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In the same spirit of the vessel breakdown module, we need to create a module for individuals breakdown where we will provide overview of statistics over the population of individuals covered by Calipseo.
General requirements (as for any module):
writing convention for R scripts _ui, _server suffixes
json definition + i18n json file for i18n terms
data accessors with i18n support for names,
(same methodology as for modules done for now)
For the inception of this module we will produce 2 dynamic - with plotly technology:
Breakdown of individuals by gender; as dynamic piechart.
Breakdown of individuals by age / gender, as dynamic pyramid age:
** age: to be calculated from the DATE_OF_BIRTH (when not NA that we exclude for the timebeing)
** for the plotly age pyramid you can see the solution provided at [https://stackoverflow.com/questions/72318377/pyramid-plot-in-plotly]
Any question on this, please ask me on chat or as comment of this ticket
Author: Emmanuel Blondel @eblondel
Date of creation: 2022-08-01T13:47:19.162+0000
Last update: 2022-08-01T13:47:19.162+0000
As 2d iteration, let's restructure the UI as follows:
We are going to add multiple types of breakdown (what you did is one type: by gender). To illustrate these various cases, let's use vertical tabs.
** First action => to wrap the breakdown you set in a first vertical tab "Breakdown by gender"
Create a second vertical tab, that will tackle "Breakdown by educational level": referring to table reg_entity_individual_education and codelist cl_app_education_levels
Remember that all terms have to be managed with i18n vocabs (JSON files, and keys to use in the code)
In the same spirit of the vessel breakdown module, we need to create a module for individuals breakdown where we will provide overview of statistics over the population of individuals covered by Calipseo.
General requirements (as for any module):
(same methodology as for modules done for now)
For the inception of this module we will produce 2 dynamic - with plotly technology:
** age: to be calculated from the DATE_OF_BIRTH (when not NA that we exclude for the timebeing)
** for the plotly age pyramid you can see the solution provided at [https://stackoverflow.com/questions/72318377/pyramid-plot-in-plotly]
Any question on this, please ask me on chat or as comment of this ticket
cc [~alexandre.bennici@fao.org]
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