
male      3
female    2
Name: Sex, dtype: int64

The same thing in the form of DF using df.groupby().size():

In [11]: df.groupby(['Sex']).size().reset_index(name='count')
Out[11]:
      Sex  count
0  female      2
1    male      3

Grouping and calling multiple aggregating functions:

In [12]: df.groupby(['Sex'])['Id'].agg(['mean', 'count'])
Out[12]:
            mean  count
Sex
female  2.500000      2
male    3.333333      3

Your option is to return a DataFrame with "two-level" column names:

In [14]: df.groupby(['Sex']).agg(['mean', 'count'])
Out[14]:
              Id
            mean count
Sex
female  2.500000     2
male    3.333333     3
 1
Author: MaxU, 2018-05-07 12:15:00