A high paced overview of many of the pandas core functionality. As one of the most popular libraries in all of programming, Pandas is an essential tool for learning data wrangling. Watch this video to get a good foundational understanding of what is possible.

Intro to Jupyter: [ Ссылка ]

Kaggle notebook made by a viewer! [ Ссылка ]
Download the dataset here: [ Ссылка ]

Timeline:
00:00 Intro
00:57 Importing Pandas
01:26 Data I/O
01:51 Reading From Files
03:03 Writing to Files
03:36 DataFrame Basics
04:57 DataFrame Summary
06:12 Subsetting Columns
07:19 Select dtypes
07:34 Select as Series vs DataFrame
07:58 .loc and .iloc
09:37 .loc Filter Expressions
10:50 .query
11:31 Summary Statistics
12:10 .agg
12:53 Sumarizing Categoricals
13:43 rank, shift, cumsum
14:44 Rolling methods
15:21 Clip
15:41 Groupby
16:44 New Columns
17:33 Sorting
18:30 Missing Data
19:33 Combining Data
19:55 concat
21:01 Merge DataFrames
21:52 Merge Suffixes
22:34 Bonus

Check out my other videos:
Data Pipelines: Polars vs PySpark vs Pandas: [ Ссылка ]
Polars for Data Science: [ Ссылка ]
Speed up Pandas Dataframes: [ Ссылка ]
Avoid These Pandas Mistakes: [ Ссылка ]

Links to my stuff:
* Youtube: [ Ссылка ]
* Discord: [ Ссылка ]
* Twitch: [ Ссылка ]_
* Twitter: [ Ссылка ]
* Kaggle: [ Ссылка ]

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