Updated 3 years ago
Assignment 2 - Numpy Array Operations
5 Numpy functions you didn't know you needed in scientific computation
NumPy is the fundamental package for scientific computing in Python. It is a Python library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra, basic statistical operations, random simulation and much more.
Want to learn more about this visit https://numpy.org/doc/stable/user/whatisnumpy.html
5 useful Numpy Functions
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np.char.add()
This function concatenates element-wise the strings of two arrays of matrices.
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np.linalg.det()
This function is used to calculate the determinant of a square matrix
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np.trim_zeros()
This function will trim the leading and trailing zeros
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np.sort()
This function is used to sort the values in an array
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np.unique()
This function help us to find the unquie values in an array
!pip install jovian --upgrade -q
import jovian
jovian.commit(project='numpy-array-operations')
[jovian] Updating notebook "anilpiparaiya/numpy-array-operations" on https://jovian.ai
[jovian] Committed successfully! https://jovian.ai/anilpiparaiya/numpy-array-operations
Let's begin by importing Numpy and listing out the functions covered in this notebook.