17 Mar Mapping the WLZ Network #2: Using ‘R’
By Miranda Magee, Data Analyst Intern
This is the second in a series of three blogs where WLZ will discuss the work it is currently undertaking on network mapping. The first, on the theory behind network mapping, is available here. The final installment will present the Network Map itself.
When I joined West London Zone, I didn’t have much experience using R. Unlike Excel, R is a coding language, which means that there are so many more options as to what it can be used for and what it can create. It is open source and is constantly being developed by other users, causing it to be immensely powerful and useful. After reading online about whether R or Excel is better for data analysis, I found that others tend to favour R for its flexibility, amongst other reasons. R is incredibly beneficial for an organisation like West London Zone as it is completely free to use. West London Zone also uses R since it is able to cope with large amounts of data that are constantly being used and changed. It also allows for sophisticated data analysis in ways that may be constrained in Excel.
I started my own journey in R by learning basic data cleaning methods and then moving on to creating scatter plots and bar graphs. Gradually I worked my way towards producing reports and producing interactive web pages which incorporated these bar charts and scatter plots. Surprisingly, I found that it wasn’t too difficult to learn – once I understood the basics I found it very logical to follow. If I did have trouble on something, I had the guidance of the Senior Data Analyst to help me – and failing that there is a huge online community of R users who are ready and willing to answer questions and solve issues, particularly on Stackoverflow. My first question that I asked on Stackoverflow had a response within an hour – it was encouraging to know that others are so keen to help.
Having gained a more comprehensive understanding of R, I began creating the WLZ Network Map, putting my newly gained skills to the test. I initially used Excel to create a spreadsheet that contained all the data I had collected; however, network maps are something that Excel on its own couldn’t possibly produce so I then loaded this data into R. A benefit of R and it being open sourced is that there are plenty of options available to reach the same end goal. In this case, I tried out a few network mapping methods in R until I found the one that I felt worked best. I also found it hugely helpful that there were step by step examples by other users available online, this meant that I could create the map and then adapt it.
The final method I chose to use in the West London Zone network map was designed specifically to be interactive and uploaded to a website. Most importantly, the method is not complicated to follow so anyone working on the Network Map in the future shouldn’t have trouble editing it.
Check back here next week to see the final installment in this blog series, and the finished Network Map itself!