Array-Oriented Programming with NumPy

From your reading of Chapter 7 of our textbook array-oriented programming with NumPy, discuss with the class (with original examples).

  • arrays creation and operations with Numpy.
  • Numpy calculation methods and functions.
  • arrays slicing and reshaping with Numpy.

Please include a Works Cited too for citations.

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  1. Array-Oriented Programming with NumPy

Objectives

In this chapter, you’ll:

  • Learn what arrays are and how they differ from lists.
  • Use the numpy module’s highperformance ndarrays.
  • Compare list and ndarray performance with the IPython %timeit magic.
  • Use ndarrays to store and retrieve data efficiently.
  • Create and initialize ndarrays.
  • Refer to individual ndarray elements.
  • Iterate through ndarrays.
  • Create and manipulate multidimensional ndarrays.
  • Perform common ndarray manipulations.
  • Create and manipulate pandas one-dimensional Series and two-dimensional DataFrames.
  • Customize Series and DataFrame indices.
  • Calculate basic descriptive statistics for data in a Series and a DataFrame.
  • Customize floating-point number precision in pandas output formatting.

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