This visualization used PISA dataset, which assessed the extent to which 15-year-old students have acquired key knowledge and skills that are essential for full participation in modern societies. And I mainly explored the strength of relationship between math score and social-economic status. The countries are divided into 9 groups due to their math score and strength of relationship.
- story I want to tell:
- Different countries varied in math performance. And the influence of social-economic status to math performance was different in each country. Like, Peru and some Latin American countries had bad math performance and less equity compared with other countries.
- I tried to express the same idea as Figure II.1.2 on PISA 2012 Results: Excellence Through Equity: Giving Every Student the Chance to Succeed (Volume II), which was in the form of a scatterplot.
- chart type: I choose to use a choropleth map for the main part and I was inspired by the graphs in this article. Also, I added two barcharts to show exactly how students behaved and how strong the relationship was in each country. Further, a scatterplot to explain how the "equity" was calculated.
- visual encodings:
- choropleth map:
- map: showing geological information
- color: showing both math performance and variance explained by social-economic status
- barchart:
- bar width(x axis): showing the mean math score or the strength of the relationship in each country
- y axis: different countries
- scatterplot:
- x axis: the index of social-economic status
- y axis: the mean math score
- line: the regresssion line
- choropleth map:
- interaction: When hovering on one country, then relative information would pop up, including mean math score, strength of relationship between math score and social-economic status. People can also switch between the two barcharts.
- changes after collecting feedback：
- Add another barchart showing strength of the relationship. I also added buttons to allow users switch between these two barcharts easily.
- Add average line to barcharts.
- Add the barchart of strength of the relationship, since there were two dimensions on the map.
- Add average line to the barchart.
- Some colors in the color matrix are a little harder to distinguish.
- Can't get what the countries in white color mean? Actually, the survey only took in around 60-70 countries.
- inspiration, already linked
- some visualizations others made using this dataset
- pisa 2012 report about equity, I tried to express the same idea as Figure II.1.2 which was in the form of a scatterplot.
- how to calculate weighted average
- how to reshape data in python
- a simple way to zoom the map
- how to draw a grid in d3
- arrow head in d3
- for adding tooltips in d3, reference 1 and reference 2
- for drawing a scatterplot with a regression line, reference 1 and reference 2