Filter Dataframe By Multiple Date Ranges

Given a dataframe with observations how can rows be returned which are within +-X days of a given list of dates? I came up with the following function, but is there a simpler more

Solution 1:

From your DataFrame :

>>> import pandas as pd
>>> from io import StringIO

>>> df = pd.read_csv(StringIO("""
date,event
2012-01-01 12:30:00,event1
2012-01-01 12:30:12,event2
2012-01-01 12:30:12,event3
2012-01-02 12:28:29,event4
2012-02-01 12:30:29,event4
2012-02-01 12:30:38,event5
2012-03-01 12:31:05,event6
2012-03-01 12:31:38,event7
2012-06-01 12:31:44,event8
2012-07-01 10:31:48,event9
2012-07-01 11:32:23,event10"""))
>>> df['date'] = pd.to_datetime(df['date'], format="%Y-%m-%d %H:%M:%S.%f")
>>> df
    date                event
02012-01-01 12:30:00 event1
12012-01-01 12:30:12 event2
22012-01-01 12:30:12 event3
32012-01-02 12:28:29 event4
42012-02-01 12:30:29 event4
52012-02-01 12:30:38 event5
62012-03-01 12:31:05 event6
72012-03-01 12:31:38 event7
82012-06-01 12:31:44 event8
92012-07-01 10:31:48 event9
102012-07-01 11:32:23 event10

First, we start by shifting the date column and substract it to the original date column :

>>> g = df['date'].sub(df['date'].shift(1)).dt.days
>>> g
0      NaN
10.020.030.0430.050.0629.070.0892.0929.0100.0
Name: date, dtype: float64

Then, we apply a cumsum for all values greater than X (here it is 1 day) to get the expect result :

>>> X = 1>>> df.groupby(g.gt(X).cumsum()).apply(print)
                 date   event
02012-01-01 12:30:00  event1
12012-01-01 12:30:12  event2
22012-01-01 12:30:12  event3
32012-01-02 12:28:29  event4
                 date   event
42012-02-01 12:30:29  event4
52012-02-01 12:30:38  event5
                 date   event
62012-03-01 12:31:05  event6
72012-03-01 12:31:38  event7
                 date   event
82012-06-01 12:31:44  event8
                 date   event
92012-07-01 10:31:48  event9
102012-07-01 11:32:23 event10