We are starting a series of videos about a new member of the collection of Kotlin libraries for Data Science.

In this episode, a lead developer of Kotlin DataFrame, Anatoly Nikitin, goes through the main features and basic operations of the library

0:00 — Intro
1:50 — Creating Kotlin JuPyter notebook and reference Kotlin DataFrame library
2:36 — Reading a dataset from a CSV file
3:49 — Indexing and horizontal slicing
4:55 — Accessing columns
7:20 — Generation of extension properties
10:04 — Schema and nullability
14:03 — Describe
15:04 — Select columns
19:51 — Statistics operations
22:23 — filter/drop, sortBy
24:30 — update/convert
28:50 — add/remove, move, rename columns
32:12 — group/ungroup, flatten columns and columns' hierarchy
36:57 — Split columns
40:42 — explode/implode
42:57 — groupBy for rows, aggregation, and nested DataFrames
48:16 — Pivot
52:45 — Useful links

Documentation - [ Ссылка ]
Installation (Jupyter, Datalore, Gradle))[[ Ссылка ]
Repository - [ Ссылка ]

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