Data Visualization

Blog of the Data Visualization & Communication Course at OSB-AUB

This is my favorite part about analytics: Taking boring flat data and bringing it to life through visualization” John Tukey

Children Out of School: Some Insights

Children Out of School: Some Insights

According to UNESCO, about 258 million children and youth are out of school for the school year ending in 2018. The total includes 59 million children of primary school age, 62 million of lower secondary school age and 138 million of upper secondary age. This is a major humanitarian challenge that all countries have united to address by anchoring it within SDG number 4: Quality Education.

Every Child deserves the opportunity to learn. In this Dashboard, we tried to show visualizations that highlight the reality behind Children Out Of School.

Poverty is a barrier that keeps children out of schools.

The gap between males and females attending schools was equal to 14% in 1970 and decreased to reach 2% in 2018. For girls in some part of this world, education chances are still restricted.

Data Source: World Bank Data

Mom Education for Infants’ Survival – Sub Saharan Africa

Mom Education for Infants’ Survival – Sub Saharan Africa

“When you carry a life and it’s there, and then gone, a part of your soul dies.  Forever”.  Casey Wiegano

Yes, I’m a mom, and just thinking about it for a fraction of a second breaks my heart! Unfortunately,  Sub-Saharan countries along with some South Asian countries which are highlighted with darker blue in the map whiteness the highest infant mortality rates. In Sub-Saharan countries ,on average, 68 infants die in every 1000 births and this rate is the second highest among the classified regions (second graph)

From the bottom graphs, we can see that there is a high correlation between the average adolescents fertility rates and the female adolescents who are out of school. On the other hand, a correlation exists between the adolescents fertility rate and the mortality rate of infants.The highest rates are also observed in Sub-Saharan countries (darker blue).

Putting these observations into one sentence, we can infer that the more adolescent females that are out of school the more likely they are to give birth to infants that have higher chances of dying.

As such, female students in Sub-Saharan countries should be empowered. They should be encouraged to continue their education aiming to lower their fertility rates and indirectly lower infants mortality rates. With no doubt, many other factors should be considered such as improving healthcare systems for both, moms and children.

 

 

Culture vs. Female Employment to Population Ratio

Culture vs. Female Employment to Population Ratio

Females in the Arab World are always faced with discriminatory situations in a ‘professional environment’. From personal questions in an interview to on-the-job obstacles, something always has to remind us of who we are and how anchored we are to it. It is not very different around the world, however, females have only recently started to break through the notions of the ‘working man’, proving that the only professional difference between them is inside the minds of those who believe it exists.

When I started exploring the World Development Indicators data on Tableau, I could not but stop at the Employment to Population Ratio. So I developed a dashboard visualized below.

Culture Vs. Female Employment to Population Ratio

As seen on the map, there are big differences in Female Employment to Population Ratios around the world. Looking deeper into the ratios of 2 adjacent but very different cultures, the European Union and Arab Countries – the line graphs to the right -, we can notice the difference in the gaps between female and male ratios. While the Male Employment to Population Ratio is almost the same across both areas, there is a big difference in the female’s numbers, of course affecting the total ratios.

I believe the needed change starts in education – not only that of little girls who need to be equipped by the time they can join the workforce, but also of societies to be welcoming, and supportive of those girls. Many forces enter in this journey, in many cases education is an unaffordable luxury, which is why the intrusion of governments and NGOs is highly needed.

The featured image is from Aptology.

Factors Contributing to Unemployment

Factors Contributing to Unemployment

Countries face a huge loss due to unemployment. In order to find a solution for unemployment, we searched for the factors causing it. As shown below, gender discrimination, country’s GDP, distribution of jobs among the economic sectors, and educational level have a huge impact on Unemployment.Above,you can alter the regions you want to analyze from using multiple values drop-down.

In Conclusion:
-As GDP increase the Unemployment rate decrease
-Female Unemployment is higher than the males due to gender discrimination in workplace
-Employment rate is higher in the services sectors which mean that there is no equal job opportunities in between sectors causing higher
unemployment
-If the educational level is more advanced, their is lower unemployment rate

Data Source: https://datacatalog.worldbank.org/dataset/world-development-indicators

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