Reformats csv-like array-of-array with header row into a dataframe-like object in a transpose/pluck-like operation
npm i transpluck -S
None. Suitable for usage on nodejs or on the browser, via browserify.
const transpluck = require('transpluck');
transpluck(csvData) uses first row as header row, starts decoding at 2nd row, extracts everything
csvData = [
['a','b','c'],
[1, 2, 3],
[2, 7, 1],
[8, 5, 6]
];
seriesData = transpluck(csvData);
// {a: [1,2,8], b: [2,7,5], c: [3,1,6] }
transpluck(csvData, {pluck: ['b']}) returns only the plucked columns, using csvData[0] as the header row.
The pluck property must be an array, and should consist of a subset of the column names from the 0th row of the data.
Missing items will be ignored, and will not appear as keys in the result.
--> {b: [2,7,5]}
transpluck(csvData, ['x','y','z']) uses the explicit header ['x','y','z'], treats all rows of csvData as data
--> {x: ['a',1,2,8], y: ['b',2,7,5], z: ['c',3,1,6]}
If an explicit header is supplied, a starting row index can also be supplied:
transpluck(csvData, ['x','y','z'], 1)
--> {x: [1,2,8], y: [2,7,5], z: [3,1,6] }
Any explicitly undefined header slots are omitted in the returned object:
transpluck(csvData, ['a',,'c'], 1)
--> {a: [1,2,8], c: [3,1,6]}
You may use an object as the second parameter to request a sparse set of columns. The sparse header object format is {colNumber: 'label', colNumber2: 'label2', ...}.
`transpluck(csvData, {1:'bb'}, 1)
--> {bb: [2,7,5]}
Remember that any header row in the csvData array-of-arrays is ignored when an explicit header is used:
transpluck(csvData, ['a','c'], 1)
--> {a: [1,2,8], c: [2,7,5] } not c:[3,1,6] because explicit header ['a','c'] means collect column 0 in property a, and column 1 in property c.
Ill-formed calls return undefined
transpluck() === undefined
transpluck([1,2,3,4,5,6]) === undefined
transpluck({}) === undefined
Use mocha framework.
Copyright 2016 Paul Brewer, Economic and Financial Technology Consulting LLC
MIT