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Quickstart
What is an Awkward Array?
Converting arrays
NumPy
Python objects
JSON
ROOT via Uproot
Arrow and Parquet
Pandas
Generic buffers
Creating new arrays
Arrays of lists
Arrays of records
Arrays of missing data
Arrays of strings
Lazy arrays [todo]
Unflattening and grouping [todo]
ArrayBuilder (easy & general)
LayoutBuilder (more control)
Direct constructors (fastest)
Examining arrays
Data type [todo]
Single item detail [todo]
Listing fields/keys/columns [todo]
Simple slicing [todo]
Checking validity [todo]
Numerical math
NumPy functions [todo]
Awkward broadcasting [todo]
Reducing (sum/min/any/all) [todo]
Statistics (mean/var/std) [todo]
Using argmin/argmax [todo]
On GPUs [todo]
Filtering data
By number of items [todo]
Cuts vs. masks [todo]
Slicing lists within arrays [todo]
Slices with missing values [todo]
Restructuring data
Zip/unzip and project [todo]
Adding fields to records [todo]
Renaming records [todo]
Flattening for plots
Padding/clipping for machine learning
Concatenating and interleaving [todo]
Sorting [todo]
Combinatorics
Cartesian and "n choose k" [todo]
Best match between collections [todo]
Using arrays in Numba
Supported features [todo]
Building array output [todo]
Specialized behavior
Subclassing Array/Record [todo]
Overriding NumPy functions [todo]
In Numba [todo]
For physics: Lorentz vectors [todo]
Differentiation using JAX
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Combinatorics
Combinatorics
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Cartesian product and “n choose k”
Best match between collections
