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Do you want to export tables from PDF files with Python programming language? You're in the right place.

Camelot is a Python library and a command-line tool that makes it easy for anyone to extract data tables trapped insidePDF files. Check theirofficial documentation andGitHub repository.

WhereasTabula-py is a simple Python wrapper of tabula-java, which can read tables in a PDF. It lets you convert a PDF file into a CSV, TSV, JSON, or even a pandas DataFrame. Make sure to haveJRE installed in your operating system if you want to use Tabula-py.

In this tutorial, you will learn how to extract tables in PDF using bothCamelot andtabula-py libraries in Python.

Download:Practical Python PDF Processing EBook.

First, you need toinstall the required dependencies for the Camelot library to work properly, and then you can install the libraries using the command line:

pip3 install camelot-py[cv] tabula-py

Note that you need to make sure that you haveTkinter andghostscript (which arethe required dependencies for Camelot) installed properly on your computer.

Extracting PDF Tables using Camelot

Now that you have installed all requirements for this tutorial, open up a new Python file and follow along:

import camelot# PDF file to extract tables fromfile = "foo.pdf"

I have aPDF file in the current directory called"foo.pdf" (get ithere) which is a standard PDF page that contains one table shown in the following image:

Just a random table. Let's extract it in Python:

# extract all the tables in the PDF filetables = camelot.read_pdf(file)

read_pdf() function extracts all tables in aPDF file. Let's print the number of tables extracted:

# number of tables extractedprint("Total tables extracted:", tables.n)

This outputs:

Total tables extracted: 1

Sure enough, it contains only one table, printing this table as aPandas DataFrame:

# print the first table as Pandas DataFrameprint(tables[0].df)

Output:

              0            1                2                     3                  4                  5                 60  Cycle \nName  KI \n(1/km)  Distance \n(mi)  Percent Fuel Savings1                                                  Improved \nSpeed  Decreased \nAccel  Eliminate \nStops  Decreased \nIdle2        2012_2         3.30              1.3                  5.9%               9.5%              29.2%             17.4%3        2145_1         0.68             11.2                  2.4%               0.1%               9.5%              2.7%4        4234_1         0.59             58.7                  8.5%               1.3%               8.5%              3.3%5        2032_2         0.17             57.8                 21.7%               0.3%               2.7%              1.2%6        4171_1         0.07            173.9                 58.1%               1.6%               2.1%              0.5%

That's precise. Let's export the table to aCSV file:

# export individually as CSVtables[0].to_csv("foo.csv")

CSV isn't the only option; you can also useto_excel(),to_html(),to_json() andto_sqlite() methods, here is an example exporting to Excel spreadsheet:

# export individually as Excel (.xlsx extension)tables[0].to_excel("foo.xlsx")

Or if you want to export all tables in one go:

# or export all in a ziptables.export("foo.csv", f="csv", compress=True)

f parameter indicates the file format, in this case,"csv".By settingcompress parameter equal toTrue, this will create aZIP file that contains all the tables inCSV format.

You can also export the tables toHTML format:

# export to HTMLtables.export("foo.html", f="html")

or you can export to other formats such asJSON andExceltoo.

It is worth noting that Camelot only works with text-basedPDFs and not scanned documents. If you can click and drag to select text in your table in aPDF viewer, it is a text-basedPDF, so this will work on papers, books, documents, and much more!

Read also:How to Split PDF Files in Python.

Extracting PDF Tables using Tabula-py

Open up a new Python file and importtabula:

import tabulaimport os

We simply useread_pdf() method to extract tables within PDF files (again, get the example PDFhere):

# read PDF filetables = tabula.read_pdf("1710.05006.pdf", pages="all")

We setpages to"all" to extract tables in all the PDF pages, thetabula.read_pdf() method returns a list of pandasDataFrames, eachDataFrame corresponds to a table. You can also pass a URL to this method and it'll automatically download the PDF before extracting tables.

The below code is an example of iterating over all extracted tables and saving them as Excel spreadsheets:

# save them in a folderfolder_name = "tables"if not os.path.isdir(folder_name):    os.mkdir(folder_name)# iterate over extracted tables and export as excel individuallyfor i, table in enumerate(tables, start=1):    table.to_excel(os.path.join(folder_name, f"table_{i}.xlsx"), index=False)

This will createtables folder and put all detected tables in Excel format into that folder, try it out.

Now, what if you want to extract all tables from a PDF file and dump them into a singleCSV file? The below code does exactly that:

# convert all tables of a PDF file into a single CSV file# supported output_formats are "csv", "json" or "tsv"tabula.convert_into("1710.05006.pdf", "output.csv", output_format="csv", pages="all")

If you have multiple PDF files and you want to run the above on all of them, then you can useconvert_into_by_batch() method:

# convert all PDFs in a folder into CSV format# `pdfs` folder should exist in the current directorytabula.convert_into_by_batch("pdfs", output_format="csv", pages="all")

This will look into thepdfs folder and output a CSV file for each PDF file in that folder.

Conclusion

For large files, theCamelot library tends to outperformtabula-py. However, sometimes you'll encounter aNotImplementedError for some PDFs using theCamelot library, you can usetabula-py as an alternative.

Note that this won't convert image characters to digital text. If you wish so, you can use OCR techniques to convert image optical characters to the actual text that can be manipulated in Python. The below tutorials can help you:

• Optical Character Recognition (OCR) in Python
• How to Extract Text from Images in PDF Files with Python

Below are some related PDF tutorials that may help you in your work:

• How to Highlight and Redact Text in PDF Files with Python
• How to Extract Images from PDF in Python
  

For a complete list, checkthe category's page.

Alright, this is it for this tutorial. CheckCamelot's official documentation andtabula-py official documentation for more detailed information.

Finally, we have an entireEBook about PDF Processing with Python, and there is a section where we dive deeper into extracting tables using Camelot, Tabula-Py, and PDFPlumber. Check it outhere if you're interested.

Check the complete codehere.

Happy Coding ♥

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