ggplotly(box)ggplotly(p)The item price is probably in pounds, since the data comes from a restaurant in London. I’m more interested in prices relative to each other than the prices themselves.
This dataset is from https://www.kaggle.com/henslersoftware/19560-indian-takeaway-orders. The set used has ~74000 rows containing information about an Indian restaurant’s order history from 01-09-2015 to 12-07-2019.
Each row represents one order of one item. The columns included are order number, date ordered, item name, item price, quantity of item ordered, and total products in order.
omg, i love stackoverflow! stackoverflow is my life…
What ideas/suggestions from Claus Wilke helped shape your visualization?
Wilke’s scatterplot of birds’ bill length against their skull size– with color indicating the birds’ sex – gave me the idea to differentiate between meat/non-meat dishes with color. As a sometime vegetarian, I’m interested in comparing the price and popularity of these two groups!
Is there anything more you wish you could do with this data?
YES. I wish I could do cooler things with it.
I’m still a noob when it comes to graphics and visualizations. This source had data for a whole other restaurant, and I wish I could have compared the two venues somehow. I also wish I could have made my graph look cooler!
Also, I wish I knew what all the names of the dishes meant. I’m not super familiar with Indian food, so it’s entirely possible I missed some meat dishes because I didn’t know what words to look for.
AND FINALLY! I wish I could have gotten my tag_as_meat() function working. Because of time constraints, I ended up using repetitive code to check for each individual meat word. :’(
What were the most interesting or frustrating technical aspects of doing this?
The most interesting aspect was deciding which comparisons I wanted to make, and how I would represent them visually.
The most frustrating aspect was definitely wrangling the data. Writing an example row from the “end goal” dataset helped… but getting there took quite the struggle!