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NumPy v2.6.dev0 Manual - Home NumPy v2.6.dev0 Manual - Home
  • பயனர் வழிகாட்டி
  • API குறிப்புகள்
  • மூலத்திலிருந்து உருவாக்குவது
  • மேம்படுத்தல்
  • Release notes
  • Learn
  • NEPs
  • GitHub
  • பயனர் வழிகாட்டி
  • API குறிப்புகள்
  • மூலத்திலிருந்து உருவாக்குவது
  • மேம்படுத்தல்
  • Release notes
  • Learn
  • NEPs
  • GitHub

Section Navigation

  • NumPy's module structure
  • Array objects
  • Universal functions (ufunc)
  • Routines and objects by topic
    • Constants
    • Array creation routines
    • Array manipulation routines
    • Bit-wise operations
    • String functionality
    • Datetime support functions
    • Data type routines
    • Mathematical functions with automatic domain
    • Floating point error handling
    • Exceptions and Warnings
    • Discrete Fourier Transform
    • Functional programming
    • Input and output
    • Indexing routines
    • Linear algebra
    • Logic functions
    • Masked array operations
    • Mathematical functions
    • Miscellaneous routines
    • Polynomials
    • Random sampling
    • Set routines
    • Sorting, searching, and counting
    • Statistics
    • Test support
    • Window functions
  • Typing (numpy.typing)
  • NumPy C-API
  • Array API standard compatibility
  • CPU/SIMD optimizations
  • Thread Safety
  • Global Configuration Options
  • NumPy security
  • Testing guidelines
  • Status of numpy.distutils and migration advice
  • NumPy and SWIG
  • NumPy reference
  • Routines and objects by topic

Routines and objects by topic#

In this chapter, routine docstrings are presented, grouped by functionality. Many docstrings contain example code, which demonstrates basic usage of the routine.

A convenient way to execute examples is the %doctest_mode mode of IPython, which allows for pasting of multi-line examples and preserves indentation.

  • Constants
  • Array creation routines
  • Array manipulation routines
  • Bit-wise operations
  • String functionality
  • Datetime support functions
  • Data type routines
  • Mathematical functions with automatic domain
  • Floating point error handling
  • Exceptions and Warnings
  • Discrete Fourier Transform
  • Functional programming
  • Input and output
  • Indexing routines
  • Linear algebra
  • Logic functions
  • Masked array operations
  • Mathematical functions
  • Miscellaneous routines
  • Polynomials
  • Random sampling
  • Set routines
  • Sorting, searching, and counting
  • Statistics
  • Test support
  • Window functions

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numpy.ufunc.signature

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Constants

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