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Getting into NumPy Basics
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Getting into NumPy Basics

Getting into NumPy Basics

IntroductionCreating NumPy ArraysManipulating and IndexingBasic Statistical OperationsLinear Algebra OperationsReshaping and StackingSaving and Loading Arrays to/from Files

bookSaving and Loading Arrays to/from Files

NumPy offers a variety of functions for saving and loading numPy arrays to and from files, such as:

  • save(): Saves an array to a binary file in NumPy's .npy format;
  • savez(): Saves multiple arrays to a single compressed .npz file;
  • savetxt(): Saves an array to a text file;
  • load(): Loads an array from a binary file in NumPy's .npy format;
  • loadtxt(): Loads an array from a text file.

Tarefa

  1. Save the newly created array in NumPy's .npy format.
  2. Save the array to a text file.
  3. Load back in the array.

Congratulations!

Congratulations on completing this NumPy tutorial! You have gained substantial knowledge about handling arrays and matrices in Python, laying down a strong foundation for utilizing NumPy in your data processing and analysis endeavors.

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NumPy offers a variety of functions for saving and loading numPy arrays to and from files, such as:

  • save(): Saves an array to a binary file in NumPy's .npy format;
  • savez(): Saves multiple arrays to a single compressed .npz file;
  • savetxt(): Saves an array to a text file;
  • load(): Loads an array from a binary file in NumPy's .npy format;
  • loadtxt(): Loads an array from a text file.

Tarefa

  1. Save the newly created array in NumPy's .npy format.
  2. Save the array to a text file.
  3. Load back in the array.

Congratulations!

Congratulations on completing this NumPy tutorial! You have gained substantial knowledge about handling arrays and matrices in Python, laying down a strong foundation for utilizing NumPy in your data processing and analysis endeavors.

Mark tasks as Completed
Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Seção 1. Capítulo 7
AVAILABLE TO ULTIMATE ONLY
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