Reshape Wide To Long

Overview

You send a rectangular table, id columns, and either valueColumns or a RE2 valueColumnPattern. We emit one row per source row and value column, in that order, with nameColumn and valueColumn you name. dropNullValues is false unless you opt in. The 100,000-row ceiling is checked before allocation. This is not a pivot, and it does not use a backtracking regex engine.

Unpivoting in hash-map order, or allocating a 100,001-row result then failing, is how a reshape becomes non-deterministic and unbounded. Selection order and the ceiling are checked first.

When to use it

Scope

Non-goals

• Does not aggregate or pivot
• Does not use a backtracking regex engine
• Does not group by semantics beyond the listed columns

Properties

Capabilities

Cost & billing

Flat rate per invocation

File handling

How we handle your data

Input schema

Output schema

API contract

curl -sS -X POST "$BASE/v1/execute" -H "Authorization: Bearer $KEY" -H 'Content-Type: application/json' -d '{"skillKey":"data.reshape_wide_to_long","input":{"table":{"columns":[{"name":"id","type":"STRING"},{"name":"m1","type":"INTEGER"}],"rows":[["a",1]]},"idColumns":["id"],"valueColumns":["m1"],"nameColumn":"metric","valueColumn":"amount"}}'

import { Squillify } from "@squillify/sdk";

const sq = new Squillify({ apiKey: process.env.SQUILLIFY_API_KEY });

const { output } = await sq.execute("data.reshape_wide_to_long", {"idColumns":["id"],"valueColumns":["m1","m2"],"nameColumn":"metric","valueColumn":"amount","table":{"rows":[["a",1,2]],"columns":[{"type":"STRING","name":"id"},{"type":"INTEGER","name":"m1"},{"type":"INTEGER","name":"m2"}]}});

Errors

Other limits

Limitations

• Does not aggregate or pivot
• Does not use a backtracking regex engine
• Does not group by semantics beyond the listed columns
• Pivoting long data back to wide
• PCRE backtracking patterns

How to call

POST /v1/execute (requires authentication)

{
  "skillKey": "data.reshape_wide_to_long",
  "input": {
    "idColumns": [
      "id"
    ],
    "valueColumns": [
      "m1",
      "m2"
    ],
    "nameColumn": "metric",
    "valueColumn": "amount",
    "table": {
      "rows": [
        [
          "a",
          1,
          2
        ]
      ],
      "columns": [
        {
          "type": "STRING",
          "name": "id"
        },
        {
          "type": "INTEGER",
          "name": "m1"
        },
        {
          "type": "INTEGER",
          "name": "m2"
        }
      ]
    }
  }
}

Examples

{
  "idColumns": [
    "id"
  ],
  "valueColumns": [
    "m1",
    "m2"
  ],
  "nameColumn": "metric",
  "valueColumn": "amount",
  "table": {
    "rows": [
      [
        "a",
        1,
        2
      ]
    ],
    "columns": [
      {
        "type": "STRING",
        "name": "id"
      },
      {
        "type": "INTEGER",
        "name": "m1"
      },
      {
        "type": "INTEGER",
        "name": "m2"
      }
    ]
  }
}

{
  "columns": [
    {
      "type": "STRING",
      "name": "id"
    },
    {
      "type": "STRING",
      "name": "metric"
    },
    {
      "type": "INTEGER",
      "name": "amount"
    }
  ],
  "rowCount": 2,
  "rows": [
    [
      "a",
      "m1",
      1
    ],
    [
      "a",
      "m2",
      2
    ]
  ],
  "columnCount": 3
}

{
  "idColumns": [
    "id"
  ],
  "nameColumn": "metric",
  "valueColumn": "amount",
  "table": {
    "rows": [
      [
        "a",
        2,
        1
      ]
    ],
    "columns": [
      {
        "type": "STRING",
        "name": "id"
      },
      {
        "type": "INTEGER",
        "name": "m2"
      },
      {
        "type": "INTEGER",
        "name": "m1"
      }
    ]
  },
  "valueColumnPattern": "^m"
}

{
  "columns": [
    {
      "type": "STRING",
      "name": "id"
    },
    {
      "type": "STRING",
      "name": "metric"
    },
    {
      "type": "INTEGER",
      "name": "amount"
    }
  ],
  "rowCount": 2,
  "rows": [
    [
      "a",
      "m2",
      2
    ],
    [
      "a",
      "m1",
      1
    ]
  ],
  "columnCount": 3
}

Recommended use cases

• Turn month_1, month_2 measure columns into month/value rows
• Select measure columns with a RE2 prefix in original order

Avoid for

• Pivoting long data back to wide
• PCRE backtracking patterns

Related skills

Composable with

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