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FiveThirtyEight reader responses to a food frequency questionnaire (FFQ).
npm install @stdlib/datasets-fivethirtyeight-ffq
Alternatively,
- To load the package in a website via a
script
tag without installation and bundlers, use the ES Module available on theesm
branch (see README). - If you are using Deno, visit the
deno
branch (see README for usage intructions). - For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the
umd
branch (see README). - To use as a general utility for the command line, install the corresponding CLI package globally.
The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.
To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
var dataset = require( '@stdlib/datasets-fivethirtyeight-ffq' );
Returns FiveThirtyEight reader responses to a food frequency questionnaire (FFQ).
var data = dataset();
// returns [ {...}, ... ]
var bifurcateBy = require( '@stdlib/utils-bifurcate-by' );
var inmap = require( '@stdlib/utils-inmap' );
var ttest2 = require( '@stdlib/stats-ttest2' );
var dataset = require( '@stdlib/datasets-fivethirtyeight-ffq' );
function predicate( v ) {
return ( v.diabetes === 1 );
}
function createAccessor( field ) {
return accessor;
function accessor( v ) {
return v[ field ];
}
}
// Retrieve the data:
var data = dataset();
// Split the data into two groups based on whether a respondent has diabetes:
var groups = bifurcateBy( data, predicate );
// For each group, extract the frequency of green salad consumption:
var mapFcn = createAccessor( 'greensaladfreq' );
var g1 = inmap( groups[ 0 ].slice(), mapFcn );
var g2 = inmap( groups[ 1 ].slice(), mapFcn );
// Perform a two-sample two-sided Student's t-test to determine if green salad consumption is different between the two groups:
var results = ttest2( g1, g2 );
console.log( results.print() );
To use as a general utility, install the CLI package globally
npm install -g @stdlib/datasets-fivethirtyeight-ffq-cli
Usage: fivethirtyeight-ffq [options]
Options:
-h, --help Print this message.
-V, --version Print the package version.
- Data is written to
stdout
as comma-separated values (CSV), where the first line is a header line.
$ fivethirtyeight-ffq
- Aschwanden, Christie. 2016. "You Can't Trust What You Read About Nutrition." https://fivethirtyeight.com/features/you-cant-trust-what-you-read-about-nutrition/.
The data files (databases) are licensed under an Open Data Commons Attribution 1.0 License and their contents are licensed under a Creative Commons Attribution 4.0 International Public License. The original dataset is attributed to FiveThirtyEight and can be found here. The software is licensed under Apache License, Version 2.0.
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
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