How can I group by month from a date field using Python and Pandas?

I have a dataframe, df, which is as follows:

| date      | Revenue |
|-----------|---------|
| 6/2/2017  | 100     |
| 5/23/2017 | 200     |
| 5/20/2017 | 300     |
| 6/22/2017 | 400     |
| 6/21/2017 | 500     |

I need to group the above data by month to get output as:

| date | SUM(Revenue) |
|------|--------------|
| May  | 500          |
| June | 1000         |

I tried this code, but it did not work:

df.groupby(month('date')).agg({'Revenue': 'sum'})

I want to only use Pandas or NumPy and no additional libraries.

Solution

Try this:

In [6]: df['date'] = pd.to_datetime(df['date'])

In [7]: df
Out[7]:
        date  Revenue
0 2017-06-02      100
1 2017-05-23      200
2 2017-05-20      300
3 2017-06-22      400
4 2017-06-21      500



In [59]: df.groupby(df['date'].dt.strftime('%B'))['Revenue'].sum().sort_values()
Out[59]:
date
May      500
June    1000