Numpy Tutorial

In this Numpy Tutorial, we will learn how to install numpy library in python, numpy multidimensional arrays, numpy datatypes, numpy mathematical operation on these multidimensional arrays, and different functionalities of Numpy library.

What is Numpy?

Numpy is a Python library that supports multi-dimensional arrays and matrix. It also provides many basic and high-level mathematical functions that can be applied on these multi-dimensional arrays and matrices with less code footprint.

Why Numpy?

There are many reasons why Numpy package has been used by data scientist and analysts, machine learning experts, deep learning libraries, etc. We will go through some of the most basic advantages of Numpy over regular lists or arrays in Python.

  • The code that involves arrays with Numpy package is precise to apply transformations or operations for each element of the multidimensional arrays unlike a Python List.
  • Since n-dimensional arrays of Numpy use a single datatype and contiguous memory for storage, they take relatively lesser memory read and write times.
  • The most useful features of Numpy package is the compact datatypes that it offers, like unsigned integers of 8 bits, 16 bits size and signed integers of different bit sizes, different floating point precisions, etc.
Numpy Tutorial

Basics of Numpy

Numpy Introduction

Installing Numpy Library

Python NumPy Arrays

Python NumPy Data Types

Python NumPy Array Creation – Empty, Zeroes and Ones

Create ndarray with Data

ndarray with Numerical Range

Python NumPy Indexing and Slicing

Python NumPy Advance Indexing

Python NumPy Broadcasting

Python NumPy Sorting

Python NumPy Copy and View

NumPy Accessing Array Elements (Iteration)

NumPy Matrix Multiplication

NumPy Basic Functions

NumPy arange() function

NumPy reshape() function

NumPy append() function

NumPy concatenate() function

NumPy array() function

NumPy transpose() function

NumPy partition() function

NumPy Mathematical Functions

NumPy ceil() function

NumPy floor() function

NumPy trunc() function

NumPy fix() function

NumPy String Functions

NumPy islower() function

NumPy find() function

NumPy count() function

NumPy istitle() function

NumPy decode() function

NumPy encode() function

NumPy replace() function

NumPy splitlines() function

NumPy add() function

NumPy multiply() function

NumPy center() function

NumPy join() function

NumPy split() function

NumPy title() function

NumPy lower() function

NumPy isupper() function

NumPy isnumeric() function

NumPy isalpha() function

NumPy index() function

NumPy startswith() function

NumPy isspace() function

NumPy isdigit() function

NumPy isdecimal() function

NumPy upper() function

NumPy capitalize() function

NumPy swapcase() function

NumPy strip() function

Numpy char.partition() function

NumPy Statistical Functions

NumPy amin() Function

NumPy amax() Function

NumPy ptp() function

NumPy median() function

NumPy mean() function

NumPy std() function

NumPy Library (Matrix Library)

NumPy eye() function

NumPy identity() function

NumPy rand() function

NumPy empty() function

NumPy ones() function

NumPy zeros() function

Binary Operations

NumPy left_shift() function

NumPy right_shift() function

NumPy bitwise_xor() function

NumPy invert() function

NumPy bitwise_or() function

Numpy bitwise_and() function

Linear Algebra

NumPy dot() function

Miscellaneous

NumPy asarray() function

NumPy frombuffer() function

NumPy logspace() function

NumPy linspace() function

NumPy fromiter() function

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