https://lifebringer.github.io/datavis/
he New York Public Library’s restaurant menu collection holds data about menus and dishes from 1840 to present. This is a crowdsourced dataset collected through spreadsheets and APIs. Since the data is crowdsourced and collected via various means, the data quality is very poor. The data contains errors due to limitations in quality achieved with Optical Character Recognition software. There are a wide variety of menus with various levels of readability.
The objective of this visualiztion is to apply various data cleaning and data visualiztion techniques to analyze the change in major ingredients represented by New York restaurant menus. Place close attention to how major categories change and think about the improvement of distribution through the ages.
Here we explore changes in the types of foods available in New York City. The data cleaning process reduced a major portion of the data available to concentrate on major ingredients.