Aggregating events. Reducing df size. In search of more elegant way

To solve this you need:

1. create while loop to go thru each datetime range
2. slice you df with new datetime range
3. get results from sliced df
4. calculate new out variable for while loop
5. collect df with results into list and then concat them

Here You go (some comments in code):

import pandas as pd
from io import StringIO
from dateutil.relativedelta import relativedelta


data = StringIO("""
Loc|Event|Start|End
A|aaa|2018-08-30 00:26:29|2018-08-30 00:26:59
A|aaa|2018-08-30 00:26:30|2018-08-30 00:26:47
A|aaa|2018-08-30 00:38:05|2018-08-30 00:39:09
A|aaa|2018-08-30 00:40:31|2018-08-30 00:40:41
A|aaa|2018-08-30 00:57:17|2018-08-30 00:57:28
A|aaa|2018-08-30 00:57:36|2018-08-30 00:58:07
A|aaa|2018-08-30 00:57:53|2018-08-30 00:59:23
A|aaa|2018-08-30 00:57:58|2018-08-30 00:58:11
A|aaa|2018-08-30 00:58:00|2018-08-30 00:58:08
A|aaa|2018-08-30 01:27:58|2018-08-30 01:28:58
""")

# load data into data frame
df = pd.read_csv(data, sep='|')

# convert string to datetime
df['Start'] = pd.to_datetime(df['Start'])
df['End'] = pd.to_datetime(df['End'])


def get_result(df_filtered):
    df2 = pd.DataFrame({'Loc':df_filtered['Loc'].unique(), 'Event':df_filtered['Event'].unique(), 'Start':df_filtered['Start'].min(), 'End':df_filtered['End'].max()})
    start_end = df_filtered['Start'].max()

    return df2, start_end


# get datetime group range
min_datetime = df['Start'].min()
max_datetime = min_datetime + relativedelta(minutes=6)
# define variables for while loop
end_end = df['Start'].max()
start_end = min_datetime

results_list = []
while end_end > start_end:
    # filter rows by dates
    df_filtered = df[(df['Start'] >= min_datetime) & (df['End'] < max_datetime)]
    # get result and new start datetime
    df2, start_end = get_result(df_filtered)
    # get new values for max and min datetime
    df_start = df[df['Start'] > start_end]
    min_datetime = df_start['Start'].min()
    max_datetime = min_datetime + relativedelta(minutes=6)
    # append df with results
    results_list.append(df2)


df = pd.concat(results_list)

Output:

  Loc Event               Start                 End
0   A   aaa 2018-08-30 00:26:29 2018-08-30 00:26:59
0   A   aaa 2018-08-30 00:38:05 2018-08-30 00:40:41
0   A   aaa 2018-08-30 00:57:17 2018-08-30 00:59:23
0   A   aaa 2018-08-30 01:27:58 2018-08-30 01:28:58