> ## Documentation Index
> Fetch the complete documentation index at: https://docs.runpulse.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Meridian — Tables to Excel

> Convert extracted tables into formatted .xlsx Excel workbooks, directly from the Playground or via the API.

## Overview

**Meridian** is Pulse's built-in table-to-Excel conversion engine. After extracting a document, any tables detected by Pulse can be exported as a formatted `.xlsx` workbook — ready for downstream analysis, reporting, or integration.

```mermaid theme={null}
flowchart LR
    A["/extract"] --> B[Bounding Boxes + Tables]
    B --> C[Meridian]
    C --> D[".xlsx Workbook"]
```

***

## When to Use

* **Financial data** — export income statements, balance sheets, or transaction tables to Excel
* **Invoices** — convert line item tables to spreadsheets for accounting systems
* **Research data** — pull experimental results or survey tables into a workable format
* **Any document with tables** — if Pulse detects tables in the extraction, you can export them

***

## How to Use in the Playground

<Steps>
  ### Extract a document

  Upload and extract your document using any pipeline — [Extract](/platform-reference/extract), [Extract → Schema](/platform-reference/extract-schema), or [Extract → Split → Schema](/platform-reference/extract-split-schema).

  ### Navigate to the Tables tab

  After extraction, switch to the **Tables** tab to see all detected tables rendered in a grid view.

  ### Click "Export to Excel"

  Click the **Export** button (spreadsheet icon) in the extraction results toolbar. This opens the Meridian export flow.

  ### Select tables and configure

  In the export view, you can:

  * **Select/deselect tables** — choose which tables to include
  * **Rename sheets** — customize the Excel sheet name for each table
  * **Choose export mode** — separate workbooks per document, combined into one, or appended to an existing workbook

  ### Configure formatting

  Set Excel formatting preferences:

  | Setting                       | Options                               |
  | ----------------------------- | ------------------------------------- |
  | **Font family**               | Arial, Calibri, Times New Roman, etc. |
  | **Font size**                 | 8–16pt                                |
  | **Font color**                | Any hex color                         |
  | **Alignment**                 | Left, Center, Right                   |
  | **Bold / Italic / Underline** | Toggle each                           |
  | **Column width**              | Auto or fixed                         |
  | **Row height**                | Auto or fixed                         |

  ### Export

  Click **Export All**. The workbook is generated and downloaded to your browser as a `.xlsx` file.
</Steps>

***

## Export Modes

| Mode         | Description                                                                                                                                         |
| ------------ | --------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Separate** | One `.xlsx` file per document. Each table gets its own sheet within the workbook.                                                                   |
| **Combined** | All tables from all documents merged into a single `.xlsx` file. Each table gets its own sheet.                                                     |
| **Appended** | Tables are added to an existing `.xlsx` workbook you upload. You can append to an existing sheet (vertically or horizontally) or create new sheets. |

***

## Appending to Existing Workbooks

The **Appended** mode is uniquely powerful — upload an existing Excel file and Meridian will add the newly extracted tables to it:

* **Vertical append** — new rows added below existing data in a target sheet
* **Horizontal append** — new columns added to the right of existing data
* **New tab** — each table becomes a new sheet in the existing workbook

Options for vertical append:

* **Include unmatched columns** — add columns from the new table that don't exist in the target
* **Add identifier column** — insert a column to tag rows by their source document

***

## API Usage

The Meridian conversion is available via the `/meridian-convert` endpoint:

