How can I Group By Month from a Date field using Python/Pandas

Question

I have a Data-frame df which is as follows:

| date      | Revenue |
|-----------|---------|
| 6/2/2017  | 100     |
| 5/23/2017 | 200     |
| 5/20/2017 | 300             


        

Answer 1

Try this:

1. Chaged the date column into datetime formate.

   ---> df['Date'] = pd.to_datetime(df['Date'])

2. Insert new row in data frame which have month like->[May, 'June']

   ---> df['months'] = df['date'].apply(lambda x:x.strftime('%B'))

   ---> here x is date which take from date column in data frame.

3. Now aggregate aggregate data on month column and sum the revenue.

   --->response_data_frame = df.groupby('months')['Revenue'].sum()

   ---->print(response_data_frame)

output -:

| month | Revenue |

|-------|---------|

| May   | 500     |

| June  | 1000    |