A python analysis of Covid-19 Italy

Photo by Markus Spiske on Unsplash

Here’s with a new simple tutorial for analysing a dataset.
In this case i’ve taken the Italian dataset of patients positive to COVID-19 aka Corona virus provided by the official Protezione civile GitHub repository:
https://github.com/pcm-dpc/COVID-19/blob/master/dati-andamento-nazionale/dpc-covid19-ita-andamento-nazionale.csv

Dataset

The dataset is as simple as possible without useless columns (Many times i’ve seen raw informations and column without meaning ).
In our analysis we take only two columns, data and totale_positivi (date, total_positive).

Goal

The goal is to forecast the number of positive patients in this time-series events.
We want to answer the question: “How many positive patients there will be in 7 days as is now?”

Model

The model is a simple time-series forecasting using python statsmodels ARIMA model.

Language

As previously said i’ve used Python3 which is very reliable for this kind of analysis.

Code

It’s a huge project and i invite to to my gitHub repository and see my code, also i suggest to fork or clone my project because is under GNUv3 licence so feel free to use it as you want and adapt it to you data.

xCloudx8/covid19Python

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Leave some comments down here and let me know what you think about it.

Thanks for your attention.