tabulapdf: Extract tables from PDF documents

tabulapdf provides R bindings to the Tabula java library, which can be used to computationaly extract tables from PDF documents.

Note: tabulapdf is released under the MIT license, as is Tabula itself.

Installation

tabulapdf depends on rJava, which implies a system requirement for Java. This can be frustrating, especially on Windows. The preferred Windows workflow is to use Chocolatey to obtain, configure, and update Java. You need do this before installing rJava or attempting to use tabulapdf. More on this and troubleshooting below.

tabulapdf is not available on CRAN, but it can be installed from rOpenSci’s R-Universe:

install.packages("tabulapdf", repos = c("https://ropensci.r-universe.dev", "https://cloud.r-project.org"))

To install the latest development version:

if (!require(remotes)) install.packages("remotes")

# on 64-bit Windows
remotes::install_github(c("ropensci/tabulapdf"), INSTALL_opts = "--no-multiarch")

# elsewhere
remotes::install_github(c("ropensci/tabulapdf"))

Code Examples

The main function, extract_tables() provides an R clone of the Tabula command line application:

library(tabulapdf)
f <- system.file("examples", "data.pdf", package = "tabulapdf")
out1 <- extract_tables(f)
out1[[1]]

# # A tibble: 32 × 11
#      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#  1  21       6  160    110  3.9   2.62  16.5     0     1     4     4
#  2  21       6  160    110  3.9   2.88  17.0     0     1     4     4
#  3  22.8     4  108     93  3.85  2.32  18.6     1     1     4     1
#  4  21.4     6  258    110  3.08  3.21  19.4     1     0     3     1
#  5  18.7     8  360    175  3.15  3.44  17.0     0     0     3     2
#  6  18.1     6  225    105  2.76  3.46  20.2     1     0     3     1
#  7  14.3     8  360    245  3.21  3.57  15.8     0     0     3     4
#  8  24.4     4  147.    62  3.69  3.19  20       1     0     4     2
#  9  22.8     4  141.    95  3.92  3.15  22.9     1     0     4     2
# 10  19.2     6  168.   123  3.92  3.44  18.3     1     0     4     4
# # ℹ 22 more rows
# # ℹ Use `print(n = ...)` to see more rows

By default, it returns a list of tibbles. It can also write the tables to disk or attempt to coerce them to a list of matrices using the output argument. It is also possible to select tables from only specified pages using the pages argument.

out2 <- extract_tables(f, pages = 1, guess = FALSE, output = "tibble")
out2[[1]]

# # A tibble: 32 × 11
#      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#  1  21       6  160    110  3.9   2.62  16.5     0     1     4     4
#  2  21       6  160    110  3.9   2.88  17.0     0     1     4     4
#  3  22.8     4  108     93  3.85  2.32  18.6     1     1     4     1
#  4  21.4     6  258    110  3.08  3.21  19.4     1     0     3     1
#  5  18.7     8  360    175  3.15  3.44  17.0     0     0     3     2
#  6  18.1     6  225    105  2.76  3.46  20.2     1     0     3     1
#  7  14.3     8  360    245  3.21  3.57  15.8     0     0     3     4
#  8  24.4     4  147.    62  3.69  3.19  20       1     0     4     2
#  9  22.8     4  141.    95  3.92  3.15  22.9     1     0     4     2
# 10  19.2     6  168.   123  3.92  3.44  18.3     1     0     4     4
# # ℹ 22 more rows
# # ℹ Use `print(n = ...)` to see more rows

It is also possible to manually specify smaller areas within pages to look for tables using the area and columns arguments to extract_tables(). This facilitates extraction from smaller portions of a page, such as when a table is embeded in a larger section of text or graphics.

Another function, extract_areas() implements this through an interactive style in which each page of the PDF is loaded as an R graphic and the user can use their mouse to specify upper-left and lower-right bounds of an area. Those areas are then extracted auto-magically (and the return value is the same as for extract_tables()). Here’s a shot of it in action:

locate_areas() handles the area identification process without performing the extraction, which may be useful as a debugger.

extract_text() simply returns text, possibly separately for each (specified) page:

out3 <- extract_text(f, page = 3)
cat(out3, sep = "\n")

# len supp dose
# 4.20 VC 0.50
# 11.50 VC 0.50
# 7.30 VC 0.50
# 5.80 VC 0.50
# 6.40 VC 0.50
# 10.00 VC 0.50
# 11.20 VC 0.50
# 11.20 VC 0.50
# 5.20 VC 0.50
# 7.00 VC 0.50
# 16.50 VC 1.00
# 16.50 VC 1.00
# 15.20 VC 1.00
# 17.30 VC 1.00
# 22.50 VC 1.00

Note that for large PDF files, it is possible to run up against Java memory constraints, leading to a java.lang.OutOfMemoryError: Java heap space error message. Memory can be increased using options(java.parameters = "-Xmx16000m") set to some reasonable amount of memory.

Some other utility functions are also provided (and made possible by the Java Apache PDFBox library):

• extract_text() converts the text of an entire file or specified pages into an R character vector.
• split_pdf() and merge_pdfs() split and merge PDF documents, respectively.
• extract_metadata() extracts PDF metadata as a list.
• get_n_pages() determines the number of pages in a document.
• get_page_dims() determines the width and height of each page in pt (the unit used by area and columns arguments).
• make_thumbnails() converts specified pages of a PDF file to image files.

Installing Java on Windows with Chocolatey

In Power Shell prompt, install Chocolately if you don’t already have it.

Run Get-ExecutionPolicy. If it returns Restricted, then run Set-ExecutionPolicy AllSigned or Set-ExecutionPolicy Bypass -Scope Process. Then, install Chocolatey by running the following command:

Set-ExecutionPolicy Bypass -Scope Process -Force; [System.Net.ServicePointManager]::SecurityProtocol = [System.Net.ServicePointManager]::SecurityProtocol -bor 3072; iex ((New-Object System.Net.WebClient).DownloadString('https://community.chocolatey.org/install.ps1'))

Install java using the following command:

choco install openjdk11

You should now be able to safely open R, and use rJava and tabulapdf. From PowerShell, you should see something like this after running java -version:

OpenJDK Runtime Environment (build 11.0.22+7-post-Ubuntu-0ubuntu222.04.1)
OpenJDK 64-Bit Server VM (build 11.0.22+7-post-Ubuntu-0ubuntu222.04.1, mixed mode, sharing)

Troubleshooting

Mac OS and Linux

We tested with OpenJDK version 11. The package is configured to ask for that version of Java. If you have a different version of Java installed, you may need to change the JAVA_HOME environment variable to point to the correct version.

You need to ensure that R has been installed with Java support. This can often be fixed by running R CMD javareconf on the command line (possibly with sudo).

Windows

Make sure you have permission to write to and install packages to your R directory before trying to install the package. This can be changed from “Properties” on the right-click context menu. Alternatively, you can ensure write permission by choosing “Run as administrator” when launching R (again, from the right-click context menu).

Meta

• Please report any issues or bugs.
• Get citation information for tabulapdf in R doing citation(package = 'tabulapdf')
• License: Apache