3 ways to scrape tables from PDFs with Python

3 ways to scrape tables from PDFs with Python

Python
This post will go through a few ways of scraping tables from PDFs with Python. To learn more about scraping tables and other data from PDFs with R, click here. Note, this options will only work for PDFs that are typed - not scanned-in images. tabula-py tabula-py is a very nice package that allows you to both scrape PDFs, as well as convert PDFs directly into CSV files. tabula-py can be installed using pip: [code] pip install tabula-py [/code] If you have issues with installation, check this. Once installed, tabula-py is straightforward to use. Below we use it scrape all the tables from a paper on classification regarding the Iris dataset (available here). [code lang="python"] import tabula file = "http://lab.fs.uni-lj.si/lasin/wp/IMIT_files/neural/doc/seminar8.pdf" tables = tabula.read_pdf(file, pages = "all", multiple_tables = True) [/code]…
Read More
Getting data from PDFs the easy way with R

Getting data from PDFs the easy way with R

R
Earlier this year, a new package called tabulizer was released in R, which allows you to automatically pull out tables and text from PDFs. Note, this package only works if the PDF's text is highlightable (if it's typed) -- i.e. it won't work for scanned-in PDFs, or image files converted to PDFs. If you don't have tabulizer installed, just run install.packages("tabulizer") to get started. Initial Setup After you have tabulizer installed, we'll load it, and define a variable referencing an example PDF. [code lang="R"] library(tabulizer) site <- "http://www.sedl.org/afterschool/toolkits/science/pdf/ast_sci_data_tables_sample.pdf" [/code] The PDFs you manipulate with this package don't have to be located on your machine -- you can use tabulizer to reference a PDF by a URL. For our first example, we're going to use a sample PDF file found here:…
Read More