Today is the first post of 2022, and the first post of DSAU17’s dashboard week.

Dashboard week requires us to create a dashboard per day on various data sets, and then write a blog post about the dashboard and data set.

Today’s challenge was working with TheMealDB. You can find more about it here –

Data Wrangling

The first challenge when working with an API is to extract the data required. I chose to do this in Alteryx, and make use of the JSON Parse tool to reduce my workload.

I first connected to the Category endpoint to get a list of categories.

These categories were then used to get a list of all recipes offered by the API through the filter endpoint.

I was finally able to use this information to lookup all Meal ID endpoints, before cleaning up field names and pivoting the data.

This concluded the preparation of the data, and the beginning of the dashboard.

Creating the Dashboard

My first thought was to simply create a recipe dashboard, and that’s what I ran with. First I began by making some sheets to use as filters.

I used some broad fields, to then narrow down our selections. I picked categories & cuisine area as our initial filters.

These filters were then applied to a sheet of meals, which we used as a preview that we could decide on.

From there, we would be able to either go to the source recipe, a youtube video or read the recipe in the workbook. The final view looked like this.

While a sloppy dashboard, it serves its purpose as a one day dash

board. I’ll keep you updated with tomorrow’s blog!

The Data School
Author: The Data School