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Use this fake dataset to practice data exploration. Pizza Paradise was generated by the Observable team. Explore a variety of data visualization forms. Visualize pizza orders by day of week, see product trends over time, map revenue by location. Plot, facet, map, and more.

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Rather than hardcoding the column names, how can one specify column names through a variable? Let's say from a checkbox input for example.

Roy Francis

Sure! You could do something like have one cell like this:

columns = ['a', 'b', 'c', 'd']

And then the map would be:

myData.map(d => ({...columns.map(e => d[e])}) )

You could use checkbox input for the "columns" cell so its interactive. I can make a quick example if this doesnt make sense :)

Thanks! This was helpful. I would love to see a full realistic analysis workflow. For example; Read in a csv file, capture the column names as a variable, filter columns to keep, then select columns to filter by rows (categorical and numeric filtering) with input widgets and all that through variable without any hard coded values. ie; it should work with any random csv file.

You got it! This should accomplish what you're looking for https://observablehq.com/d/55dd0fe0f276ccfd

The function `d3.rollup` returns a Map, which does not allow for further reference to the elements, by their names. How to deal with that if I want to do some more grouping or other wrangling afterwards?

JuliaR

Good question! You can use d3.flatRollup or d3.rollups instead to return an array. Combined with map (as shown here: https://observablehq.com/@d3/d3-flatgroup#cell-54), this will get your grouped values back into a 2D array that you can continue with.