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

Python Data Analysis and Visualization

From Python to Numpy

## Introduction
One of the strengths of NumPy is that it can be used to build new objects or to
[subclass the ndarray](https://docs.scipy.org/doc/numpy/user/basics.subclassing.html) object. This
later process is a bit tedious but it is worth the effort because it allows you
to improve the `ndarray` object to suit your problem.


We'll examine in the following section two real-world cases (typed list and memory-aware array)
that are extensively used in the [glumpy](http://glumpy.github.io) project
(that I maintain).
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## What is a Typed list?

Typed list (also known as ragged array) is a list of items that all have the same data type (in the sense of NumPy). They offer both the list and the `ndarray` API (with some restriction of course) but because their respective APIs may not be compatible in some cases, we have to make choices. For example, concerning the `+` operator, we'll choose to use the NumPy API where the value is added to each individual item instead of expanding the list by appending a new item (1).


# Introduction
One of the strengths of NumPy is that it can be used to build new objects or to
[subclass the ndarray](https://docs.scipy.org/doc/numpy/user/basics.subclassing.html) object. This
later process is a bit tedious but it is worth the effort because it allows you
to improve the `ndarray` object to suit your problem.


We'll examine in the following section two real-world cases (typed list and memory-aware array)
that are extensively used in the [glumpy](http://glumpy.github.io) project
(that I maintain).
$$$$

# What is a Typed list?

Typed list (also known as ragged array) is a list of items that all have the same data type (in the sense of NumPy). They offer both the list and the `ndarray` API (with some restriction of course) but because their respective APIs may not be compatible in some cases, we have to make choices. For example, concerning the `+` operator, we'll choose to use the NumPy API where the value is added to each individual item instead of expanding the list by appending a new item (1).


This lesson is a brief introduction to Typed list and how it is implemented using the NumPy library. 

Introduction

Anatomy of an Array

Code Vectorization

Problem Vectorization

Custom Vectorization

Beyond NumPy

Typed list

Introduction

What is a Typed list?