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03 Feb 2023

Extracting Tables From PDFs [No coding skills required]

Automated table extraction from PDF refers to a special form of data extraction, where information from rows and columns in PDF documents is converted into structured data that can be further processed (usually in Microsoft Excel or Google Spreadsheets). Table extraction combines several techniques, including object recognition, as well as table OCR and entity extraction features.

Coming by a table in a document isn’t hard, right? Perhaps you never thought about it, so let me state the obvious. Invoices, purchase orders, but also contracts, bank account statements, tax returns, and many more document types contain various tables.

You may not notice them, but they’re everywhere.

Doctor Who GIF
Source: Giphy.com

Each table contains key information that becomes useful in various business processes – product information sold or purchased, client or employee data, and so on. Transferring data manually – from tables to excel files or other software – is tedious.

That’s where extracting data from PDF to Excel comes in handy. So that this becomes your reality:

Table Extraction

Now that we’re done with the meme/gif part (not entirely done, a few more will pop up), let’s look at what you’ll get from this article:

  • Why should you automate importing data from tables to excel
  • Ways to handle PDF table to excel conversion
  • Why opting for free online tools puts your data in danger
  • Alphamoon’s table extraction feature
  • Business applications of automated table extraction

Let’s start with the first nagging question: why automate this process in the first place?

Extracting data from PDF to Excel

If you’re new to the automation talk – which, by the way, causes you to miss some substantial day-to-day improvements and benefits – the chances are that you or your team manually process each document. In such a case, the following might seem familiar.

After receiving a digital copy via e-mail or any other repository, the user has to open the file. Then, understand its contents, find the necessary information, import data manually (that is, type it in or copy&paste it) into another software, and then repeat the process. Something like this:

Infographic showing the step-by-step process of Manual Document Processing

That process may take up to 30 minutes, depending on the information’s complexity.

Since we’re discussing extracting data from PDF to Excel, let’s stick to invoices and purchase orders to paint the picture. They often contain scanned tables and a specific combination of text and numbers.

Moreover, both share similarities and have a direct connection as part of transactional document workflow. Invoices and purchase orders contain information that often requires a tabular presentation, with rows of items and columns indicating the numerical features of each item – descriptions, prices, tax information, and so on.

Where automation – Intelligent Document Processing, to be particular – comes in is the step where the document arrives in your inbox.

That early.

Jason Sudeikis Yes
Source: Giphy.com

By connecting the repository to a cloud-based platform (I’ll explain the solution in more detail soon, or you can also click here and jump directly to our business proposition), you support the entire workflow with AI. The platform pulls documents, then all the critical information from them, and leaves you with a nice CSV file (alternatively, you can also opt for API implementation and request a specific integration).

Document Processing workflow

No need to keep multiple windows open or tire yourself with the tedious copy&paste routine from PDFs.

Also, you’re in control of each step and can validate field extraction to free your work from errors.

This augmented document processing – with the assistance of Artificial Intelligence, as well as modes of Natural Language Processing, Object Detection, and Optical Character Recognition – is available with document automation software from Alphamoon.

Alternative (And Less Efficient) Ways To Handle PDF table to excel (.CSV) Conversion)

Since a simple Google search may bring about many ways to scrape tables from pdf, let’s consider these options too.

Python Coding

Do you have a knack for coding or a team that cannot wait to deploy their own thing? Awesome, there are better ways to put your skills to practice then.

Creating your own solution sounds tempting – particularly if someone convinces you that all you need is one line of code. But the truth is that using Tabula – a package enabling the conversion of pdfs into excel files – can be tricky and has limitations.

Most importantly, Tabula – like all the other alternatives to cloud-based software like Alphamoon – works only for digital documents. This implementation won’t do you any good for table scans and photographs (not to mention processing a crumpled piece of paper).

Moreover, you won’t be able to process batches of documents – such as an individual PDF file containing 50 various invoices.


  • a solution tailored to your specific needs
  • proprietary
  • works well with repeatable templates


  • Single-line coding solves only the most straightforward tasks
  • Very costly solution as it requires a dedicated Dev team
  • Time-consuming because it requires proper specification, project estimation, etc.
  • Handles only digital documents (no scans or photographs of documents)
Image of code on a screen

Free online tools

You may wonder why pay for a tool if there are free alternatives.

Indeed, some websites help with extracting data from tables, and no $$ is needed. A quick search with the correct query will give you a list of free online table converters.

Naturally, every free tool has one huge advantage – it’s free. But that’s not all.


  • Quick and efficient for individual fields
  • Document type-agnostic
  • Some of them don’t require any authentication or sign-up

No cons?

