Education is a very common topic in the world. I choose to visualize this topic from a specific perspective, which focuses on the female secondary education ratio in the world. Before I find data, my initial idea is to visualize the comparison ratio between female and males and find some insights into sexism from education data. However, when I download the data in the UN Data, I found that in this database file “Enrollment in primary, secondary and tertiary education levels“, most of sections are incomplete except the secondary education data. In order to finish a relatively persuasive and visible visualization work, I decided to narrow down to secondary education section and pay attention to the gross enrollment ratio of female education to find some insights.
- Use two new visualization tools that I just learned to enhance my proficiency with the tools.
- Build a readable, interactive, informative, aesthetic visualization page to display my topic.
This infographic (Figure 1) is the most mentionable inspiring example for me. I love its clarity and minimalism. Even it doesn’t display the shape of continents, we will recognize this is a world map. Also, the mechanic of this infographic is ingenious. There is a bar under the title, which is interactive. When people click or drag anyplace on the bar, the red number will change to the corresponding word and the dark areas on the map will change into the corresponding pattern.
However, this infographic also has limitations. For example, we cannot know the exact concise location on this map. Additionally, though the bar is interactive, the user will hard to know how to interact with it initially because the bar is too flat to look like be unclickable.
I think in my work, a map can help me present the relationship between location and education enrollment ratio, which is more directly and impactful to audiences. So this infographic hints me a form to present my data.
To build this visualization work, the first thing to do is finding a relative database to my topic. I previewed the data that I found in the UN Data and thought the categories and subtitles in this data chart are very suitable for my visualization. The preview format of the database is PDF, which is totally displayed for human’s reading habits but not for the machine. So if I download the CSV format from that website directly and use some software to read them, the data analysis software can not read the data correctly and transform them in a proper format.
For those reasons, I have to do the second step, which is refining the data. The tool I used to refine the data is OpenRefine, a free, open-source, powerful tool for working with messy data. I found that in the original database, lots of data such as elementary, secondary, tertiary data were combined together in one column and each of them was noted in another column, which is hard for me to extract one type of them and analyze that. By using open refine, I deleted irrelevant rows and columns and separated the 8different types of education data into 8 new columns. See screenshot in OpenRefine below:
The third step to make an information visualization work is to transform them into proper infographics. I used Tableau, a useful tool to help people see and understand their data. There are three parts that compose my final interactive visualization web page. The Bar chart on the top displayed the average (2001 to 2017) ratio of female’s secondary education in every country. The color green and red is in the same spectrum. The redder color means the lower ratio and the greener color means the higher ratios. I use these two colors
When a visitor hovers the bar, there will show the detail data of that country.
The second part of this work is this line chart. There are many lines in this a chart and each line stands for a country. From this chart, we can see the world female secondary education average ratio is higher and higher with time going by. We can also hover mouse on the line to see the value.
The third part of my work is this map chart, which geographically shows the distribution of female secondary education ratio. As we can see the red areas appear in Middle Africa and south west of Asia.
Additionally, by clicking one of the bars in the top bar chart, we can have two specific views of that country. We can simultaneously see the trend of education ratio and the geographic location of that country.
Although my visualization is relatively complete, there are still some limitations in my data and topic. For example, my data is just about the female education ratio, which cannot completely show the comparison with female’s and male’s ratios. Also, the design of that bar chart is too overwhelming so that some bars are too small to click.
I was still not completely satisfied with my database because there is much year information that is missing in many countries’ section, especially in Tertiary education ratio. Because of that, I have to choose Secondary Education as my final topic. Another data issue makes me confused is the ratios that are over 100. That’s why in my charts and graphics, you can see some value is over 100, though the spectrum’s scale is from 0 to 100.
All in all, this visualization can display education current situation in the world to some extent. But it still cannot reflect the real situation comprehensively and concisely. I will check the detail more carefully if I do data visualization work next time.