node-data-preprocessing

node-data-preprocessing

A node package for data preprocessing.

The package exposes the individual steps, as well as one to the entire process.

Individual Steps

csvParser

var data = process.csvParser(options);

options

List of options with defaults -

var options = {
    path: ''
};

path

String - The path to the data.

extract

var extracted = process.extract(options, data);

options

List of options with defaults -

var options = {
    useHeaders: 'true'
};

useHeaders

Boolean - Indicates whether the first row of data is the heading or not. Note - The heading will not be used in the process. Setting it to true simply strips the first row from the data.

cleanse

var cleansed = process.cleanse(options, data);

options

List of options with defaults -

var options = {
    formats: [],
    ranges: []
};

formats

Array - of strings representing the formats that the fields should be. The string should match the result of typeof() applied to the expected data format.

ranges

Array - of objects, such that { 'validatorName': 'validatorValue' }.

validators

Available validators -

• greater - expects value, min, returns value > min;
• greaterOrEqual - expects value, min, returns value >= min;
• less - expects value, max, returns value > max;
• lessOrEqual - expects value, max, returns value > max;
• between - expects value, range, where range is a string such that 'min-max', and returns greater(value, min) && less(value, max);
• betweenOrEqual - expects value, range, where range is a string such that 'min-max', and returns greaterOrEqual(value, min) && lessOrEqual(value, max);

standardise

var standardised = process.standardise(options, data);

options

List of options with defaults -

var options = {
    min: 0.1,
    max: 0.9,
    standardisationMethod: 'default'
};

min

number - The minimum value for the standardisation.

max

number - The maximum value for the standardisation.

standardisationMethod

string - Can be default, normal or ss (Sum of Squares).

ignore

Array - of integers representing columns of the data to ignore while standardising. They will retain their non-standardised values.

divide

var divided = process.divide(options, data);

options

List of options with defaults -

var options = {
    split: [60, 20, 20]
};

split

Array - Indicates how many subsets the data should be split into, and with what weighting.

process (combined)

var result = process.process(options);

options

The combined proces takes all the options that the individual steps take, in one object.

var options = {
    path: '',
    useHeaders: true,
    formats: [],
    min: 0.1,
    max: 0.9,
    standardisationMethod: 'default',
    split: [60, 20, 20]
};