The above code reads the first page of the PDF file, searching for tables, and appends each table as a DataFrame into a list of DataFrames dfs.
Step 1: Import library and define file pathĭfs = tabula.read_pdf(pdf_path, pages='1') Now we can extract it to CSV or DataFrame using Python: Method 1: We know that it is on the first page of the PDF file. Suppose you are interested in extracting the first table which looks like this: If you took a look, you can see that it has a total of 3 tables on 2 pages: 1 table on page 1 and 2 tables on page 2. In this section we will work with the file mentioned above. This file is used solely for the purposes of the code examples:Įxtract single table from single page of PDF using Python Now that we have the requirements installed, let’s find a few sample PDF files from which we will be extracting the tables.
Tabula-py is a Python wrapper for tabula-java, so you will also need Java installed on your computer.
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If you don’t have it installed, please open “Command Prompt” (on Windows) and install it using the following code: To continue following this tutorial we will need the following Python library: tabula-py. Thanks to Python and some of its amazing libraries, you can now extract these tables with a few lines of code! However, we all face a difficulty of easily extracting those tables to Excel or to DataFrames. They carry a lot of useful information and the reader may be particularly interested in some tables with datasets or findings and results of research papers. When reading research papers or working through some technical guides, we often obtain then in PDF format.
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