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Updated 4 years ago
Useful NumPy functions for plotting and linear algebra
From finding relevant plotting points to checking matrix diagonlization
NumPy's main object is the array, which can be used on one to two axes for plotting functions of y with respect to x.
However, NumPy's powerful linalg
package allows for further insight into matrix manipulation for solving nxn systems of linear equations.
Both of these topics will be covered through explanation and examples of the following functions:
np.where()
np.linspace()
np.linalg.det()
np.linalg.inv()
np.linalg.matrix_power()
!pip install jovian --upgrade -q
import jovian
jovian.commit(project='numpy-array-operations')
[jovian] Attempting to save notebook..
[jovian] Please enter your API key ( from https://jovian.ml/ ):
API KEY: ········
[jovian] Updating notebook "janrhaverkamp/numpy-array-operations" on https://jovian.ml/
[jovian] Uploading notebook..
[jovian] Capturing environment..
[jovian] Committed successfully! https://jovian.ml/janrhaverkamp/numpy-array-operations
Let's begin by importing Numpy and listing out the functions covered in this notebook.