Over the course of creating this portfolio, my goal was to create a link between the exploratory and narrative project. Is there some dataset out there that can explain or provide a fractional story behind the trends of international departures? This question ended up being difficult to pursue as I investigated different topics that either had a link with my exploratory project or none at all. I originally danced around the idea of building onto the exploratory project and compare the international departures dataset with the data from the World Happiness Report. I decided to pursue a different path because I had already studied some aspects of that idea in Working with Data Fundamentals. 
I was reflecting on some past experiences during undergrad when I attended guided tours at the UN and City Hall in Lower Manhattan. During the City Hall tour, the tour guide emphasized the impact men had at City Hall and its history; therefore, I had asked her if there’s any historical presence of women… the answer is no, unsurprisingly. As such, I started searching datasets on gender in a government or women’s participation in society. I came across the art collection dataset from the Museum of Modern Art (MoMA)—only to learn that the dataset has already been explored by the Guerilla Girls in a similar capacity. Then after more searching, I came across the Gender Data Portal on World Bank that covers gender statistics on a wide-range of areas such as education, health, access to economic opportunities, etc.
Exploring the dataset, while the different areas covered would make an interesting analysis to aggregate with tourism data, there was just no time to explore them all. Therefore, I picked a couple of indicators that imply accessibility to travel for a woman:
A woman can apply for a passport in the same way as a man (SG.APL.PSPT.EQ)
A woman can choose where to live in the same way as a man (SG.LOC.LIVE.EQ)
A woman can open a bank account in the same way as a man (SG.OPN.BANK.EQ)
A woman can sign a contract in the same way as a man (SG.CNT.SIGN.EQ)
A woman can travel outside her home in the same way as a man (SG.HME.TRVL.EQ)
A woman can travel outside the country in the same way as a man (SG.CTR.TRVL.EQ)
Using those 6 indicators, I calculated a country’s Travel Indicator Score: the total number of Yes’s (or 1s) divided by 6. As such, a country can score the following numbers: 
0 – Women are not able to do any of the indicators on the list in the same way as a man
0.17 – Women can do any of 1 indicator on the list in the same way as a man
0.33 – Women can do any of 2 indicators on the list in the same way as a man
0.50 – Women can do any of 3 indicators on the list in the same way as a man
0.67 – Women can do any of 4 indicators on the list in the same way as a man
0.83 – Women can do any of 5 indicators on the list in the same way as a man
1 – Women can do all indicators on the list in the same way as a man
The World Bank dataset also included a country’s GDP, as such, this was also included in the analysis. This information was provided as a tooltip on a couple of charts for the audience to make their own conclusions. Originally, I had created my narrative prospectus on gender representation at the MoMA. The only ideas that have remained from that prospectus is a bar chart and gender. The prospectus for my exploratory project has remained the same. 
While developing the narrative project, based off the idea of a fellow student, I played around with a donut chart code to visualize the gender ratio of the world population. Prior to creating this chart, I did not know that the male to female ratio would almost be 50 to 50 (or rather 50.4 to 49.6). Thus, once the donut chart was created, I found the minimal difference between the genders rather difficult to visualize. Next, I chose to compare this chart with a vertical bar chart and successfully saw that minor difference. I was contemplating between which visual to choose, but chose the bar chart in the end to highlight the European countries that have predominantly more women—in contrast to the Middle Eastern countries where men are a majority in the population.
Additionally, I had difficulty with the categorical scatter plot. Since there are 127 countries that scored a 1 (100%) for their Travel Indicator Score, the data points are smooshed along the (1, x) plot line. I played around with the code to spread the data points out like a bubble chart. However, due to time restraints, I left this chart as is. In the future, I’d like to play around with the zoom function in D3, as I feel this would enhance the user experience of exploring this visual chart.
While this data provided some interesting insight, such as the small travel accessibility score for women across Africa and the Middle East, I think learning about the processes in place in these countries would be interesting. One such example is Philippines’s Travel Indicator Score of 0.83. My relatives from the country always boasted about the freedom of women in this country; therefore, I was surprised to see they didn’t receive a score of 1. The Philippines scored a 0 in a woman having the freedom to apply for a passport in the same way as a man. I spoke with my friend and she mentioned that single unmarried women have no problems applying for a passport; on the other hand, if they’re married they have to submit in documentation to prove their identity—while men do not have to do any of this. For personal enrichment, I may dig deeper and learn about the standard processes for women in retrospect to the 6 chosen. Overall, I definitely do see potential to building this project as the World Bank data set has over 150k data points to explore. 
On a side note, at the beginning of the semester, my first couple of tutorials (albeit they are not a part of this portfolio) are space-theme. I had originally wanted to pursue an astronomy-themed portfolio project, primarily due to my interest in NASA spinoffs and love for space in general. However, I found the dataset either difficult to work with or I was unfamiliar with APIs. So, one goal is to learn to work with APIs and pull data.
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