These are the six visualizations I am working on for this project. There is still much to work on in terms of making them prettier. I plan on playing with the color schemes a bit more as well as the titles. I also need to clean up some of the alias for some of the records. For the line graph, I need to figure out how to make the lines less scrunched up to the left-hand side of the chart. I tried excluding the later years, but that only resulted in the lines being even more squished. I’m going to keep fiddling with that one. The outlier is definitely what is messing it up – that year might have been an error in the records or a typo.
Here is the first draft of my StoryMap, Visualizing the Fur Trade. I included this to show the sequential order that I will present both my Tableau visualizations and the map layers I added from MapWarper. Here you can see I was able to figure out how to embed Tableau into StoryMap with some help from Google and the Esri community. This is the general layout I will be following, but note that there will be other images I will include from peer-reviewed sources I will be citing in my text blocks. I need to edit the maps by cropping them to the area that I want to highlight for this project. I’ll also want to improve the transitions between each visual so it seems less jumbled together and exhibits a flow that is easy to follow. This is what I’ll work on next week.
One reply on “10: Work”
Small copyediting things: the current preference in most venues right now is for capital I Indigenous and nation rather than tribe, unless referring to the specific current name of a political entity.
For the highest earners bar chart, you should make a pence total calculated field. Right now it’s hard to tell that pence, pounds, and shillings are all related and not three separate things like bear, beaver, and martin–calculating money in just terms of the total pence will make the comparison across difference people/nations more clear. You could also consider coloring your bars by nation or just leaving them a single color; right now having them colored by individual makes it hard to see any trends. I assume that this chart is all from Fonda, since as far as I recall that’s the only one that uses p.s.d; you may want to consult the conversion charts I did for my book, because one of the main difficulties with these long term comparisons of earnings is the use of different pelts/currencies over time. You don’t need to do the same conversions, but I flag it for your attention because the state of things for Fonda’s customers who were paying/being paid in cash or credit was different from those paying/being paid in corn or pelts, and that’s a significant question in the scholarly literature.
The box and whisker plot is great–make sure you spend some time talking through that. A bunch of your high outliers are Onondaga and Mohawk, when from the literature one might expect them to be Seneca or Laurentian/Canadian Mohawk, so that’s a pretty significant point to think about.
In your Traders Per Year line graph, have you tried just clicking the outlying point and selecting exclude to filter it out? That works for me, so I’m having trouble visualizing the issue you’re running into. Share a screenshot or write up some more details here or on Slack and we’ll try to get that figured out. Wendell does go to 1726, but it’s fine to filter out outliers as long as you note that.
For your Most Common Goods treemap, you should work with categories of goods rather than individual entries, which is what it looks like now. If there isn’t already a column for this in the anonymous Dutch acctbk, that’s small enough that you should be able to add a column and categorize things like rum; clothing; blanket; debt paid; multiple items, etc etc. Right now it looks like you’re just comparing the price for individual items, which doesn’t really say much. You could further break it down by nation as well as category of good, and see if there are trends in who’s spending what by nation.
Is the final trading by month chart a combination of accountbooks or is that all Fonda? The aliasing will be important for that one; eg, Oquaga is an Onondaga town and Schohary and Canajohary are Mohawk, etc. LMK if you need help tracking those down.
The StoryMap looks good so far; think about what maps you’re including and why. It’s not apparent to me right what the Morgan map does for your argument. Make sure that your maps aren’t only illustrative, and that each individual one relates to your argument somehow, otherwise we’re just seeing New York over and over again. For images, you might consider some of the objects from the Onöndowa’ga:’ collection. Those are fine to include with a link and citation.