PHP Unflatten Dot Notation Array

unflatten.php

<?

$results = [
  'id' => 'abc123',
  'address.id' => 'def456',
  'address.coordinates.lat' => '12.345',
  'address.coordinates.lng' => '67.89',
  'address.coordinates.geo.accurate' => true,
];

function unflatten($data) {
  $output = [];
  foreach ($data as $key => $value) {
    $parts = explode('.', $key);
    $nested = &$output;
    while (count($parts) > 1) {
      $nested = &$nested[array_shift($parts)];
      if (!is_array($nested)) $nested = [];
    }
    $nested[array_shift($parts)] = $value;
  }
  return $output;
}

echo json_encode(unflatten($results));

/*
{
  "id": "abc123",
  "address": {
    "id": "def456",
    "coordinates": {
      "lat": "12.345",
      "lng": "67.89",
      "geo": {
        "accurate": true
      }
    }
  }
}
*/

I took the liberty of building on this and expanding it to a function that can handle duplication of values when joined data is pulled from a database:

<?php

/**
 * Normalise a flat dot notation array.
 *
 * @param array  $rows The flat array
 * @param string $dot The character that separates the layers.
 *
 * @return array
 */
function unflatten(array $rows, string $dot = "."): array
{
	# The last row's main table columns
	$last_main_table = [];

	# A collection of all the joined tables belonging to a given row of the main table
	$joined_tables = [];

	# For each row in the result set
	foreach($rows as $id => $row){

		# Contains this row's main table columns
		$main_table = [];

		# Contains this row's joined table columns
		$joined_table = [];

		# Foreach column and value
		foreach($row as $col => $val){

			/**
			 * Whether a column name contains a period or not
			 * is the determining factor of whether the column
			 * belongs to the main table (no period) or a joined
			 * table (periods).
			 */
			if(!strpos($col, $dot)){
				//if the column belongs to the main table
				$main_table[$col] = $val;

			} else {
				//If the column belongs to a joined table

				# Break open the column name
				$col = explode($dot,$col);

				# Extract out the joined table, and the column names (that may include joined children)
				$joined_table[array_shift($col)][$id][implode($dot,$col)] = $val;
			}
		}

		# If this is the first row, or if this row's main columns are the same as the last row
		if(!$last_main_table || ($main_table == $last_main_table)){

			# Update the last main table variable
			$last_main_table = $main_table;

			# merge all rows of columns belonging to joined tables
			$joined_tables = array_merge_recursive($joined_tables ?:[], $joined_table ?:[]);

			# Go to the next row
			continue;
		}

		# At this point, the main columns are different from the previous row's main columns

		# Add the last row's main columns, merged with all of it's joined table rows to the normalised array
		$normalised[] = array_merge($last_main_table, $joined_tables);

		# Update the last main table variable
		$last_main_table = $main_table;

		# Reset the joined tables
		$joined_tables = [];

		# Add this row's joined table columns
		$joined_tables = array_merge_recursive($joined_tables ?:[], $joined_table ?:[]);
	}

	# Capture the last row
	$normalised[] = array_merge($last_main_table, $joined_tables);

	# Go deeper
	foreach($normalised as $id => $row){
		//For each row that is now normalised
		foreach($row as $key => $val){
			//For each column value
			if(is_array($val)){
				//if any of the values are arrays, make sure that array is also normalised
				$normalised[$id][$key] = unflatten($val, $dot);
			}
		}
	}

	return $normalised;
}

$results[] = [
  'id' => 'A1',
  'address.id' => '11f456A1',
  'address.coordinates.lat' => '12.345',
  'address.coordinates.lng' => '67.89',
  'address.coordinates.geo.accurate' => true,
];
$results[] = [
  'id' => 'A1',
  'address.id' => '22f456A1',
  'address.coordinates.lat' => '12.345',
  'address.coordinates.lng' => '67.89',
  'address.coordinates.geo.accurate' => true,
];
$results[] = [
  'id' => 'A2',
  'address.id' => '44f456A2',
  'address.coordinates.lat' => '11.345',
  'address.coordinates.lng' => '67.89',
  'address.coordinates.geo.accurate' => true,
];
$results[] = [
  'id' => 'A2',
  'address.id' => '44f456A2',
  'address.coordinates.lat' => '22.345',
  'address.coordinates.lng' => '67.89',
  'address.coordinates.geo.accurate' => true,
];

$normalised = unflatten($results);
var_dump($normalised);

Produces

array (
  0 => 
  array (
    'id' => 'A1',
    'address' => 
    array (
      0 => 
      array (
        'id' => '11f456A1',
        'coordinates' => 
        array (
          0 => 
          array (
            'lat' => '12.345',
            'lng' => '67.89',
            'geo' => 
            array (
              0 => 
              array (
                'accurate' => true,
              ),
            ),
          ),
        ),
      ),
      1 => 
      array (
        'id' => '22f456A1',
        'coordinates' => 
        array (
          0 => 
          array (
            'lat' => '12.345',
            'lng' => '67.89',
            'geo' => 
            array (
              0 => 
              array (
                'accurate' => true,
              ),
            ),
          ),
        ),
      ),
    ),
  ),
  1 => 
  array (
    'id' => 'A2',
    'address' => 
    array (
      0 => 
      array (
        'id' => '44f456A2',
        'coordinates' => 
        array (
          0 => 
          array (
            'lat' => '11.345',
            'lng' => '67.89',
            'geo' => 
            array (
              0 => 
              array (
                'accurate' => true,
              ),
            ),
          ),
          1 => 
          array (
            'lat' => '22.345',
            'lng' => '67.89',
            'geo' => 
            array (
              0 => 
              array (
                'accurate' => true,
              ),
            ),
          ),
        ),
      ),
    ),
  ),
)

Sandbox: https://3v4l.org/P4RVZ