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

Python Data Analysis and Visualization

From Python to Numpy



You've almost reached the end of the course and, hopefully, you've learned that
NumPy is a very versatile and powerful library. However in the meantime,
remember that Python is also quite a powerful language. In fact, in some
specific cases, it might be more powerful than NumPy.

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## Allocations 

Let's consider, for example, an interesting exercise that has been proposed by Tucker Balch in his Computational Investing course. The exercise
is written as:
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### 

>*Write the most succinct code possible to compute all "legal" allocations to 4 stocks such that the allocations are in 1.0 chunks, and the allocations sum to 10.0.*
$$$$
Yaser Martinez collected the different answers from the community and the proposed solutions yield surprising results. But let's start with the most obvious Python solution:



You've almost reached the end of the course and, hopefully, you've learned that
NumPy is a very versatile and powerful library. However in the meantime,
remember that Python is also quite a powerful language. In fact, in some
specific cases, it might be more powerful than NumPy.

$$$$
# Allocations 

Let's consider, for example, an interesting exercise that has been proposed by Tucker Balch in his Computational Investing course. The exercise
is written as:
$$$$
##  

>*Write the most succinct code possible to compute all "legal" allocations to 4 stocks such that the allocations are in 1.0 chunks, and the allocations sum to 10.0.*
$$$$
Yaser Martinez collected the different answers from the community and the proposed solutions yield surprising results. But let's start with the most obvious Python solution:

Python is quite a powerful language! Let's find out how by looking at an interesting example proposed by Tucker Balch. 

Introduction

Anatomy of an Array

Code Vectorization

Problem Vectorization

Custom Vectorization

Beyond NumPy

Back to Python

Allocations