Of the fonts, formatting, colours and graphics of any source document, regardless of The lest most is the a receipt and the left most is the output which one gets after applying tesseract onto it.Īdobe® Portable Document Format (PDF) is a universal file format that preserves all In the above picture we can see how information is extracted. Tesseract is one of the best example of it. In real world scenario one can get any kind of PDFs, so one needs to use Optical character recognition (OCR) libraries which are meant for this. PDF2Text can extract data from text PDF, where as it will fail for extracting data from image PDF. Run file pdftotext_sample.py from the terminal using python pdftotext_sample.py command. data/sample_csv.csv to your desired file path. data/sample_file.pdf to your desired file path.Ĭhange the name of the output file at the line line 16 from. Do following to use thatĬhange the name of the pdf file path at the line 5 from. You can use the sample code that we have used from code folder. We have added some files in data folder as examples. After that anyone can apply regular extractions to get the most out of the data from the csv file.

The example taken is to show the capability of the library to extract the tables and data at the same time in meaningful way. In the above two pictures, the first one is the image of the pdf file and the second one is of the csv file that is generated from by the pdftotext library. It is really easy to use and can convert the pdf data into simple raw text very precisely. If the pdf is not made out of images this library is one of the best to use. There are some libraries already created, open sourced for doing such extractions.

Here we would like to show our research and work around how to get the data from pdfs. In order to study more about the companies we need some way to extract this data efficiently and precisely. Even the broachers of the companies are into pdfs. This is really one of the issue when we have to work with financial data as most of the companies works with pdfs to store their P&L, tax returns, general meeting notes and much more. There is so much data into the pdfs that we store but for other purposes like training the machine learning model we can not use that data directly from pdfs. Financial documents parsing examples with various different libraries

Ocr pdf to excel python