ts-data-model

ts-data-model library

• Using the library
• Library documentation
  • Mapping
  • Data Adapters
    • dhis2Adapter
  • Data Transformations
    • Aggregators
    • Reducers
  • Mapping diagram

Using the library

To install the library in your project

    yarn add "ts-data-model"

To use the library in your react project

import { DataModel, fromDhis2 } from "ts-data-model"

const x = DataModel({ input: data, adapter: fromDhis2 })

Library Documentation

The ts-data-model libary consists of 4 major modules:

1. Data Adapters
2. Data Transformations
3. Data Formmaters
4. Utils functions

Mapping

Function	Function type	Functions used in implementation
fromDhis2	Data Adapter	findPosition, transpose, fromColumnDict
fromColumnDict	Data Adapter
fromArrayOfArrays	Data Adapter
toColumnDict	Data Formatter
toArrayOfArrays	Data Formatter
apply	Data Transformation
map	Data Transformation	addColumns, apply
agg	Data Transformation
join	Data Transformation	innerJoin, outerJoin
filter	Data Transformation	buildFilterFn, evaluateOr, evaluateAnd
addColumns	Data Transformation
fillNaN	Data Transformation	detectNaN
dropNaN	Data Transformation	detectNaN
selectColumns	Data Transformation
rename	Data Transformation
transpose	Utils
findPosition	Utils
innerJoin	Utils
outerJoin	Utils

Mapping diagram

Diagram

Data Adapters

Description: Data adapters are functions that convert output from different sources to the standard data model structure i.e. an array of objects

fromDhis2

Description: function to convert output from a dhis2 analytics query to the standard model structure i.e. an array of objects Example usage

import { DataModel } from "ts-data-model"
 const response = {
    headers: [
                { name: "dx", column: "Data", valueType: "TEXT", type: "java.lang.String", hidden: false, meta: true,},
                { name: "pe", column: "Period", valueType: "TEXT", type: "java.lang.String", hidden: false, meta: true,},
                { name: "ou", column: "Organisation unit", valueType: "TEXT", type: "java.lang.String", hidden: false, meta: true,},
                {name: "value", column: "Value", valueType: "NUMBER", type: "java.lang.Double", hidden: false, meta: false,},
                {name: "factor", column: "Factor", valueType: "NUMBER", type: "java.lang.Double", hidden: false, meta: false,},
                {name: "multiplier", column: "Multiplier", valueType: "NUMBER", type: "java.lang.Double", hidden: false, meta: false,},
                {name: "denominator", column: "Denominator", valueType: "NUMBER", type: "java.lang.Double", hidden: false, meta: false,},
                {name: "divisor", column: "Divisor", valueType: "NUMBER", type: "java.lang.Double", hidden: false, meta: false,},
              ]
    rows:
            [
               ['fbfJHSPpUQD', '202205', 'ARZ4y5i4reU', '18', '0', '0', '0', '0', '0'];
               ['fbfJHSPpUQD', '202201', 'YmmeuGbqOwR', '23', '0', '0', '0', '0', '0']
            ]
  }

const data = new DataModel({ input: response, adapter: fromDhis2 })

fromColumnDict

Description: You can create the data model object from a column dictionary using the fromColumnDict adapter Example usage

import { DataModel } from "ts-data-model"
const d2 = {
  "column 1": ["1", "2"],
  "column 2": ["3", "4"],
}

const data = new DataModel({ input: response, adapter: fromColumnDict })

Data Transformations

Description: functions that operate on a data model object, changing its columns or rows, but returning an object that keeps the structure of the data model. Transformations are categorizd into Aggregators, Selectors, Reducers, Mutators

Aggregators

Transformations implemented: agg
Example usage

import { agg } from "ts-data-model"

const aggregations = [
  ["age", "sum"],
  ["age", "mean"],
]

const result = data.agg({ groupBy: ["city", "gender"], aggregations })

Reducers

Transformations implemented: filter
Example usage:

import { filter } from "ts-data-model"

const filterCriteria = [
  "city",
  "=",
  ["London", "Paris"],
  "&&",
  "age",
  ">",
  30,
  "&&",
  "age",
  "<=",
  40,
]

const filteredData = data.filterData({ filterCriteria: filterCriteria })

Mutators

Transformations implemented: apply, fillNaN

apply

Example usage

const transformFn = (row) => {
  const bonus = row.salary * 0.1
  return { age: row.age * 2, salary: row.salary + bonus, name: row.name }
}

const transformedData = data.apply({ transformFn: transformFn })

fillNaN

Example usage

data.fillNaN()