Udacity Data Visualisation Nanodegree Capstone Project
A few months ago, I enrolled in my third nanodegree on Udacity: Data Visualisation
After several projects, I came to the capstone project and that’s why I’m writing this story.
My last task to obtain my certification is to write a blog to describe how you would improve an existing visualisation from MakeoverMonday.
I choose one of the latest challenge and specifically: Viz5: Perceived Obstacles to Gender Equality
So, here we go :)
The context
On January 28, 2021, Focus 2030 and Women Deliver unveiled the findings of Citizens Call for a Gender-Equal World: A Roadmap for Action, a first-of-its-kind international survey on public perceptions of gender equality.
The report represents a “first-of-its-kind global survey,” and is based on data and results collected from a multi-national survey of 17,160 adults — a sample of approximately 1,000 people for each of the 17 countries highlighted in the report.
One of the question of this survey was:
Thinking about the list of reasons below, which, if any, do you personally think are the main reasons why women may not be equal to men in your country? (Please tick up to three from the options below):
- Because women and men are not equally represented in politics
- Because of religion and culture that do not treat women and men as equals
- Because boys and girls are treated differently growing up
- Because women and men have different employment opportunities
- Because unpaid care, domestic work, and parental responsibilities are not shared equally between women and men
- Because women and men cannot exercise the same level of control over their bodies
- Because crises have unequal effects on women and men
- Because men tend to be physically stronger than women
- Because girls do not receive the same access to education as boys
Here is the original visualisation of the results of the survey
The goal
The goal of our visualisation is answering some questions.
- What is the main reason perceived for gender gap?
- How a specific answer differs across the globe?
- What is the most common answer for each country? Is there any difference between respondent gender?
Looking at the original visualisation, data are there and is still possible to give an answer. But is the visualisation built in the most effective way to provide quick answers?
Is it possible to improve it using Tableau and including also interactive capabilities?
First question
First question that we would like to answer is:
- What is the main reason perceived for gender gap?
It is not easily possible to answer to this question from the data shown in the original visualisation. I cannot easily ‘order’ the reasons based on their overall score.
For this reason I built a different chart with the ordered average response across all countries split by gender.
From there is quite clear that the first reason for gender gap is: Unpaid care, domestic work, and parental responsibilities are not shared equally between women and men
It is also quite evident that women was choosing this answer more than men.
Men also look more undecided as they answered more often “None of these” or “Don’t know”
Hovering the mouse over an answer will show the overall percentage and the male and female percentage.
Second question
The second question that we would like to answer is:
- How a specific answer differs across the globe?
To answer this question but keeping the clutter as low as possible, I built an interactive graph linked to the previous one.
Selecting any of the reason, it will be possible to see how the question was answered in the different countries and between the respondent gender.
I find this chart more immediate than the heat map in the original visualisation because it makes much clearer.
Third question
Finally we want to answer the question:
- What is the most common answer for each country? Is there any difference between respondent gender?
This visualisation is similar to the original one as it looks a good way to spot the differences between countries and gender.
Conclusions
In this blog post, I discussed how I tried to improve the original visualisation in order to more easily convey the information.
This is how the final visualisation looks like:
The new view takes advantage of the interactivity of the dashboard allowing to provide precise data but at the same time not to be too chaotic.
It was fun to learn new tips and tricks to be used in Tableau to have a better looking dashboard. Some of the things that I learnt :
- how to built a butterfly chart
- how to lock section using an empty transparent box to avoid interaction
- how to link charts together to use one as a navigation map
- …and more :)
If you want to compare the two visualisation you can find them in the following links:
Original visualisation: https://data.world/makeovermonday/2021w6/workspace/project-summary?agentid=makeovermonday&datasetid=2021w6
New visualisation:
https://public.tableau.com/profile/buposki#!/vizhome/PerceivedObstaclestoGenderEquality_16139980323880/Dashboard1
