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
  • Indexing and slicing
  • 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
• The MaskedArray class
  • 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 arithmetics

numpy.broadcast.reset The numpy.ma module