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Contributor guide
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10 minutes to Awkward Array
Converting arrays
NumPy
Python objects
JSON
Arrow and Parquet
Pandas
Generic buffers
ROOT via RDataFrame
Creating new arrays
Arrays of lists
Arrays of records
Arrays of missing data
Arrays of strings
Unflattening and grouping [todo]
ArrayBuilder (easy & general)
Direct constructors (fastest)
Examining arrays
Data type [todo]
Single item detail [todo]
Listing fields/keys/columns
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
Slices with missing values [todo]
Restructuring data
Zip/unzip and project
Adding fields to records
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
Building Awkward Arrays in C++
Using arrays in Numba
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Supported features [todo]
Building array output [todo]
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