A human without brain can’t do anything, similarly python without packages are of no use. But fortunately,we have got a number of packages, libraries to handle data. One such useful library is **numpy**.

## NumPy

**Numpy** also called **numerical python** is one of the core libraries of python used for scientific computing of data. It has tools that makes easy to work with **multi dimensional array** objects and **efficient** computation of matrices.

## USAGE

- Data structures consume
**less memory**. - They have
**faster**computation than lists. - They have built in linear
**algebra****operations**.

## INSTALLATION

This package is not installed in python by default.Follow these steps for installation.

**Pip**is a package management system used to install and manage software packages written in Python. Upgrade pip before installing python.

pip install pip --upgrade pip --version

**Download**the NumPy package from NumPy library**Copy**the file to**C:\Python27\Scripts**- Open the
**terminal**or command prompt and type

pip install numpy-1.14.5+mkl-cp27-cp27m-win32.whl

## 1) Array Creation

#Input import numpy as np first=np.array([10,20,30,40,50]) print("Addition of 1", first+1) print("Subtraction of 10", first-10) print("Multiplication of 2", first*2) #Output Addition of 1 [11,21,31,41,51] Subtraction of 10 [0,10,20,30,40] Multiplication of 2 [20,40,60,80,100]

## 2) Find the largest element of Array

#Input a= np.array([[1, 15, 6],[14, 7, 12]]) print ("Largest element in this array:", a.max()) #Output Largest element in this array:15

## 3) Array Multiplication

#Input first= np.array([[1, 2],[3, 4]]) second= np.array([[1, 2],[3, 4]]) print("array multiplication:",first*second) #Output array multiplication:[[1 4] array multiplication:[9 16]]

## 4) To specify type of array during array creation

#Input arr=np.array( [ [1,2],[3,4] ],dtype=complex) #Output array( [1.+0.j,2.+0.j],[3.+0.j,4.+0.j] ] )

## Universal Functions

- sin
- cos
- exp
- sqrt

Hope this post has provided an overview of this package.What are you waiting for?Time to prove that you are a data scientist.

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