Observable

Allison Horst

Paul Buffa

Collection of notebooks related to data science in Observable

Data Science in Observable

Data Analysis

Workflow Resources

Examples of how Data Scientists are using Observable

Data Science 

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.

index-array.png

Purpose-built for displays of data