Data analytics and exploratory data analysis

Department of Environmental Engineering
University of Genoa

Marie Curie Early Stage Training Site at the University of Genova, Italy

Data scraping, data wrangling, data analytics, exploratory data analysis, advanced plotting and clustering with love.

These are the Python (version 2.7.0) libraries that you will need to install to follow these tutorials:

•    requests 2.7.0 or newer.
•    pandas 0.16.2 or newer.
•    ipython 3.2.1 or newer.
•    json 2.0.9 or newer.
•    matplotlib 1.4.3 or newer.
•    seaborn 0.6.0 or newer.
•    scipy 0.16.0 or newer.

These tutorials are locate in the following githun link:
https://github.com/joelguerrero/data_science/tree/master/sport_analytics1

Sport analytics - Tutorial 1.

This is the first part of this series of tutorials on sport analytics.
In this tutorial we mainly address data scraping from the web.

The notebook related to this tutorial is:
•    sport_analytics_1.ipynb

You can open the notebook using nbviewer, just go to this link
http://nbviewer.ipython.org/github/joelguerrero/data_science/blob/master/sport_analytics1/sport_analytics_1.ipynb

Sport analytics - Tutorial 2.

This is the second part of this series of tutorials on sport analytics.
In this tutorial we mainly address how to read a csv and json file, some data wrangling and data manipulation using pandas, and basic data analytics and plotting.

The notebook related to this tutorial is:
•    sport_analytics_2.ipynb

You can open the notebook using nbviewer, just go to this link
http://nbviewer.ipython.org/github/joelguerrero/data_science/blob/master/sport_analytics1/sport_analytics_2.ipynb

Sport analytics - Tutorial 3.

This is the third part of this series of tutorials on sport analytics.
In this tutorial we mainly address advanced data analytics and plotting.

The notebook related to this tutorial is:
•    sport_analytics_3.ipynb

You can open the notebook using nbviewer, just go to this link
http://nbviewer.ipython.org/github/joelguerrero/data_science/blob/master/sport_analytics1/sport_analytics_3.ipynb

Sport analytics - Tutorial 4.

This is the last of this series of tutorials on sport analytics.
In this tutorial we address unsupervised machine learning (clustering) using scipy and some advanced plotting.

The notebook related to this tutorial is:
•    sport_analytics_4.ipynb

You can open the notebook using nbviewer, just go to this link
http://nbviewer.ipython.org/github/joelguerrero/data_science/blob/master/sport_analytics1/sport_analytics_4.ipynb

Joel GUERRERO
joel.guerrero@unige.it
Personal Web Page

DICAT, University of Genova
1, Via Montallegro
16145 Genova, Italy

Last update: 21/AUG/2015