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mortality-viz

Basic descriptive statistics on mortality data

The present project provides with some visualisation/analyses on data on 2020 mortality from various (national authoritative) sources based on availability.

1. Early mortality data from ISTAT

Objectives

This material will enable you to reproduce most of the figures presented in Ricciato's preliminary study on 2020 mortality data from ISTAT (see below):

The "Data resources" section below references the data used for the study (freely available for download). Note that the results and figures presented in Ricciato's document refer to the data downloaded at the time of the study, hence on April, 16th.

(Re)run

You can rerun the notebook :

  • in Google colab environment (you will need a Google login): launch Open In Colab.
  • in binder environment: Binder
Resources and references

2. Weekly excess mortality rates over Europe

Objectives

This material will enable you to visualise available data on weekly excess mortality rates over available European countries (see below):

(Re)run

You can rerun the notebook :

  • in Google colab environment (you will need a Google login): launch Open In Colab.
Resources and references
  • Eurostat data on "Deaths by age group, sex, week and NUTS 3 region": demo_r_mweek3.
  • Eurostat geographical data on regional units NUTS 2016 (see GISCO website).

Usage

You will need standard Python library for data handling, e.g., pandas, numpy, matplotlib, and date manipulation, e.g., datetime, calendar (see also below). The code herein also uses the pyeudatnat package.

The environment.yml file in this directory provides with all requirements. See also the "Settings" cell of the ITmortality.py source code file.

Note

Most of the data used in the provided notebooks will fetch data from the original sources directly. Therefore, when (re)running the notebook, the results and figures you generate always refer to the latest available (possibly updated) data.

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status since 2020
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license EUPL

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