RAPIDS cuDF release 0.19 introduces improved support for nested types such as lists and structs. This means that you can now leverage the GPU to perform operations on even more complex data while using familiar Pandas-like syntax.

>>> import cudf
>>> cudf.Series([[1, 2, 3], [4, 5], [6, 7]])
>>> s
Out[9]:
0 [1, 2, 3]
1 [4, 5]
2 [6, 7]
dtype: list
>>> s.dtype
ListDtype(int64) # a new dtype!

This blog post will cover everything you need to know about nested types in cuDF: what they are, how they work, and how they can be used.

Motivation

Ashwin Srinath

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