Learn how to extract tables from PDFs with ease using Intelligent Document Processing solutions like FormX. Automate your table e
Almost every business today stores its documents in PDF format. It's no surprise, given the convenience of the format and its popularity for sharing documents. However, extracting data from PDFs can be challenging, especially when the files contain scanned images of the physical document.
Although you can use the tedious approach of manually copying and pasting data from PDFs into another document, extracting tables from PDF files is certainly way more challenging and complicated. You cannot copy and paste without distorting columns and rows.
Despite the challenges, it's vital to understand how to extract tables from PDFs because various documents like bank statements, purchase orders, and other financial statements include tables. You can only benefit from the data in these documents if you make sense of it by digitizing and turning it into a structured format.
Luckily, there are several tools like FormX to help you extract tables from PDF efficiently. Read on to learn about the various solutions you can leverage to get a table from a PDF in no time.
If your tabulated data is trapped in a PDF file and you would like to use it elsewhere, you don't have to waste time copying it manually. The following solutions will help you extract tables from PDFs quickly and accurately:
FormX is an intelligent document processing solution that helps businesses extract data and tables from PDFs or images and converts them into structured data formats like JSON or CSV. It leverages AI technologies like OCR and machine learning to enhance data validation, document classification, and information extraction. The AI technologies ensure data extraction is not limited to native PDFs and allow users to create and train their own extractors without writing a single line of code.
FormX is fast, accurate, and more importantly easy to use. It comes with a set of pre-trained extractors, such as IDs, receipts, business registration, etc., that users can use directly to extract table and data fields from various documents. Moreover, the simple integration via API allows businesses to easily send the extracted result to different software for further processing or analysis.
Extracting tables from PDF only takes a few steps to set up.
Step 1. Sign up for a free trial
You can process the first 100 pages of bank statements with FormX for free! You simply have to sign up here.
Step 2. Create your table extractor
After creating an account, you can then create an extractor to extract tables or other data fields based on the type of your documents.
Step 3. Upload your master image and mark your fields/regions
If your document has a fixed layout, you can then upload a master image and label the anchor regions, which are regions with fixed positions, and detection regions, which are the places where the data can be found.
When labelling the detection regions, you have a variety of extraction items or data types to choose to maximize the accuracy of the extracted results.
Step 4. Test your extractor
After labelling the regions, you can then upload a sample image to test the accuracy of your table extractor. As you can see, FormX has successfully extracted the table.
Step 5. Integrate FormX with your software to automate table extraction from PDF
After you have tested out your extractor, you can then integrate it with your software using RESTful API to automate table extraction from PDF. The images will be sent to the API endpoint "https://worker.formextractorai.com/extract" with the Form ID and Access Token. You will see the extracted information in the API response.
Tabula is an open-source software that specifically journalists created to help them extract data trapped in PDF files. Its simple and easy-to-use interface will help you extract data from PDFs into a CSV or Microsoft Excel spreadsheet. Tabula works on Mac, Windows, and Linux, making it accessible to many users.
The process of using Tabula is straightforward. You start by uploading the PDF file you want to extract data from. Then, select the table or area of text containing your desired data by drawing a box around it.
Tabula will try to detect the data you want and extract it in a structured format. You can preview the columns and rows before exporting your table.
Although Tabula is an effective solution for extracting tables from PDFs, there are some downsides. For example, it only works on native PDFs produced directly by a text editor such as Adobe Acrobat or Microsoft Word. This means you can't use Tabula to extract data from PDFs created from scanned documents and images.
Another disadvantage of using Tabula is that it doesn't support batch processing. You can only extract data from one document at a time, which can be time-consuming.
Additionally, it does not use Optical Character Recognition (OCR), so it won't recognize text in images, such as scanned documents and photos. Tabula is also not fully automated, so it will require a lot of manual input on your end to extract tables from PDFs.
PDFTables is a PDF-to-Excel converter that allows you to convert PDF files into CSV, Excel, JSON, and XML files. The solution relies entirely on internal algorithms, so you can’t customize the conversion process results. Once you upload your PDF file, PDFTable will convert it into an organized table format.
PDFTables will work well on large and small data sets and handle multiple files simultaneously. However, the solution does not have OCR-integrated engines and can only extract data from native PDFs. Like Tabula, it won’t be able to extract data from PDFs created from scanned images.
PDFTables also limits your ability to customize the table algorithm. Since it solely relies on an underlying algorithm, it might not recognize certain characters and table structures. As a result, you might not get the exact output you want from your PDFs.
Furthermore, this solution does not support cloud integration. You should manually upload your files to the platform whenever you want to extract tables from PDFs. After the extraction, you should manually download the files before uploading them to other systems for further use.
Docparser is a cloud-based document data extraction solution that you can use to retrieve data from PDFs, Word documents, and image files. Docparser uses advanced pattern recognition and Zonal OCR technology to identify and extract data from documents. This makes it easy to convert your documents into structured data that you can use in other applications or databases.
Docparser works by first analyzing the document and identifying key patterns in the text. It then uses these patterns to identify specific fields within the document, such as purchase order numbers, customer names, or product codes.
After identifying these fields, Docparser can extract them into a structured format such as CSV or Excel. This format allows you to access the necessary information without manually searching through each document.
One advantage of Docparser is that it has built-in OCR capabilities. It can extract data from documents created from scanned images and other non-native PDFs. The solution also supports batch processing, so you can extract data from multiple documents simultaneously.
However, Docparser has downsides because it doesn't leverage machine learning. As a result, you may not get the most accurate extraction results, especially when dealing with complex or new documents in new formats. DocParser only yields accurate results when you use known templates or documents with specific region formatting.
Once you extract a table from a PDF, you’ll have the data in a structured format such as CSV or Excel. You can use this in the same way you would use any other structured data.
For example, when you have your financial statements in digital form, it's easier to protect them from unauthorized access. You can do this by storing them safely in the cloud, encrypting sensitive data, and implementing user authentication.
Moreover, when you have the tables in a structured format, it's easier to use them for further financial analysis. For instance, you can use the data to create visualizations of trends and forecasts and gain actionable insights from financials.
After tabulating data from purchase orders, invoices, and receipts, you can use it for inventory management and other accounting purposes. You can use data from your invoices to track inventory levels, compare shipping costs across vendors, and analyze customer purchasing patterns.
At the same time, the table you extract from receipts submitted by your employees will help you keep track of your business expenses. From these receipts, you can make a table of what was purchased, who purchased it, and how much they spent. This data makes it much easier to monitor spending, audit employee reimbursement requests, and create financial reports.
If you're in the public sector, the table you extract from PDFs can help with customer service, fraud prevention, and regulatory compliance. Governments often rely on PDF forms for collecting data from citizens. Extracting information from these documents into a table makes it easier to manage the data and provides faster services.
As the volume of PDF documents increases, you need a reliable solution that can extract data from these documents as quickly and accurately as possible. FormX is an excellent solution for this and can help you turn PDF documents into structured data.
FormX is a no-code solution that allows you to extract data and tables from all kinds of documents, including receipts, IDs, passports, purchase order, and business certificates. Simply upload some samples of the documents you want to process, label the data fields, and verify the results.
FormX will automatically detect patterns in each document and extract tables with minimal manual intervention. Contact us today to schedule a demo and experience the power of FormX.
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