#65 Pandas (Part 42): GroupBy - 3: Aggregate in Python | Tutorial
The video discusses GroupBy with Aggregate in Pandas in Python.
Timeline
(Python 3.7)
00:00 - Welcome
00:12 - Outline of video
01:13 - Open Jupyter notebook
01:21 - Data
01:48 - GroupBy: Create a GroupBy object: using one column
02:21 - GroupBy: get sum: .sum()
03:04 - GroupBy: Aggregate: .aggregate().sum()
03:30 - GroupBy: Aggregate: .agg().sum()
04:13 - GroupBy: Create GroupBy object: using two columns
04:27 - GroupBy: Aggregate: .agg().sum()
05:28 - GroupBy: Aggregate: Avoid converting column to Index: as_index=False
06:39 - GroupBy: Aggregate: Avoid converting column to Index: .reset_index()
07:40 - GroupBy: Create GroupBy object: using two columns
07:55 - GroupBy: Get size of groups: .size()
08:28 - GroupBy: Get statistics: .describe()
09:52 - GroupBy: Create a GroupBy object
10:07 - GroupBy: Aggregate Multiple Functions: One column
11:20 - GroupBy: Aggregate Multiple Functions: Multiple column
12:22 - GroupBy: Aggregate: Rename one column: using .rename()
14:14 - GroupBy: Aggregate: Rename multiple columns: using .rename()
14:53 - GroupBy: Aggregate: Rename column: One column: using pd.NamedAgg
16:40 - GroupBy: Aggregate: Rename column: Multiple column: using pd.NamedAgg
17:55 - GroupBy: Aggregate: Rename column: Multiple column: using strings
18:50 - GroupBy: Aggregate: Rename column: One column: using pd.NamedAgg and .agg(**{})
20:45 - GroupBy: Aggregate: One column in DataFrame
22:34 - GroupBy: Create a GroupBy object
22:48 - GroupBy: Aggregate: using different functions to each column in the same DataFrame
24:02 - Ending notes