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Can anyone please suggest me how to extract tabular data from a PDF using python/java program for the below borderless table present in a pdf file?

enter image description here

Richie
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3 Answers3

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This table might be difficult one for tabla. How about using guess=False, stream=True ?

Update: As of tabula-py 1.0.3, guess and stream should work together. No need to set guess=False to use stream or lattice option.

chezou
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  • Hi @chezou Thanks you for your comment. I tried your answer with the below code `tabula.convert_into("/Downloads/Test_Invoices/Invoice4.pdf", "/Downloads/Test_Invoices/Invoice4.csv", output_format="csv",spreadsheets=True,guess=False, stream=True) ` But no table has been extracted – Richie Aug 08 '18 at 12:12
  • Hi @chezou , Any other Python/Java related libraries you know? – Richie Aug 08 '18 at 12:14
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    I recommend you to set `pages` option. By default, tabula-py sets 1. – chezou Aug 08 '18 at 23:18
  • Hi @chezou , how would i do that? I'm not quite familiar with specifying these parameter values.. – Richie Aug 09 '18 at 04:52
  • **Here's my code** `df = tabula.read_pdf("/Downloads/Invoice1.pdf",guess=False, stream=True) print(df)` – Richie Aug 09 '18 at 04:53
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    set `pages="all"` lor `pages=2` for `read_pdf()` or `convert_into()`. For future detail, it’d be nice you to read the manual https://github.com/chezou/tabula-py/blob/master/README.md or you can check test codes https://github.com/chezou/tabula-py/blob/master/tests/test_read_pdf_table.py – chezou Aug 09 '18 at 04:59
  • Thanks for your update, I updated my code and went through the docs as you mentioned, but no hope in extracting it. Its alright i'm working on Python's **invoice2Data** code on Github and its helping a bit. Just need to make this process automated. Thanks a lot for your application. Its great..! – Richie Aug 09 '18 at 05:56
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I solved this problem via tabula-py

conda install tabula-py

and

>>> import tabula
>>> area = [70, 30, 750, 570] # Seems to have to be done manually
>>> page2 = tabula.read_pdf("nar_2021_editorial-2.pdf", guess=False, lattice=False, 
                 stream=True, multiple_tables=False, area=area, pages="all",
                   ) # `tabula` doc explains params very well
>>> page2

and I got this result

> 'pages' argument isn't specified.Will extract only from page 1 by default. [      
> ShortTitle                                              Text  \  0    
> Arena3Dweb         3D visualisation of multilayered networks     1    
> Aviator       Monitoring the availability of web services     2       
> b2bTools  Predictions for protein biophysical features and     3      
> NaN                                their conservation     4         
> BENZ WS          Four-level Enzyme Commission (EC) number     ..      
> ...                                               ...     68 
> miRTargetLink2              miRNA target gene and target pathway    
> 69             NaN                                          networks  
> 70       mmCSM-PPI            Effects of multiple point mutations on  
> 71             NaN                      protein-protein interactions  
> 72        ModFOLD8           Quality estimates for 3D protein models  
> 
>  
>                                                 URL    0                    http://bib.fleming.gr/Arena3D    1         
> https://www.ccb.uni-saarland.de/aviator    2                   
> https://bio2byte.be/b2btools/    3                                    
> NaN    4                 https://benzdb.biocomp.unibo.it/    ..       
> ...    68  https://www.ccb.uni-saarland.de/mirtargetlink2    69       
> NaN    70          http://biosig.unimelb.edu.au/mmcsm ppi    71       
> NaN    72       https://www.reading.ac.uk/bioinf/ModFOLD/      [73
> rows x 3 columns]]

This is an iterable obj, so you can manipulate it via for row in page2:

Hope it help you

zhangjq
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0

Tabula-py borderless table extraction:

Tabula-py has stream which on True detects table based on gaping.

from tabula convert_into
src_pdf = r"src_path"
des_csv = r"des_path"
convert_into(src_pdf, des_csv, guess=False, lattice=False, stream=True, pages="all")
dataninsight
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