Data Slicer

An in memory data transformer and aggregator to give summary counts for small to medium size datasets.

API

Create an give your Slicer some Data

var DataSlicer = require('data-slicer');
 
var ds = DataSlicer().setData([
  {
    type: 'firstType',
    a: '0',
    b: 1,
    c: '0.5'
  },
  {
    type: 'firstType',
    a: 0,
    b: 8,
    c: '0.25'
  },
  {
    type: 'secondType',
    a: 0,
    b: 9,
    c: '0.0'
  }
]);

DataSlicer does not know much about the data that you pass through it, other than the fieldnames that you give it at each stage.

Transforms

Methods:

• transform
• modify

Getting good information out of your data normally takes a few stages, first you need to clean the data. To assist with this, DataSlicer has two methods, transform and modify. Continuing with our example above, we can see that the first case of a is a String, when really want integers.

Transform(fieldName, transformValue)

fieldName: (string) - key to transform on each record transformValue: (function | string) - function or key to pre defined transform function.

TransformValue String values:

lowercase
parseFloat
parseInt

Example:

ds.transform('a', 'parseInt')
  .transform('c', 'parseFloat')
  .modify(); // data is modified

No transforms will be applied until you call .modify()

Custom Transforms

If you do not use one of the preset transform functions, you can supply custom functions.

These functions are passed two arguments, record and field. You are expected to reassign the field to the record if it's appropriate to change the record.

example of turning 0's into 'zilch's:

ds.transform('a', function(record, field) { 
  if (record[field] === 0) {
    record[field] = 'zilch';
  }
});

Totals

The Totals API allows you to get general information about the combination of a set of records.

Methods:

• uniqueBy(field)
• sortBy(totalType)
• total(field)
• min(field)
• max(field)
• count(field)
• mean(field)
• customTotals(field, definition)

input: To answer the question: For each unique type, what are the total (added) values of a:

ds.totals()
  .uniqueBy('type')
  .total('a')
  .process() // must be called to process the data

output:

{
  "type": {
    "firstType": {
      "aggs": {
        "total": 0
      }
    },
    "secondType": {
      "aggs": {
        "total": 0
      }
    }
  }
}

UniqueBy

This chooses a specific field to gather additional nested data on. UniqueBy's can be nested as many times as desired.

input: For each unique type, what are the totals of a, and for each unique secondaryType what are the totals, mean, min and max values of a?

ds.totals()
  .uniqueBy('type') // first level of nesting
  .total('a')
  .uniqueBy('secondaryType') // second level of nesting
  .total('a')
  .mean('a')
  .min('a')
  .max('a')
  .process();

output:

{
  "type": {
    "firstType": {
      "aggs": {
        "total": 0
      },
      "type": {
        "firstType": {
          "aggs": {
            "total": 0
          },
          "secondaryType": {
            "food": {
              "aggs": {
                "total": 0,
                "average": 0,
                "min": 0,
                "max": 0
              }
            },
            "beverage": {
              "aggs": {
                "total": 0,
                "average": 0,
                "min": 0,
                "max": 0
              }
            }
          }
        }
      }
    },
    "secondType": {
      "aggs": {
        "total": 10
      },
      "type": {
        "secondType": {
          "aggs": {
            "total": 10
          },
          "secondaryType": {
            "food": {
              "aggs": {
                "total": 10,
                "average": 10,
                "min": 10,
                "max": 10
              }
            }
          }
        }
      }
    }
  }
}

SortBy

Note that until now, all data returned has been stored in an object. Applying a sort changes the values of the aggregation objects to arrays. The object gets an additional key added named key, that stores the original key value of the object.

example: input:

  ds.totals()
    .uniqueBy('type')
    .total('a')
    .sortBy('total')
    .process();

output:

{
  "type": [
    {
      "aggs": {
        "total": 10
      },
      "key": "secondType"
    },
    {
      "aggs": {
        "total": 0
      },
      "key": "firstType"
    }
  ]
}

Custom totals / Totals Definitions

todo