Finding 'n' Largest Values in NumPy

Python
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NumPy is a powerful library for scientific computing in Python that provides a convenient way to perform mathematical operations on large, multi-dimensional arrays and matrices. Finding the first ‘n’ largest value(s) from a NumPy array is a common task in data analysis and machine learning. There are several ways to accomplish this task using NumPy, which are mentioned below:

1. Using “np.sort()” function:

  • Imports the NumPy library and creates a 1D NumPy array.
  • Sets a variable n to 3.
  • Code sorts the input array in ascending order using np.sort() and reverses the sorted array using [::-1].
  • Code then selects the first n (3) elements of the reversed sorted array using [:n] and stores the result in a new array.
  • Finally, the new array is printed to the console.

This code returns the n largest values of the input array, sorted in descending order. This is slower compared to the second method as this function first sorts the elements and then fetches the required element(s).

2. Using “np.partition()” function:

  • Imports the NumPy library and creates a 1D NumPy array.
  • Sets a variable n to 3.
  • Code partitions the input array using np.partition(), with the -n index indicating that the right partition should contain the n largest values.
  • Code then selects the last n elements of the right partition using [-n:] and stores the result in a new array.
  • Finally, the new array is printed to the console.

This code returns the n largest values of the input array, sorted in ascending order.

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