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Suicide rates vs prevalence of depressive disorder rates

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Mmnalk
Last edited Sep 10, 2021
Created on Sep 5, 2021

This example displays a text-based summary of a dataset comparing suicide rates and depressive disorder prevalence across countries. The visualization loads a CSV file from a GitHub repository and outputs the file size in kilobytes, the total number of data rows, and the number of columns using D3 v5’s `d3.csv` and `d3.csvFormat` methods. The rendered result is a simple preformatted text block, highlighting the dataset’s structure rather than a graphical chart. The original data originates from Our World in Data.

AI-generated description

Mental health Depression disorder Data summary

Found this concerning topic for #datavisualization. Sharing the data set here if you wish to create dataviz.

These are few questions one can get from the data viz.

What are mental health disorder types? How many people suffer these disorder types? How many people in your country have depression? Is depression is higher in men or women? Does depressoin leads to suicide? What percentage? Which age group has more depression?

Original data set source : https://ourworldindata.org Original blog : https://ourworldindata.org/mental-health#all-charts-preview

Some informative youtube videos about depression : https://www.youtube.com/watch?v=z-IR48Mb3W0 https://www.youtube.com/watch?v=IDPDEKtd2yM

This dataset contain : 1)prevalence_by_mental_and_substa 2)depression_by_level_of_educatio 3)prevalence_of_depression_by_age 4)prevalence_of_depression_males 5)Suicide rates vs prevalence of depressive disorder rates* 6)number_with_depression_by_count

This file is Suicide rates vs prevalence of depressive disorder rates , and it's contain the following :

1)entity is categorical attributes 2)code is categorical attributes 3)year is categorical attributes 4)suicide_rate_deaths_per_100_000_individuals is quantitative attributes 5)depressive_disorder_rates_number_suffering_per_100_000 is quantitative attributes 6)population is quantitative attributes

I'm intrestin in categorical attributes We remove the rows with missing values

MIT Licensed

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