Name: Akshaya Ayyah

Link to Datasets:

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Link to Github:

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Inspiration

As education and independence become core factors of determining the state of an area, I wanted to create an analogous representation of these factors on the life expectancies of a country’s people. It is important to understand that the data presented is a testament to the conditions of people living in these countries, and that the relationship between certain variables can prove pivotal to developing policies that address their struggles and improve their wellbeing. In keeping with the theme of social justice, I decided to analyze three factors that differentiate the world’s disparities in living conditions: life expectancy, schooling, and the freedom to make life choices. I explored 2 data sets, multiple csv files, and compared their contents to create cogent visualizations that demonstrated the lacking factors of different regions of the world. I believe that developing a mutual understanding of underlying conditions is the key to building effective solutions, so I hope this project makes strides towards that goal.

What it does

Hover over the visualizations to learn cool statistics about the relationships between certain factors of living conditions in different regions of the world!

How we built it

The first step was to find data sets that contained information related to social justice and humanitarian conditions; the Human Development and World Happiness Report fit the bill perfectly! I conducted exploratory data analysis (EDA) for both of these datasets and examined the variables both individually, and in a larger context, to see how I could use them in my visualization. I also analyzed historical data to see why there were certain dips in the graphs, which proved helpful in furthering my understanding. I build all three of these plots using the language Python and graphing library Plotly (aided by Pandas) on Jupyter Notebook. It was a lot of trial and error, or as I like to call it, Google and YouTube, but it was successful at the end.

Challenges we ran into

Given the robust nature of the datasets in question as well as vastness of my topic of choice, the range of appropriate visualizations is virtually endless. I wanted to highlight disparities in social justice indicators like Education and the Freedom to Make Life Choices across the globe, and in doing so, decided that geospatial heatmaps would be a valuable tool.

My strategy was to begin by visualization the globe as a whole, through the line graph and bar chart visuals to identify where countries and regions were similar and how they differed. It was a little hard to figure out which plot to use, as there are so many choices. However, I'm glad I chose the ones I did(geospatial bubble map, bar chart, and line graph), because they are interactive, visually stunning, and get the point across very well.

Accomplishments that we're proud of

The interactive plots, aesthetics, and overall readability of the plots is something I thought was super cool. For example, all of the visualizations an be hovered over to see specific details and values. The size of the bubbles in the geospatial heat map is influenced by the variable of mean years of schooling. The color in all the graphs in indicative of various variables. I wanted to create something that someone could understand just by glancing at it, and I hope that I achieved that.

What we learned

The main takeaways from this project are that: I. Different regions of the world have different priorities and social structures, leading to differences in not just life expectancy, but also other elements like years of education. II. Life Expectancy has a strong correlation with social support and the average years of education. III. The freedom to make life choices is dynamic throughout time. IV. Countries and regions with a higher average years of education, more social support, and more freedom tend to also have higher life expectancies.

What's next for Global Social Justice - Data Visualization + Analysis

Historical factors such as colonialism and the growing gap between the Global North and Global South were also clearly indicated in my analysis. I want to dive deeper into these effects. I believe that in order to encroach this gap, we need to focus on the next generation’s education, expand their involvement in governmental decision making, and increase the collective support that they get from their authorities.

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