Author: Alden Denny*
*Alden won second place in the Tableau data visualization challenge. We are very proud at strictlyfishwrap. ~ The Management
Not a country usually looked at on this ever so nautical blog. I am doing so as part of a Tableau data visualization challenge. This program is largely focused on the business world, but I believe it has cross-application to all sorts of data visualization challenges that we face in the marine field. Enough though about the software – it’s the data that really matters.
Lesotho is a landlocked country with a surprisingly high literacy rate (85%), but a low life expectancy of 51 years and a GDP per capita of $1,400 and is dominantly an agrarian society. The challenge is to explore a dataset collected by CARE, a Village Saving and Loan Association (VSLA) program, and to give them a solid understanding of the people they are trying to serve. This dataset is quite large, and also heavily weighted towards survey questions which pose a unique challenge in visualizing.
To explore this data I decided to focus on two ideas – household choices made at the village level, and economic resources at the district level. To quickly explore the data I grouped together the districts based on the number of households that are married and unmarried:
Household size can here by used as a proxy for the health of a community – the Mokhotlong district has large, married and what I see as healthy households. This image quickly shows the basic trends of Lesotho by district. Mokhotlong is the populous and rich district, Quthing is a distant second, and Qachas’nek is dramatically far behind.
Now to look in more detail at families and family structures I decided that the village level was a great place to look. Here we can explore financial decisions and domestic abuse in each of the villages visited in this survey.
The answers to these questions strongly correlates to the financial success of the families – in situations where the wife is safe and in financial control of the household the entire household is much better off.
These however are all societal indicators – crucial factors to any population but an incomplete story. To understand the population and their economic situation it is useful to explore their assets. Below I have made an attempt to do just that – this is an interactive exploration of resources based on gender and district. I encourage you to spend some time working with this figure – it shows a lot of information.
Of note in this figure – Lesotho is obviously an agrarian society, but the distribution of resources is far from uniform across the districts and genders. For example, while men tend to own a great many chickens, the chicken resale value is quite low. Conversely women own more goats and cattle with a much higher resale value. This is only a window into the Lesotho society – but I do hope what I’ve shown here is illuminating.