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NumPy manual contents¶

Setting up
- What is NumPy?
  - Why is NumPy Fast?
  - Who Else Uses NumPy?
- Installing NumPy
Quickstart tutorial
- Prerequisites
- The Basics
- Shape Manipulation
- Copies and Views
- Less Basic
  - Broadcasting rules
- Advanced indexing and index tricks
- Linear Algebra
  - Simple Array Operations
- Tricks and Tips
- Further reading
NumPy: the absolute basics for beginners
- Welcome to NumPy!
- Installing NumPy
- How to import NumPy
- Reading the example code
- What’s the difference between a Python list and a NumPy array?
- What is an array?
- More information about arrays
- How to create a basic array
- Adding, removing, and sorting elements
- How do you know the shape and size of an array?
- Can you reshape an array?
- How to convert a 1D array into a 2D array (how to add a new axis to an array)
- Indexing and slicing
- How to create an array from existing data
- Basic array operations
- Broadcasting
- More useful array operations
- Creating matrices
- Generating random numbers
- How to get unique items and counts
- Transposing and reshaping a matrix
- How to reverse an array
- Reshaping and flattening multidimensional arrays
- How to access the docstring for more information
- Working with mathematical formulas
- How to save and load NumPy objects
- Importing and exporting a CSV
- Plotting arrays with Matplotlib
NumPy Tutorials
- NumPy basics
- Miscellaneous
- NumPy for Matlab users
- Tutorial: Linear algebra on n-dimensional arrays
- Building from source
- Using NumPy C-API
NumPy How Tos
- How to read and write data using NumPy
NumPy Reference
- Array objects
- Constants
- Universal functions (ufunc)
- Routines
- Packaging (numpy.distutils)
- NumPy Distutils - Users Guide
- NumPy C-API
- NumPy internals
- NumPy and SWIG
  - numpy.i: a SWIG Interface File for NumPy
  - Testing the numpy.i Typemaps
- Acknowledgements
Explanations
- Broadcasting
  - General Broadcasting Rules
F2PY Users Guide and Reference Manual
- Three ways to wrap - getting started
- Signature file
- Using F2PY bindings in Python
- Using F2PY
  - Command f2py
  - Python module numpy.f2py
- Using via numpy.distutils
- Advanced F2PY usages
Glossary
Contributing to NumPy
- Development process - summary
- Development process - details
Under-the-hood Documentation for developers
NumPy’s Documentation
- A Guide to NumPy/SciPy Documentation
  - numpydoc docstring guide
- Example Source
- Example Rendered
- Building the NumPy API and reference docs
  - Instructions
  - Sphinx extensions
A Guide to NumPy/SciPy Documentation
- numpydoc docstring guide
Example Source
Example Rendered
NumPy benchmarks
- Usage
- Writing benchmarks
Reporting bugs
Release Notes
- NumPy 1.19.0 Release Notes
  - Highlights
  - Deprecations
  - Expired deprecations
  - Compatibility notes
  - C API changes
    - Better support for const dimensions in API functions
    - Const qualify UFunc inner loops
  - New Features
  - Improvements
    - Use 64-bit integer size on 64-bit platforms in fallback lapack_lite
  - Changes
- NumPy 1.19.0 Release Notes
- 1.18.2
  - Contributors
  - Pull requests merged
- 1.18.1
  - Contributors
  - Pull requests merged
- 1.18.0
  - Highlights
  - New functions
    - Multivariate hypergeometric distribution added to numpy.random
  - Deprecations
  - Expired deprecations
  - Compatibility notes
  - C API changes
    - PyDataType_ISUNSIZED(descr) now returns False for structured datatypes
  - New Features
  - Improvements
  - Changes
- 1.17.5
  - Contributors
  - Pull requests merged
- 1.17.4
  - Highlights
  - Contributors
  - Pull requests merged
- 1.17.3
  - Highlights
  - Compatibility notes
  - Contributors
  - Pull requests merged
- 1.17.2
  - Contributors
  - Pull requests merged
- 1.17.1
  - Contributors
  - Pull requests merged
- 1.17.0
  - Highlights
  - New functions
  - Deprecations
  - Future Changes
    - Shape-1 fields in dtypes won’t be collapsed to scalars in a future version
  - Compatibility notes
  - C API changes
    - dimension or stride input arguments are now passed by npy_intp const*
  - New Features
  - Improvements
  - Changes
- 1.16.6
  - Highlights
  - New functions
    - Allow matmul (@ operator) to work with object arrays.
