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Overview

JSONata is a powerful data query and transformation language designed for processing JSON data. It is used to preprocess, merge, and format data retrieved from APIs, allowing developers to perform complex calculations and data manipulations.

Key Features of JSONata

  1. Data Transformation: Modify and enhance JSON data by adding calculated fields.

  2. Merging Data: Combine information from multiple JSON data sources.

  3. Advanced Query Functions: Perform calculations using functions like map, filter, distinct, and sort.

  4. Debugging Support: Explore and debug the data processing context using debug tools.

  5. Data Visualization Integration: Use transformed JSON data to create dynamic visualizations.

Fetch data from an API endpoint

  1. Use a REST node to fetch data from an API endpoint. This example will generate data for 3 people.

Code Block
languagejson
{
  type: 'rest',
  uri: 'https://randomuser.me/api/?results=3',
  id: 'people',

  children: [
    {type: 'json'}
    ]
}

image-20241212-003020.pngImage Removedimage-20241212-003020.pngImage Added

  1. Determine the new data you want to calculate, such as the decade of birth based on the date of birth.

  2. Use JSONata functions to perform the necessary calculations. The map function is commonly used to iterate over each record in the results array.

  3. Store the calculated data in a new key within the original data structure. For example, add a "decade" key to each record in the results array.

  4. Perform additional calculations if needed, such as extracting distinct decades from the enriched data and sorting them. Store these values in separate keys, like decades.

This will generate a sorted list of the decades that these three people were born in. This example displays only two decades because two of the people generated in Step 1 were born in 1980.

Code Block
languagejson
{
  type: 'rest',
  uri: 'https://randomuser.me/api/?results=3',
  id: 'people',

  children: [
    {type: 'json'}
    ]
}

image-20241212-003439.pngImage Removedimage-20241212-003439.pngImage Added

Add a chart

  1. Add a chart node to the report.

  2. Define the chart's dimensions and appearance.

  3. Set the style of the chart's grid.

  4. Customize the axes' appearance.

  5. Populate the X-axis values using data from the report context, such as the decades key.

  6. Use JSONata functions to calculate the values for each data series in the chart. For example, calculate the number of male and female records per decade. Using the code below, the report displays a bar chart showing the number of males and females born in each decade.

Expand
titleJSON code that displays a bar chart showing the number of males and females born in each decade.
Code Block
languagejson
{
  type: 'rest',
  uri: 'https://randomuser.me/api/?results=300',
  id: 'people',
  path: '(\
    /* Calculate the decade of birth for each person */\
    $withDecades := $map($.results, function($p) { $merge([{ "decade": $substring($formatDate($p.dob.date), -4, 3) & "0" }, $p]) });\
    \
    /* Extract decades range */\
    $decades := $sort($distinct($map($withDecades, function($p) { $p.decade })));\
    \
    { "data": $withDecades, "decades": $decades }\
  )',
  children: [
    {
      type: 'json'
    },
    {
      type: 'chart',
      options: {
        chart: {
          width: 700,
          height: 400,
          
        },
        cartesianGrid: {
          stroke: "#eee",
          strokeDasharray:"5 5",
          vertical: false
        },
        xAxis: {
          axisLine: false,
          tickLine: false
        },
        yAxis: {
          axisLine: false,
          tickLine: false
        },
      },
      data: {
        categories: '$.decades',
        series: [
          {
            chartType: 'bar',
            name: 'Males',
            stackId: 'a',
            fill: '#82ca9d',
            data: '$map($.decades, function($d) {\
              $count(\
                $map(\
                  $filter(\
                    $filter($.data, function($p) { $p.gender = "male"}),\
                    function($p) { $d = $p.decade}),\
                  function($v) {$v.decade}))})',
          },
          {
            chartType: 'bar',
            name: 'Females',
            stackId: 'a',
            fill: '#8884d8',
            data: '$map($.decades, function($d) {\
              $count(\
                $map(\
                  $filter(\
                    $filter($.data, function($p) { $p.gender = "female"}),\
                    function($p) { $d = $p.decade}),\
                  function($v) {$v.decade}))})',
          },
        ],
      },
    },
  ]
}

image-20241212-004328.png

Debugging and Context Exploration


Enabling

Debug Mode

  1. Toggle debug mode Debug Mode to view additional buttons for inspecting the report context.

    image-20241212-004835.pngImage Added

  2. Right-click in the Report Description Editor and select Inspect to access the console.

  3. Explore the JSON context at various levels:

    • Root context: Contains global data sources and metadata.

    • Node context: Contains data specific to the current processing node.


Tips and Best Practices

  1. Start Small: Begin with simple queries to understand the structure of your data.

  2. Leverage Debug Mode: Use the debug tools to trace errors and verify transformations.

  3. Utilize Functions: JSONata provides a wide range of built-in functions for advanced data manipulation.

  4. Reuse and Optimize: Store reusable queries in variables to simplify and optimize transformations.


Common Functions in JSONata

Function

Description

Example

$map

Maps a function to each element in an array.

$map(data, $p -> $p.name)

$filter

Filters elements based on a condition.

$filter(data, $p -> $p.age > 20)

$merge

Merges objects into a single object.

$merge([$a, $b])

$distinct

Returns unique values from an array.

$distinct(data)

$sort

Sorts an array.

$sort(data)

$count

Counts elements in an array.

$count(data)