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4 Comments
The name of every U.S. restaurant was pulled from OpenStreetMap, which is a crowdsourced dataset.
The data was transformed and cleaned in Pandas to exclude chain restaurants (like Red Lobster or Long John Silvers). The visualization was done with seaborn using a custom color palette matching the x-axis.
The match checks for whitespace or the end of the string, so partial matches are not included. E.g. “Red Restaurant” would be included under Red, but not “Sacred Cow Restaurant”.
Red Robin and Red Lobster doing some heavy lifting
Can we please rename the sub in r/isthisdatabeautiful and add a poll for every entry?
In this case, I suggest to reduce the repetitiveness of the coulourblind-friendly repetition of repeating each colour and its name. Have the top 5 big on the left, orange as last as well and the rest put in a list. Maybe also offer a stacked barplot of combined mentions. Then to go crazy, look up the states and see if it somehow matches the state* colours or the colours of the nation their food is from. Are there animals in the restaurant-title the colour matches?
There is a lot to play with in this dataset but little effort seems to go in there.
*does this exist?
[edit: remove unnecessary footnote]
[edit2: have the top x name repetitions in another visualization may be interesting as well]
Should specify that we’re talking the actual names of restaurants here
For a second I thought we were scraping menus and was very impressed lol. Still neat