Tabula

Ad free sharing & download. No ads, no interruptions. 100GB cloud storage. Just enough 4shared storage space for your files. Premium download. Instant and Resumable download at faster download speed. Maximum data security. SSL data encryption for maximum protection of your files. Camelot: PDF Table Extraction for Humans¶. Release v0.10.1. (Installation)Camelot is a Python library that can help you extract tables from PDFs!

Current Version:1.2.1

Other Versions:pre-releases & archives

Need help? Open an issue on Github.

Donate: Help support this project by backing us on OpenCollective.

We'd love to hear from you! Say hi on Twitter at @TabulaPDF

Latest Version: Tabula 1.2.1

June 4, 2018

Tabula 1.2.1 fixes several bugs in the user interface and processing backend. (You can read about all the changes in the release notes.)

Download Tabula below, or on the release notes page.

Special thanks to our OpenCollective backers for supporting our work on Tabula; if you find Tabula useful in your work, please consider a one-time or monthly donation.

How Can Tabula Help Me?

If you’ve ever tried to do anything with data provided to you in PDFs, you know how painful it is — there's no easy way to copy-and-paste rows of data out of PDF files. Tabula allows you to extract that data into a CSV or Microsoft Excel spreadsheet using a simple, easy-to-use interface. Tabula works on Mac, Windows and Linux.

Who Uses Tabula?

Tabula is used to power investigative reporting at news organizations of all sizes, including ProPublica, The Times of London, Foreign Policy, La Nación (Argentina), The New York Times and the St. Paul (MN) Pioneer Press.

Grassroots organizations like SchoolCuts.org rely on Tabula to turn clunky documents into human-friendly public resources.

And researchers of all kinds use Tabula to turn PDF reports into Excel spreadsheets, CSVs, and JSON files for use in analysis and database applications.

Download & Install Tabula

Windows & Linux users will need a copy of Java installed. You can download Java here. (Java is included in the Mac version.)

Download the version of Tabula for your operating system:

Windows:tabula-win.zip
Mac OS X:tabula-mac.zip
Linux/Other:tabula-jar.zip, view README.txt inside for instructions

Extract the zip file. (Instructions: Windows, Mac)
Go into the folder you just extracted. Run the 'Tabula' program inside.
A web browser will open. If it doesn't, open your web browser, and go to http://localhost:8080. There's Tabula!

How to Use Tabula

Upload a PDF file containing a data table.
Browse to the page you want, then select the table by clicking and dragging to draw a box around the table.
Click 'Preview & Export Extracted Data'. Tabula will try to extract the data and display a preview. Inspect the data to make sure it looks correct. If data is missing, you can go back to adjust your selection.
Click the 'Export' button.
Now you can work with your data as text file or a spreadsheet rather than a PDF! (You can open the downloaded file in Microsoft Excel or the free LibreOffice Calc)

Note: Tabula only works on text-based PDFs, not scanned documents.

Authors and Contributors

Tabula was created by Manuel Aristarán, Mike Tigas and Jeremy B. Merrill with the support of ProPublica, La Nación DATA, Knight-Mozilla OpenNews, The New York Times. Tabula was designed by Jason Das.

Tabula was created by journalists for journalists and anyone else working with data locked away in PDFs. Tabula will always be free and open source.

Want to contribute? Fork it on GitHub and check out the to-do list for ideas. You can also support our continued work on Tabula with a one-time or monthly donation.

Tabula is made possible in part through the generosity of our users and through grants from the Knight Foundation and the Shuttleworth Foundation.

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:

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).

The result stored into tables is a list of data frames which correspond to all the tables found in the PDF file. To search for all the tables in a file you have to specify the parameters page = “all” and multiple_tables = True.

You can also use tabula-py to convert a PDF file directly into a CSV. The first line below will find the first table in the PDF and output it to a CSV. If we add the parameter all = True, we can write all of the PDF’s tables to the CSV.

tabula-py can also scrape all of the PDFs in a directory in just one line of code, and drop the tables from each into CSV files.

We can perform the same operation, except drop the files out to JSON instead, like below.

Camelot

Camelot is another possibility for scraping tables from PDFs. Camelot can be installed like so:

Camelot does have some additional dependencies, including GhostScript, which are listed here. Once installed, we can use Camelot similarly to tabula-py to scrape PDF tables.

This returns a TableList object. To access any of the tables found by index, you can do this:

One cool feature of Camelot is that you also get a “parsing report” for each table giving an accuracy metric, the page the table was found on, and the percentage of whitespace present in the table.

From here we can see that the 0th-indexed identified table is essentially whitespace. If we look at the raw PDF, we can see there’s not a table on that page, so it’s safe to ignore this empty data frame.

Like tabula-py, you can export all the scraped tables to a file. Camelot supports (as of this writing) CSV, JSON, HTML, and SQLite. If you choose CSV, Camelot will create a separate CSV file for each table by default. You can create a zip file of these CSVs by adding the parameter compress = True. Choosing to export to excel will create a single workbook containing an individual worksheet for each table.

If you want to export just a single table, you can do it just like in pandas since each individual table can be referred to as a data frame object.

Excalibur

Cached

If you’re looking for a web interface to use for extracting PDF tables, you can check out Excalibur, which is built on top of Camelot.

After Camelot Pdf Free Download Pdf

If Camelot is already installed, you can just use pip to install Excalibur:

You can get started with Excalibur from the command line. After you open the command line, just type the following:

The above command will initialize a meta database needed for the application. Next, run the below command to start the web server via Flask:

If you open a web browser to your local host, you should see an interface like below.

From here, you’ll be able to upload a PDF file of your choice, and Excalibur will do the rest.

After Camelot PDF Free Download

For more on working with PDF files, check out this post for how to read PDF text with Python.

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