Numpy

Numpy commands for managing numerical computing, linear algebra, and random number generation

16 commands

Commands

16 commands available

numpy

Import NumPy

Import NumPy library in Python

import numpy as np

numpy

import

setup

numpy

Create Array

Create a NumPy array

np.array([1,2,3])

numpy

array

create

numpy

Arange

Create array with evenly spaced values

np.arange(start, stop, step)

numpy

array

sequence

numpy

Linspace

Create array with evenly spaced numbers over interval

np.linspace(start, stop, num)

numpy

array

sequence

numpy

Zeros

Create array filled with zeros

np.zeros((rows, cols))

numpy

array

init

numpy

Ones

Create array filled with ones

np.ones((rows, cols))

numpy

array

init

numpy

Random Numbers

Generate random numbers

np.random.rand() / np.random.randint()

numpy

array

random

numpy

Array Shape

Get shape of array

arr.shape

numpy

array

info

numpy

Reshape

Reshape an array

arr.reshape(new_shape)

numpy

array

reshape

numpy

Sum

Compute sum of array elements

np.sum(arr, axis)

numpy

math

aggregate

numpy

Mean

Compute mean of array elements

np.mean(arr, axis)

numpy

math

aggregate

numpy

Standard Deviation

Compute standard deviation

np.std(arr)

numpy

math

aggregate

numpy

Dot Product

Matrix dot product

np.dot(arr1, arr2)

numpy

math

matrix

numpy

Transpose

Transpose an array

arr.T

numpy

array

matrix

numpy

Max & Min

Find maximum and minimum values

np.max(arr), np.min(arr)

numpy

math

aggregate

numpy

Indexing & Slicing

Access array elements by index

arr[row, col]

numpy

array

indexing