11.1.7. 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.

• 11.1.7.1. The numpy.ma module
  • 11.1.7.1.1. Rationale
  • 11.1.7.1.2. What is a masked array?
  • 11.1.7.1.3. The numpy.ma module
• 11.1.7.2. Using numpy.ma
  • 11.1.7.2.1. Constructing masked arrays
  • 11.1.7.2.2. Accessing the data
  • 11.1.7.2.3. Accessing the mask
  • 11.1.7.2.4. Accessing only the valid entries
  • 11.1.7.2.5. Modifying the mask
  • 11.1.7.2.6. Indexing and slicing
  • 11.1.7.2.7. Operations on masked arrays
• 11.1.7.3. Examples
  • 11.1.7.3.1. Data with a given value representing missing data
  • 11.1.7.3.2. Filling in the missing data
  • 11.1.7.3.3. Numerical operations
  • 11.1.7.3.4. Ignoring extreme values
• 11.1.7.4. Constants of the numpy.ma module
• 11.1.7.5. The MaskedArray class
  • 11.1.7.5.1. Attributes and properties of masked arrays
• 11.1.7.6. MaskedArray methods
  • 11.1.7.6.1. Conversion
  • 11.1.7.6.2. Shape manipulation
  • 11.1.7.6.3. Item selection and manipulation
  • 11.1.7.6.4. Pickling and copy
  • 11.1.7.6.5. Calculations
  • 11.1.7.6.6. Arithmetic and comparison operations
  • 11.1.7.6.7. Representation
  • 11.1.7.6.8. Special methods
  • 11.1.7.6.9. Specific methods
• 11.1.7.7. Masked array operations
  • 11.1.7.7.1. Constants
  • 11.1.7.7.2. Creation
  • 11.1.7.7.3. Inspecting the array
  • 11.1.7.7.4. Manipulating a MaskedArray
  • 11.1.7.7.5. Operations on masks
  • 11.1.7.7.6. Conversion operations
  • 11.1.7.7.7. Masked arrays arithmetics