## Python Lists VS Numpy Arrays

**NumPy** is the essential package for scientific computing in Python.** Numpy** arrays exhibits advanced mathematical and different types of operations on large numbers of data. Commonly, such operations are run more efficiently and by using Python’s built-in sequence it is possible with less code. NumPy is Python extension module but not another programming language. It offers quick and efficient operations on arrays of homogeneous data.

**Important things about Numpy arrays:**

- We can make N-dimensional array in python using numpy.array().
- Data inside array must be of same Datatype i.e., Homogeneous.
- It is possible to perform operations element wise.
- For easy matrix computation
**Numpy**array has various function, methods, and variables. - In memory elements of an array are stored contiguously.

**Advantages of using Numpy Arrays Over Python Lists:**

- consumes less memory.
- fast as compared to the python List.
- convenient to use.

**List:**

A **list** is a collection of items which are ordered and changeable. In Python, lists are enclosed with in square brackets.

**Important things about Python Lists:**

- The list might be homogeneous or heterogeneous.
- It is not possible to perform element wise operation on the list.
- Python list is 1 dimensional by default. Yet we can create an N-Dimensional list.
- Elements of a list not required to be contiguous in memory.

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