Data science is analyzing of datasets and Numpy or Numerical Python library is the best available library to play around with numerical data. It is extensively used in data calculation, and even when you are using highly encapsulated libraries build on top of numpy, a fair understanding and knowledge of numpy is essential, to fit the data for the purpose the program is being designed.

## How to install Numpy?

In most use cases the best way to install NumPy on your system is by using a pre-built package for your operating system.

*Perquisites*

- A working Python 3 environment
- A working pip installation

Installation using pip

from the command line

python pip install numpy

## Numpy Data Structures

At the core of the NumPy package, is the *ndarray* object. This encapsulates n-dimensional arrays of homogeneous data types, with many operations being performed in compiled code for performance.

There are several important differences between NumPy arrays and the standard Python sequences:

- NumPy arrays have a fixed size at creation, unlike Python lists (which can grow dynamically). Changing the size of an ndarray will create a new array and delete the original.
- The elements in a NumPy array are all required to be of the same data type, and thus will be the same size in memory. The exception: one can have arrays of (Python, including NumPy) objects, thereby allowing for arrays of different sized elements.
- NumPy arrays facilitate advanced mathematical and other types of operations on large numbers of data. Typically, such operations are executed more efficiently and with less code than is possible using Python’s built-in sequences.
- A growing plethora of scientific and mathematical Python-based packages are using NumPy arrays; though these typically support Python-sequence input, they convert such input to NumPy arrays prior to processing, and they often output NumPy arrays. In other words, in order to efficiently use much (perhaps even most) of today’s scientific/mathematical Python-based software, just knowing how to use Python’s built-in sequence types is insufficient – one also needs to know how to use NumPy arrays.

## How to import Numpy

Numpy libraries can be imported into python using the following code

import numpy as np #here we are importing numpy library with alias np