#36 Pandas: Categorical data: operators, missing values, StringIO in Python - 22 | Tutorial
The video discusses categories with operators, missing values and StringIO in Python
Timeline
(Python 3.7)
00:00 - Welcome
00:09 - Outline of video
00:32 - Open Jupyter notebook
00:39 - Data
00:55 - Operators: Series category: values_counts()
01:53 - Create DataFrame using category
02:36 - Check DataFrame: dtypes
03:05 - Operators: DataFrame category: mean() using groupby()
04:40 - Operators: DataFrame category and object: mean() using groupby()
05:45 - DataFrame category and object: .pivot_table()
07:05 - Missing categories: Series
07:35 - Missing categories: Series: .value_counts()
08:05 - Missing categories: Series: .codes()
08:53 - Missing categories: Series: .isna()
09:27 - Missing categories: Series: .fillna()
10:00 - Input/Output categorical data
11:21 - Input/Output categorical data: .set_categories()
12:18 - Input/Output categorical data: import io
12:24 - Input/Output categorical data: create a virtual file: io.StringIO()
12:49 - Input/Output categorical data: .to_csv()
13:11 - Input/Output categorical data: .read_csv()
14:10 - Input/Output categorical data: convert object to category
14:30 - Input/Output categorical data: .set_categories()
15:28 - Ending notes
