Скачать или смотреть #83 Pandas (Part 60): Time: Slice, Exact match, time index resolution, pd.Truncate()

The video discusses slicing, exact match, index resolution and truncate for a time series using Pandas in Python.

Timeline
(Python 3.7)
[Background sound: It was raining at the time of recording!]

00:00 - Welcome
00:11 - Outline of video
00:50 - Open Jupyter notebook
01:15 - Create a Series with time index
02:40 - Time resolution of an index: 'minute'
03:20 - Partial index: ['year-month-day hour']
03:49 - Exact match: ['year-month-day hour:minute:second']
05:01 - Create a DataFrame with time index
05:55 - Slice a DataFrame: Partial index: ['year-month', :]
06:53 - Change datetime index of a DataFrame
07:26 - Time resolution of an index: 'day'
08:32 - Create a DatetimeIndex with millisecond re
10:02 - Time resolution of an index: 'millisecond'
10:26 - Slice a DataFrame: Partial index: ['year-month-day hour:minute:second':'year-month-day hour:minute:second', :]
11:08 - DataFrame: Exact match: [datetime.datetime(year, month, day, hour,minute,second):datetime.datetime(year, month, day, hour,minute,second),:]
12:53 - Create a DataFrame with DatetimeIndex
14:17 - Truncate a DataFrame: df.truncate(): 'year-month'
15:43 - Slice a DataFrame: 'year-month'
17:12 - Truncate a Series: df.truncate(): 'year-month'
17:40 - Slice a Series: 'year-month'
19:00 - Ending notes