We will use the stationary distribution of an absorbing markov chain to simulate a Galton board.

In this notebook will try to convert pure Python code to Cython and test speed up with magic functions.

In this notebook we will compute and visualise some famous and nice looking number sequences.

The goal of this notebook is to provide an introduction to stock market portfolio optimisation using Python.

Continuing short series on data analysis applied to finance, this article is a step further into exploring Python’s many functionalities towards stock market diagnosis.

This article is the first of a short series on data analysis applied to finance, in which I’ll seek to demonstrate a few useful artifacts used by stock market professionals, data analysts and traders. The whole approach is done using Python.

In this notebook we will use the data-set, International football results from 1872 to 2019. We will try ANOVA hypothesis testing technique.