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NumPy v2.5.dev0 Manual - Home NumPy v2.5.dev0 Manual - Home
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章节导航

  • NumPy’s module structure
  • 陣列物件
    • N 維陣列(ndarray)
    • Scalars
    • Data type objects (dtype)
    • Data type promotion in NumPy
    • Iterating over arrays
    • Standard array subclasses
    • Masked arrays
      • The numpy.ma module
      • Constants of the numpy.ma module
      • Masked array operations
    • The array interface protocol
    • Datetimes and timedeltas
  • Universal functions (ufunc)
  • Routines and objects by topic
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  • NumPy and SWIG
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  • 陣列物件
  • Masked arrays

Masked arrays#

Masked arrays are arrays that may have missing or invalid entries. The numpy.ma module provides a nearly work-alike replacement for numpy that supports data arrays with masks.

  • The numpy.ma module
    • Rationale
    • What is a masked array?
    • The numpy.ma module
  • Using numpy.ma
    • Constructing masked arrays
    • Accessing the data
    • Accessing the mask
    • Accessing only the valid entries
    • Modifying the mask
    • 索引與切片
    • Operations on masked arrays
  • Examples
    • Data with a given value representing missing data
    • Filling in the missing data
    • Numerical operations
    • Ignoring extreme values
  • Constants of the numpy.ma module
    • masked
    • nomask
    • masked_print_option
  • The MaskedArray class
    • MaskedArray
    • Attributes and properties of masked arrays
  • MaskedArray methods
    • Conversion
    • Shape manipulation
    • Item selection and manipulation
    • Pickling and copy
    • Calculations
    • Arithmetic and comparison operations
    • Representation
    • Special methods
    • Specific methods
  • Masked array operations
    • Constants
    • Creation
    • Inspecting the array
    • Manipulating a MaskedArray
    • Operations on masks
    • Conversion operations
    • Masked arrays arithmetic

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The numpy.ma module

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