<Tabs>
  <Tab title="Python">
    ```python theme={null}
    import requests

    # After extraction, you have bounding_boxes with table data
    tables = [
        {
            "name": "Income Statement",
            "rows": 5,
            "columns": 3,
            "page": 1,
            "cells": [
                {"rowIndex": 0, "columnIndex": 0, "content": "Category"},
                {"rowIndex": 0, "columnIndex": 1, "content": "Q1"},
                {"rowIndex": 0, "columnIndex": 2, "content": "Q2"},
                {"rowIndex": 1, "columnIndex": 0, "content": "Revenue"},
                {"rowIndex": 1, "columnIndex": 1, "content": "1200000"},
                {"rowIndex": 1, "columnIndex": 2, "content": "1350000"}
            ],
            "customSheetName": "Income Statement"
        }
    ]

    response = requests.post(
        "https://api.runpulse.com/meridian-convert",
        headers={"x-api-key": "YOUR_API_KEY"},
        json={
            "tables": tables,
            "filename": "financial_tables.xlsx",
            "formatSettings": {
                "fontFamily": "Calibri",
                "fontSize": 11,
                "alignment": "left"
            }
        }
    )

    # Response contains a presigned download URL
    download_url = response.json()["presigned_url"]
    print(f"Download: {download_url}")
    ```
  </Tab>

  <Tab title="curl">
    ```bash theme={null}
    curl -X POST https://api.runpulse.com/meridian-convert \
      -H "x-api-key: YOUR_API_KEY" \
      -H "Content-Type: application/json" \
      -d '{
        "tables": [
          {
            "name": "Income Statement",
            "rows": 5,
            "columns": 3,
            "page": 1,
            "cells": [
              {"rowIndex": 0, "columnIndex": 0, "content": "Category"},
              {"rowIndex": 0, "columnIndex": 1, "content": "Q1"},
              {"rowIndex": 0, "columnIndex": 2, "content": "Q2"}
            ],
            "customSheetName": "Income Statement"
          }
        ],
        "filename": "financial_tables.xlsx",
        "formatSettings": {
          "fontFamily": "Calibri",
          "fontSize": 11,
          "alignment": "left"
        }
      }'
    ```
  </Tab>
</Tabs>

### Response

```json theme={null}
{
  "s3_object_url": "https://bucket.s3.amazonaws.com/meridian-convert/.../financial_tables.xlsx",
  "presigned_url": "https://bucket.s3.amazonaws.com/meridian-convert/...?X-Amz-Signature=...",
  "filename": "financial_tables.xlsx",
  "content_type": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
}
```

The `presigned_url` is valid for **7 days** and can be used to download the file directly.

***

## End-to-End: Extract → Meridian

A common workflow is to extract a document with tables and immediately convert them to Excel:

```python theme={null}
from pulse import Pulse
import requests

client = Pulse(api_key="YOUR_API_KEY")

# 1. Extract the document
result = client.extract(
    file=open("financial_report.pdf", "rb"),
    storage={"enabled": True}
)

# 2. Get tables from bounding_boxes
bounding_boxes = result.bounding_boxes or {}
raw_tables = bounding_boxes.get("Tables", [])

# 3. Convert to Meridian table format
tables = []
for i, tbl in enumerate(raw_tables):
    cells = [
        {
            "rowIndex": c["position"]["row"],
            "columnIndex": c["position"]["column"],
            "content": c.get("text", "")
        }
        for c in tbl.get("cell_data", [])
    ]
    tables.append({
        "name": f"Table {i+1}",
        "rows": tbl.get("table_info", {}).get("dimensions", {}).get("rows", 0),
        "columns": tbl.get("table_info", {}).get("dimensions", {}).get("columns", 0),
        "page": 1,
        "cells": cells,
        "customSheetName": f"Table {i+1}"
    })

# 4. Export to Excel
resp = requests.post(
    "https://api.runpulse.com/meridian-convert",
    headers={"x-api-key": "YOUR_API_KEY"},
    json={"tables": tables, "filename": "report_tables.xlsx"}
)

print(f"Download: {resp.json()['presigned_url']}")
```

***

## Related

<CardGroup cols={2}>
  <Card title="Extract Pipeline" icon="file-lines" href="/platform-reference/extract">
    The extraction step that produces the tables for Meridian
  </Card>

  <Card title="Bounding Boxes" icon="vector-square" href="/api-reference/bounding-boxes">
    Understanding the bounding box output that powers table detection
  </Card>
</CardGroup>