Search Results - computer program based data processing.

Search alternatives:

  1. 421
    Published 2019
    Subjects: ...Data mining Computer programs....
    Connect to this streaming video
    Video
  2. 422
    Published 2022
    Connect to the full text of this electronic book
    eBook
  3. 423
    Get full text
    Government Document eBook
  4. 424
    Published 2020
    Serial
  5. 425
  6. 426
  7. 427
  8. 428
  9. 429
    by Nguyen, Quan
    Published 2022
    Connect to the full text of this electronic book
    eBook
  10. 430
  11. 431
  12. 432
  13. 433
    Published 2005
    Get full text
    Government Document eBook
  14. 434
    by Sun, Qiming
    Published 2025
    Table of Contents: ...1.5.3 Magics -- 1.5.4 Remote execution -- Summary -- References -- 2 Data processing -- 2.1 Vectorized data processing with NumPy -- 2.1.1 The basics of NumPy -- 2.1.2 Universal functions (ufunc) -- 2.1.3 Inplace operations -- 2.1.4 Broadcasting -- 2.1.5 Fancy indexing -- 2.1.6 Mask array -- Indexing a dense array -- Indexing a sparse array -- Randomly distributed mask array -- Indexing a high-dimensional array -- 2.1.7 Data structure of NumPy ndarray -- 2.1.7.1 The strides attribute for flexible array structure -- 2.1.7.2 C-contiguous and F-contiguous storage -- 2.1.8 Array views -- Slicing an array -- NumPy functions that return a view of the input array -- Calling np.ndarray() with the keyword argument buffer -- 2.1.9 The reshape function -- 2.2 Data types in NumPy -- 2.2.1 Type casting -- 2.2.2 Scalar type and zero-dimensional array -- 2.2.3 Infinity ( inf ) and not-a-number ( nan ) -- 2.2.4 Data with high precision -- 2.2.5 Structured array -- 2.3 Data with labels: Pandas -- 2.3.1 Pandas data objects -- 2.3.1.1 Series -- 2.3.1.2 DataFrame -- 2.3.2 Broadcasting -- 2.3.3 Indexing -- 2.3.3.1 Location-based indexing -- 2.3.3.2 Label-based indexing -- 2.3.3.3 Attribute-based indexing -- 2.3.3.4 Indexing elements in DataFrame -- 2.3.4 query and eval methods -- 2.3.5 Altering structure of DataFrame -- 2.3.5.1 Changing axes labels -- 2.3.5.2 Inserting or removing rows and columns -- 2.3.5.3 Reorganizing rows and columns -- 2.3.6 Data types -- 2.3.7 Missing data -- 2.3.8 Grouping and aggregation -- 2.3.9 View and copy -- Summary -- References -- 3 Visualization -- 3.1 Matplotlib -- 3.2 Pandas visualization -- 3.3 Mayavi for 3D plotting -- 3.4 Quantum chemistry visualization -- 3.4.1 Jinja template -- Expression -- Control statements -- Whitespace control -- 3.4.2 Molden format -- 3.4.3 Cube format -- Summary -- References -- 4 Scientific computing tools....
    Connect to the full text of this electronic book
    eBook
  15. 435
    by Sun, Qiming
    Published 2025
    Table of Contents: ...1.5.3 Magics -- 1.5.4 Remote execution -- Summary -- References -- 2 Data processing -- 2.1 Vectorized data processing with NumPy -- 2.1.1 The basics of NumPy -- 2.1.2 Universal functions (ufunc) -- 2.1.3 Inplace operations -- 2.1.4 Broadcasting -- 2.1.5 Fancy indexing -- 2.1.6 Mask array -- Indexing a dense array -- Indexing a sparse array -- Randomly distributed mask array -- Indexing a high-dimensional array -- 2.1.7 Data structure of NumPy ndarray -- 2.1.7.1 The strides attribute for flexible array structure -- 2.1.7.2 C-contiguous and F-contiguous storage -- 2.1.8 Array views -- Slicing an array -- NumPy functions that return a view of the input array -- Calling np.ndarray() with the keyword argument buffer -- 2.1.9 The reshape function -- 2.2 Data types in NumPy -- 2.2.1 Type casting -- 2.2.2 Scalar type and zero-dimensional array -- 2.2.3 Infinity ( inf ) and not-a-number ( nan ) -- 2.2.4 Data with high precision -- 2.2.5 Structured array -- 2.3 Data with labels: Pandas -- 2.3.1 Pandas data objects -- 2.3.1.1 Series -- 2.3.1.2 DataFrame -- 2.3.2 Broadcasting -- 2.3.3 Indexing -- 2.3.3.1 Location-based indexing -- 2.3.3.2 Label-based indexing -- 2.3.3.3 Attribute-based indexing -- 2.3.3.4 Indexing elements in DataFrame -- 2.3.4 query and eval methods -- 2.3.5 Altering structure of DataFrame -- 2.3.5.1 Changing axes labels -- 2.3.5.2 Inserting or removing rows and columns -- 2.3.5.3 Reorganizing rows and columns -- 2.3.6 Data types -- 2.3.7 Missing data -- 2.3.8 Grouping and aggregation -- 2.3.9 View and copy -- Summary -- References -- 3 Visualization -- 3.1 Matplotlib -- 3.2 Pandas visualization -- 3.3 Mayavi for 3D plotting -- 3.4 Quantum chemistry visualization -- 3.4.1 Jinja template -- Expression -- Control statements -- Whitespace control -- 3.4.2 Molden format -- 3.4.3 Cube format -- Summary -- References -- 4 Scientific computing tools....
    Connect to the full text of this electronic book
    eBook
  16. 436
  17. 437
  18. 438
  19. 439
  20. 440