addPage (pg3 ) #filename of your PDF/directory where you want your new PDF to be PdfFileWriter ( ) #create PdfFileWriter object #add pages I used PdfFileReader() and PdfFileWriter() classes for reading and writing the table data. Reading a PDF document is pretty simple and straight forward. But it can extract text and return it as a Python string. After spending a little time with it, I realized PyPDF2 does not have a way to extract images, charts, or other media from PDF documents. PyPDF2 can extract data from PDF files and manipulate existing PDFs to produce a new file. When I Googled around for ‘Python read pdf’, PyPDF2 was the first tool I stumbled upon. Method 1: Extract the Pages with Tables using PyPDF2 and PDFTables I liked this solution much better and I am using it for my work.

Later I came across PDFMiner and started exploring it for extracting data using its pdf2txt.py script. It did serve my requirement but is paid service. I will extract the table data for Hispanic or Latino Origin Population by Type: 20 from of the PDF file.įor achieving this, I first tried using PyPDF2 (for extracting) and PDFtables (for converting PDF tables to Excel/CSV). If you look at the content of the PDF, you can see that there is a lot of text data, table data, graphs, maps etc.

We will take an example of US census data for the Hispanic Population for 2010. In this post, I will show you a couple of ways to extract text and table data from PDF file using Python and write it into a CSV or Excel file. The PDF file format was not designed to hold structured data, which makes extracting data from PDFs difficult.

When government organizations publish data online, barring a few notable exceptions, it usually releases it as a series of PDFs. When testing highly data dependent products, I find it very useful to use data published by governments.

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