  - Compatibility notes
    - Fix regression in matmul (@ operator) for boolean types
  - Improvements
    - Array comparison assertions include maximum differences
  - Contributors
  - Pull requests merged
- 1.16.5
  - Contributors
  - Pull requests merged
- 1.16.4
  - New deprecations
    - Writeable flag of C-API wrapped arrays
  - Compatibility notes
    - Potential changes to the random stream
  - Changes
    - numpy.lib.recfunctions.structured_to_unstructured does not squeeze single-field views
  - Contributors
  - Pull requests merged
- 1.16.3
  - Compatibility notes
    - Unpickling while loading requires explicit opt-in
  - Improvements
    - Covariance in random.mvnormal cast to double
  - Changes
    - __array_interface__ offset now works as documented
- 1.16.2
  - Compatibility notes
    - Signed zero when using divmod
  - Contributors
  - Pull requests merged
- 1.16.1
  - Contributors
  - Enhancements
  - Compatibility notes
  - New Features
    - divmod operation is now supported for two timedelta64 operands
  - Improvements
    - Further improvements to ctypes support in np.ctypeslib
    - Array comparison assertions include maximum differences
  - Changes
    - timedelta64 % 0 behavior adjusted to return NaT
- 1.16.0
  - Highlights
  - New functions
  - New deprecations
  - Expired deprecations
  - Future changes
  - Compatibility notes
  - C API changes
  - New Features
  - Improvements
  - Changes
- 1.15.4
  - Compatibility Note
  - Contributors
  - Pull requests merged
- 1.15.3
  - Compatibility Note
  - Contributors
  - Pull requests merged
- 1.15.2
  - Compatibility Note
  - Contributors
  - Pull requests merged
- 1.15.1
  - Compatibility Note
  - Contributors
  - Pull requests merged
- 1.15.0
  - Highlights
  - New functions
  - Deprecations
  - Future Changes
  - Compatibility notes
  - C API changes
    - New functions npy_get_floatstatus_barrier and npy_clear_floatstatus_barrier
    - Changes to PyArray_GetDTypeTransferFunction
  - New Features
  - Improvements
- 1.14.6
  - Contributors
  - Pull requests merged
- 1.14.5
  - Contributors
  - Pull requests merged
- 1.14.4
  - Contributors
  - Pull requests merged
- 1.14.3
  - Contributors
  - Pull requests merged
- 1.14.2
  - Contributors
  - Pull requests merged
- 1.14.1
  - Contributors
  - Pull requests merged
- 1.14.0
  - Highlights
  - New functions
  - Deprecations
  - Future Changes
  - Compatibility notes
  - C API changes
    - PyPy compatible alternative to UPDATEIFCOPY arrays
  - New Features
  - Improvements
  - Changes
- 1.13.3
  - Contributors
  - Pull requests merged
- 1.13.2
  - Contributors
  - Pull requests merged
- 1.13.1
  - Pull requests merged
  - Contributors
- 1.13.0
  - Highlights
  - New functions
  - Deprecations
  - Future Changes
  - Build System Changes
  - Compatibility notes
  - C API changes
    - GUfuncs on empty arrays and NpyIter axis removal
    - PyArray_MapIterArrayCopyIfOverlap added to NumPy C-API
  - New Features
  - Improvements
  - Changes
- 1.12.1
  - Bugs Fixed
- 1.12.0
  - Highlights
  - Dropped Support
  - Added Support
  - Build System Changes
  - Deprecations
  - Future Changes
    - Multiple-field manipulation of structured arrays
  - Compatibility notes
  - New Features
  - Improvements
  - Changes
- 1.11.3
  - Contributors to maintenance/1.11.3
  - Pull Requests Merged
- 1.11.2
  - Pull Requests Merged
- 1.11.1
  - Fixes Merged
- 1.11.0
  - Highlights
  - Build System Changes
  - Future Changes
  - Compatibility notes
  - New Features
  - Improvements
  - Changes
  - Deprecations
  - FutureWarnings
    - Assigning to slices/views of MaskedArray
- 1.10.4
  - Compatibility notes
  - Issues Fixed
  - Merged PRs
- 1.10.3
- 1.10.2
  - Compatibility notes
  - Issues Fixed
  - Merged PRs
  - Notes
- 1.10.1
- 1.10.0
  - Highlights
  - Dropped Support
  - Future Changes
  - Compatibility notes
  - New Features
  - Improvements
  - Changes
  - Deprecations
- 1.9.2
  - Issues fixed
- 1.9.1
  - Issues fixed
- 1.9.0
  - Highlights
  - Dropped Support
  - Future Changes
  - Compatibility notes
  - New Features
  - Improvements
  - Deprecations
- 1.8.2
  - Issues fixed
- 1.8.1
  - Issues fixed
  - Changes
    - NDIter
    - Optional reduced verbosity for np.distutils
  - Deprecations
    - C-API
- 1.8.0
  - Highlights
  - Dropped Support
  - Future Changes
  - Compatibility notes
  - New Features
  - Improvements
  - Changes
  - Deprecations
    - General
  - Authors
- 1.7.2
  - Issues fixed
- 1.7.1
  - Issues fixed
- 1.7.0
  - Highlights
  - Compatibility notes
  - New features
  - Changes
    - General
    - Casting Rules
  - Deprecations
    - General
    - C-API
- 1.6.2
  - Issues fixed
  - Changes
    - numpy.f2py
    - numpy.poly
- 1.6.1
  - Issues Fixed
- 1.6.0
  - Highlights
  - New features
  - Changes
  - Deprecated features
  - Removed features
- 1.5.0
  - Highlights
    - Python 3 compatibility
    - PEP 3118 compatibility
  - New features
  - Changes
- 1.4.0
  - Highlights
  - New features
  - Improvements
  - Deprecations
  - Internal changes
- 1.3.0
  - Highlights
  - New features
  - Deprecated features
    - Histogram
  - Documentation changes
  - New C API
  - Internal changes
About NumPy
- NumPy community
About this documentation
- Conventions
NumPy License