Extracting tables

When a document carries data in tables, you usually want that data as rows and columns rather than as rendered text. The structured result returns each table as a grid of cells, each cell placed by its row and column index and carrying any spans. This guide turns that grid into a structure your code can iterate.

Prerequisites

A completed parse job. See Parse your first document if you need one.
The structured result, fetched with get_structured_result, which is where the cell grid is exposed.

Find the tables

The structured result groups elements by page. Walk the pages and filter their elements by label to pull out the tables. Each table element holds a table object with its cell grid, its num_rows and num_cols counts, the page it sits on, and a confidence score.

from meibel import ParseLayoutLabel

result = client.documents.get_structured_result(job_id=job_id)

tables = [
    el for page in result.pages for el in page.elements if el.label == ParseLayoutLabel.TABLE
]
print(f"Found {len(tables)} tables")

const result = await client.documents.getStructuredResult(jobId);

const tables = result.pages
  .flatMap((page) => page.elements)
  .filter((el) => el.label === 'Table');
console.log(`Found ${tables.length} tables`);

Read cells into a grid

Each cell reports its row, its col, and its text. Because the grid dimensions are known from num_rows and num_cols, you can allocate a 2D array and place every cell at its coordinate. This gives you the table as nested lists, ready to write to a CSV, load into a dataframe, or compare against expected values.

def to_grid(table):
    grid = [["" for _ in range(table.num_cols)] for _ in range(table.num_rows)]
    for cell in table.cells:
        grid[cell.row][cell.col] = cell.text
    return grid

for element in tables:
    grid = to_grid(element.table)
    for row in grid:
        print(row)

function toGrid(table) {
  const grid = Array.from({ length: table.numRows }, () =>
    Array.from({ length: table.numCols }, () => ''),
  );
  for (const cell of table.cells) {
    grid[cell.row][cell.col] = cell.text;
  }
  return grid;
}

for (const element of tables) {
  const grid = toGrid(element.table);
  grid.forEach((row) => console.log(row));
}

Handle merged and spanning cells

Real tables sometimes merge cells, most often in headers. A cell that spans more than one column or row reports col_span or row_span greater than 1. The cell’s text belongs at its starting row and col; the positions it covers hold no separate cell of their own. To keep the grid rectangular, write the text across every position the cell spans.

def to_grid(table):
    grid = [["" for _ in range(table.num_cols)] for _ in range(table.num_rows)]
    for cell in table.cells:
        for r in range(cell.row, cell.row + cell.row_span):
            for c in range(cell.col, cell.col + cell.col_span):
                grid[r][c] = cell.text
    return grid

function toGrid(table) {
  const grid = Array.from({ length: table.numRows }, () =>
    Array.from({ length: table.numCols }, () => ''),
  );
  for (const cell of table.cells) {
    for (let r = cell.row; r < cell.row + cell.rowSpan; r++) {
      for (let c = cell.col; c < cell.col + cell.colSpan; c++) {
        grid[r][c] = cell.text;
      }
    }
  }
  return grid;
}

Each cell carries is_header, so you can separate header cells from data cells directly rather than assuming the first row. Group the header cells to build column names, and treat the rest as the body.

Check confidence before trusting a table

A table element carries a confidence score. Complex or scanned tables score lower than clean digital ones. When you extract tables at scale, gate on this score and route low-confidence tables to review rather than into a system of record.

Python

LOW = 0.7

for page in result.pages:
    for element in page.elements:
        if element.label == ParseLayoutLabel.TABLE and element.confidence < LOW:
            print(f"Low-confidence table on page {page.page_number}, flag for review")

Output schema

The full cell and table field definitions.

Confidence Scoring

How Meibel scores the quality of extracted content.

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Core concepts

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Data and documents

Operations

Document parsing reference

Support

Extracting tables

Prerequisites

Find the tables

Read cells into a grid

Handle merged and spanning cells

Check confidence before trusting a table

Output schema

Confidence Scoring

​Prerequisites

​Find the tables

​Read cells into a grid

​Handle merged and spanning cells

​Check confidence before trusting a table

​Related

Output schema

Confidence Scoring

Prerequisites

Find the tables

Read cells into a grid

Handle merged and spanning cells

Check confidence before trusting a table

Related