Data Manifested, Numbers Analyzed
Ledger Analysis
The Ledgers accessed were presented in a way that made them both extremely easy to read, and analyze. All data was presorted with an ID number, a country of origin, port of origin, slaves taken on, and slaves that survived the journey. Also available was information about the boat itself, the ports docked at en route, and the sourcing to numerous manifests and ledgers used to cross reference the data. With all the information already analyzed and readily available, the real issue came with assembling all this data in one location that can further be analyzed so that visualizations can be made. With some assistance from Dr. Thomas, a webscrape was set up to analyze roughly 10,000 entries of the 36,000 available. Even though we only analyzed a third of the data, a trend can already be seen in the data.
The Process
After the webscrape, the data was collected and input into a fairly massive excel document. After cleaning up a few "unusable" entries via filter (ie no proven port of origination, no year of disembarkment, among other issues found with damaged documents) the data was ready to be analyzed in Tableau. The big issue came with ordering the data as individual entries. With each voyage number, Tableau would incorrectly read it as an amount of voyages, taking our roughly 10,000 entry strong document and making it into one over 40,000 strong.
The Result
While some visualizations were easily created in Tableau, and the map of exports already made for us, the true challenge came in using Tableau with little knowledge in order to create visually pleasing charts and graphs that effectively conveyed the findings of our data; Portugal was a major exported of slaves, to the point that it eclipsed every other exporter combined. A massive amount of slaves were sent to the newly formed colony of Brazil, while a sizeable portion of the exported Portuguese slaves went to America and the Caribbean.