# Excel & CSV Extractor — xlsx, xls, csv to JSON (`gochujang/excel-extractor`) Actor

Extract data from Excel (.xlsx) and CSV files into structured JSON. Input: URL or base64. Output: sheet name, headers, rows. Batch multiple files. $0.01/file + $0.0001/row.

- **URL**: https://apify.com/gochujang/excel-extractor.md
- **Developed by:** [Hojun Lee](https://apify.com/gochujang) (community)
- **Categories:** AI, Developer tools, Automation
- **Stats:** 4 total users, 3 monthly users, 97.3% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Excel & CSV Extractor — xlsx, xls, csv to JSON

**Excel & CSV Extractor** converts `.xlsx`, `.xlsm`, and `.csv` files into clean, structured JSON — one record per sheet or one record per row in flat mode. Pass a URL or base64-encoded file, get back sheet names, headers, and row data. Works with multi-sheet workbooks up to 500,000 rows. No API key required. **$0.01/file + $0.0001/row.**

Spreadsheet data is locked in binary formats that no API can read directly. This actor is the extraction layer that unlocks it — turning Excel reports, exported CSVs, and supplier data files into JSON that any system can consume.

***

### Why use Excel & CSV Extractor?

1. **AI data ingestion** — Feed spreadsheet data directly into Claude, GPT, or RAG pipelines. JSON output from this actor is ready for vector embedding, tabular Q\&A, or structured analysis without manual conversion.
2. **ETL pipeline automation** — Transform Excel reports and CSV exports into database-ready records. Trigger on new file uploads, extract the data, push to your API — fully automated with no manual steps.
3. **Financial report processing** — Extract P\&L, balance sheet, or budget rows from multi-sheet workbooks. The `sheetNames` filter lets you target specific tabs without processing the entire file.
4. **Supplier data import** — Parse product catalogs, inventory sheets, and price lists from supplier Excel files and sync them to your e-commerce or ERP system in real time.
5. **Multi-sheet workbook handling** — Extract all tabs from complex workbooks in one run. Each sheet becomes a separate output record with its own `sheet`, `row_count`, `columns`, and `rows` fields.

***

### How to use

1. Open the actor on Apify Store and click **Try for free**.
2. Paste a direct URL to your `.xlsx` or `.csv` file in `fileUrl` (or provide `fileBase64` for local files).
3. Set `sheetNames` to target specific tabs, or leave empty to extract all sheets.
4. Enable `flatMode: true` for one-record-per-row output (useful for large datasets feeding downstream systems).
5. Click **Start**. Returns one output record per sheet.

***

### Input options

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `fileUrl` | string | — | Direct URL to `.xlsx`, `.xlsm`, or `.csv` file |
| `fileBase64` | string | — | Base64-encoded file content (alternative to URL) |
| `fileName` | string | auto | File name for format detection |
| `includeHeaders` | boolean | `true` | Treat first row as column headers |
| `sheetNames` | string\[] | `[]` (all) | Specific sheet names to extract |
| `maxRowsPerSheet` | integer | `10000` | Row cap per sheet (up to 500,000) |
| `flatMode` | boolean | `false` | One output record per row instead of per sheet |

***

### Output

**Per-sheet output (default):**

```json
{
  "file_name": "sales-report.xlsx",
  "sheet": "Q1 Sales",
  "row_count": 842,
  "columns": ["Date", "Product", "Region", "Revenue", "Units"],
  "rows": [
    {"Date": "2026-01-03", "Product": "Widget A", "Region": "US", "Revenue": "12400", "Units": "124"},
    {"Date": "2026-01-04", "Product": "Widget B", "Region": "EU", "Revenue": "8900", "Units": "89"}
  ]
}
```

**Flat mode (`flatMode: true`):**

```json
{
  "file_name": "sales-report.xlsx",
  "sheet": "Q1 Sales",
  "Date": "2026-01-03",
  "Product": "Widget A",
  "Region": "US",
  "Revenue": "12400",
  "Units": "124"
}
```

***

### Cost estimation

**$0.01 per file + $0.0001 per row extracted.**

| Example | Rows | Cost |
|---------|------|------|
| Small CSV (500 rows) | 500 | $0.06 |
| Sales report (5,000 rows) | 5,000 | $0.51 |
| Large dataset (50,000 rows) | 50,000 | $5.01 |

***

### Supported formats

| Format | Extension | Notes |
|--------|-----------|-------|
| Excel (modern) | `.xlsx`, `.xlsm` | Multi-sheet, formulas evaluated |
| CSV / TSV | `.csv`, `.tsv` | Auto-detects encoding (UTF-8, Latin-1) |

> **Legacy `.xls`**: Open in Excel or LibreOffice and save as `.xlsx` before processing.

***

### FAQ

**Can it handle password-protected files?**
No — password-protected files cannot be opened without the password, and the actor has no mechanism for it. Remove password protection before uploading.

**What happens with formula cells?**
Formulas are evaluated to their current values. The raw formula string is not included in output — you get the calculated result.

**Is there a file size limit?**
No hard limit, but very large files (100MB+) will require longer run times. Use `maxRowsPerSheet` to cap output if you only need a sample.

**Can it process files from Google Drive or Dropbox?**
Yes — generate a direct download link (not the sharing link) and pass it as `fileUrl`. For Google Sheets, use File → Download → xlsx to get a downloadable URL.

***

### Related actors

- [PDF Text Extractor](https://apify.com/gochujang/pdf-text-extractor) — Extract text from PDF files (same document-to-JSON workflow)
- [Web to Markdown](https://apify.com/gochujang/web-to-markdown) — Convert web pages to clean text for AI pipelines
- [RSS Feed Parser](https://apify.com/gochujang/rss-feed-parser) — Parse RSS/Atom feeds into JSON

### Feedback

If this actor unlocks your spreadsheet data, a review helps others find it: [Leave a review on Apify Store](https://apify.com/gochujang/excel-extractor#reviews)

# Actor input Schema

## `fileUrl` (type: `string`):

Direct URL to an Excel (.xlsx) or CSV file

## `fileBase64` (type: `string`):

Base64-encoded file content (alternative to fileUrl)

## `fileName` (type: `string`):

Used to detect format (.xlsx, .csv). Auto-detected from URL if omitted.

## `includeHeaders` (type: `boolean`):

Treat first row as column headers (rows output as objects). Default: true.

## `sheetNames` (type: `array`):

Which sheets to extract. Leave empty to extract all sheets.

## `maxRowsPerSheet` (type: `integer`):

Maximum rows to extract per sheet. Default: 10000.

## `flatMode` (type: `boolean`):

Output one dataset record per data row instead of one record per sheet.

## Actor input object example

```json
{
  "fileUrl": "https://example.com/data.xlsx",
  "includeHeaders": true,
  "sheetNames": [],
  "maxRowsPerSheet": 10000,
  "flatMode": false
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("gochujang/excel-extractor").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("gochujang/excel-extractor").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call gochujang/excel-extractor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,gochujang/excel-extractor"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/mLCxQsjuon0cW5sqC/builds/aFucGrJFL51a7Usq2/openapi.json