Futurama meme with the words "Wait A Second..."
Source: makeameme.org

Drawbacks of Free Online Tools For Table Extraction

Sure, free tools for importing data from pdf tables have indisputable benefits. However, there are also numerous disadvantages and potential risks associated with their use.

Complex & analog table structures

The bigger the table, the less accurate the tool. Most free tools that snap tables and convert them into data don’t have a continual learning module built-in. What’s the consequence? Every document that skews too far from the most common examples will likely cause trouble or won’t be processed at all.

Furthermore, importing scanned tables to Excel spreadsheet won’t be possible because free tools operate with digital copies only.

No batch processing & integrations

Free tools usually rely on a simple drag & drop system, which is easy and quick to use. However, that often comes with the limitation of adding just one file at a time.

Low accuracy

I’ve mentioned this before, but I can’t stress that enough, so here I go: the art of continual learning. Cloud-based tools are constantly trained, which allows them to sharpen their accuracy thanks to the influx of new data to process.

Data privacy at risk

That may be a general rule of thumb, but any document you upload into a free online tool stays there. Because “once on the Internet, always on the Internet.” And the Internet is a dark place.

But in all seriousness, some documents contain sensitive information you wouldn’t like to share anywhere. Opting for a platform like Alphamoon drastically increases the safety of the data stored in the papers.

A poor version of automation

If users still need to perform plenty of manual tasks, forced by a new tool used in the process, then the level of automation’s low. Automation is often expressed as time-saving, as SaaS businesses often want to save their clients’ time. Free pdf to excel converters require manual upload of individual documents, so it’s not a groundbreaking innovation.

The reality is that free tools can be recommended only for documents that:

  • do not contain sensitive data
  • come in very small numbers
  • include simple table extraction

By now, you have a better grip on how table extraction works. As part of a more extensive functionality known as data extraction, it may not be enough reason to onboard yourself with a new tool, teach colleagues how to use it…

Unless, data extraction was only a fraction of what the AI-supported platform for document automation could do.

data extracted from the table

Alphamoon IDP Platform – Page splitting, table extraction from PDFs & more

Alphamoon offers a tool that gives you control over several document-related tasks: including converting PDF tables to Excel. With these various features combined, you can pick apart every document workflow and adjust it to your needs.

Page splitting

Have you ever heard of monstrous scans? Neither have I, but that’s what I call a PDF that includes hundreds of documents. Page splitting function automates the division of pages within large batches, saving you time and stress.


The function of Optical Character Recognition means converting images to text. Table OCR, in particular, enables you to convert images to Excel tables. Supported by Artificial Intelligence, Alphamoon’s OCR manages photographs and scans of low quality – crumpled or stained copies too.

Entity Extraction

The IDP technology’s core is understanding the entities’ relations and pulling data contextually. Early versions of OCR software aimed at generating a wall of text that wasn’t structured at all. Meanwhile, modern engines scrape data that the user indicates, removing the unnecessary noise of irrelevant information. With Alphamoon’s IDP technology, you extract information that you pre-define, which gives you control over the process.


Sometimes, all companies need to speed up a process is the automatic labeling of documents. Customer Support teams use that function often because each team member may be assigned to a different document type. There are many ways to segment records, and Alphamoon lets you create the classes that reflect your situation.

Now, you’re almost there, at the very end. So, onto the last section of this article – the case study.

In the case of a complete idea blackout, this section helps to get the ball rolling. But you know your business best, so feel free to contact our team and tell us about your needs.

Case study #1: Receipts Processing [Paper document]

Technically speaking, a receipt listing items with associated prices, discounts, taxes, and quantities is pretty much a table itself, and it’s a perfect use case for table OCR and extracting tables from images or scans. Note that pulling data from receipts can massively help PoS providers and brick-and-mortar shops (among many other use cases).

The receipts workflow can also utilize several features of Intelligent Document Processing.

When printed directly at the point of sale – in the case of gas stations in Poland – invoices look almost identical to receipts. When a particular document workflow contains documents that need to be segmented, it’s best to start with Classification. Each document will have its class, and the classes can be adjusted to the use case.

Two necessary steps in receipts automation are OCR and data extraction. While the first aims to convert paper slips (scans and photographs) into text, the latter pulls only the critical information you need. Therefore, the conversion of a table from PDF to Excel is a part of the extraction feature.

Source: Google Images


That’s all – hopefully, you’re more knowledgeable in the table extraction topic and have a good understanding of the benefits of using Alphamoon. We’re one short form away from helping you identify the bottlenecks in document workflows.

So, let’s chat!

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