grouping by weekly break down of datetimes 64 python

Question

I have a pandas data frame with a column that represents dates as:

Name: ts_placed, Length: 13631, dtype: datetime64[ns]

It looks like this:

0    2014-10-18 16:53:00
1    2014-10-27 11:57:00
2    2014-10-27 11:57:00
3    2014-10-08 16:35:00
4    2014-10-24 16:36:00
5    2014-11-06 15:34:00
6    2014-11-11 10:30:00
....

I know how to group it in general using the function:

grouped = data.groupby('ts_placed')

What I want to do is to use the same function but to group the rows by week.

score 0 · Accepted Answer · answered Jun 26 '15 at 13:08

0

Pass

pd.DatetimeIndex(df.date).week

as the argument to groupby. This is the ordinal week in the year; see DatetimeIndex for other definitions of week.

answered Jun 26 '15 at 13:08

Ami Tavory

74,578
11
141
185

it works. just one more thing. the output is do you know how can I see it? sorry for the nooby question but I can't find it anyway. – Blue Moon Jun 26 '15 at 13:17
Oh, you need to refer to the [`groupby` docs](http://pandas.pydata.org/pandas-docs/stable/groupby.html). Groupby is just a step - you need to do something with the result, e.g., `df.groupby(...).mean()`. I really suggest you read the docs. – Ami Tavory Jun 26 '15 at 13:33
once I have grouped them how do I save them as separated datasets? – Blue Moon Jun 26 '15 at 13:59
You mean to separate files? That's a legitimate question, but I really think it's a separate one. It's not that easy to converse via these comments. – Ami Tavory Jun 26 '15 at 14:04
I'll ask one more question then. Thank you – Blue Moon Jun 26 '15 at 14:09

score 0 · Answer 2 · answered Jun 26 '15 at 14:06

0

you can also use Timergrouper

df.set_index(your_date).groupby(pd.TimeGrouper('W')).size()

answered Jun 26 '15 at 14:06

steboc

1,161
1
7
17

grouping by weekly break down of datetimes 64 python

2 Answers2