Dive into NumPy! Start organizing, rearranging, and sampling your data.

Python Data Analysis and Visualization

From Python to Numpy

The [NumPy documentation](https://docs.scipy.org/doc/numpy/reference/arrays.ndarray.html) defines the
ndarray class very clearly:

  >*An instance of class **ndarray** consists of a contiguous one-dimensional segment
  of computer memory (owned by the array, or by some other object), combined
  with an indexing scheme that maps N integers into the location of an item in
  the block.*

Said differently, an array is mostly a contiguous block of memory whose parts
can be accessed using an indexing scheme. Such indexing scheme is in turn
defined by a [shape](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.shape.html#numpy.ndarray.shape)
and a [data type](https://docs.scipy.org/doc/numpy/reference/arrays.dtypes.html) and this is
precisely what is needed when you define a new array:


This lesson explains the memory layout using NumPy.

Introduction

Anatomy of an Array

Code Vectorization

Problem Vectorization

Custom Vectorization

Beyond NumPy

Memory layout