Visualizing suicide data with javascript libraries
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Updated
Jan 11, 2022 - JavaScript
Visualizing suicide data with javascript libraries
Data analysis of suicide happened in India between year 2001 to 2012
Data Analysis of suicides in India
To categorize tweets according to the severity level of suicidal intentions expressed in tweets’ text.
This research project seeks to comprehensively investigate suicide rates and their underlying factors over the period from 1985 to 2020.
In this project, three different models based on GAT, GCN and SAGE have been implemented to examine their performance on two prominent social networking platforms, namely Twitter and Reddit.
You don't have to face it alone.
From growing up in the heart of Silicon Valley, I have always wondered what was the factors that play a role in Suicide. There have been a plethora of suicide clusters from my High School in Palo Alto. This project seeks to explore the underlying factors. We will use a sample of 44,000 gather data from 141 different Countries, between the 80's …
This part of the Capstone Project entails a machine learning model to predict macroeconomic movements using geo-regional data in the EU. This project involved extensive data analysis, predictive modeling, and cross-comparison techniques.
Analysis scripts and randomly generated data for Suicide and Life-Threatening Behavior paper: 'Identifying person-specific coping responses to suicidal urges: A case series analysis and illustration of the idiographic method'
Suicide Statistics for India in the year 2020 classified by Gender, Age Bracket and Reposted Cause. Visualised using Python
Analysis of suicides that occurred in 35-year period
Statistical analysis of relationship between overall happiness, climate and suicide ratio accross the Globe.
Building a dashboard to present the suicide rate (per 100,000 population) for 2019 across the world for as crude suicide rate and suicides rate by gender.
Our study aims to explore the suicides pattern from the year 1985 to the year 2016 through global, continent and country scales, as well as gender, age, GDP and generation factors. The descriptive exploration obtained will then be verified through statistical inferential analysis. We set the target audience as World Health Organization officer w…
Suicide rate research
Problem to solve: find the patterns for increased suicide rates (1985 to 2016) among different cohorts globally, across the socioeconomic spectrum, using exploratory data analysis. Using bivariate analysis, I try to determine if there is any relationship between two variables.
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