Quickstart
What is an Awkward Array?
Converting arrays
NumPy
Python objects
JSON
ROOT via Uproot
Arrow and Parquet
Pandas
Generic buffers
Creating new arrays
ArrayBuilder (easy & general)
LayoutBuilder (medium) [todo]
Direct constructors (faster) [todo]
Unflattening and grouping [todo]
Arrays of records [todo]
Arrays of strings [todo]
Arrays of categories [todo]
Lazy arrays [todo]
Partitioned arrays [todo]
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 [todo]
Padding/clipping for machine learning [todo]
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
.md
.pdf
repository
open issue
suggest edit
Filtering data
ΒΆ
By number of items
Cuts vs. masks
Slicing lists within arrays
Slices with missing values
How to use Awkward Arrays on GPUs
How to filter arrays by number of items
