Data Summary

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✓ Published0🌍 Public

Last edited Dec 16, 2017

Created on Dec 16, 2017

This example displays a textual summary of a restaurant reservation dataset, aggregating records by source and status using Datalib’s `groupby` and `count` methods. After loading the CSV with `d3.csv`, the code computes row counts, format size, and column summaries, then renders the results in a `<pre>` element. Built with D3 v4 and Datalib, the visualization focuses purely on concise table statistics rather than graphical charts, drawing from the provided CCDC-November-NoPrivateData.csv file.

AI-generated description

This summarizes the data table using Datalib.

This data is from Data.gov: Consumer Complaint Database.

The data set has data about complaints sent to the Consumer Financial Protection Bureau about financial services. This data set was too big for the constraints of the assignment so it had to be modified. This set only includes January, Feburary and March of 2017 and does not have the narratives that consumer put with the complaint. The attributes in this data include the product, subproduct, issue and subissue of the complaint as well as company the complaint is about and the kind of response the company gave.

forked from <a href='http://bl.ocks.org/curran/'>curran</a>'s block: <a href='http://bl.ocks.org/curran/f849f374f21c490c5490d501636bdb77'>Data Table Summary</a>

forked from <a href='http://bl.ocks.org/emilyw15/'>emilyw15</a>'s block: <a href='http://bl.ocks.org/emilyw15/553e8acc8bccf2a4237a3e977e70568d'>CFPB Data Table Summary</a>

forked from <a href='http://bl.ocks.org/curran/'>curran</a>'s block: <a href='http://bl.ocks.org/curran/1c0af6a67f85d5c82bd7de421f9aaf13'>Aggregation with Datalib</a>

mit Licensed

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