Python for Pdf

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Why Python for PDF processing

PDF processing comes under text analytics. Most of the Text Analytics Library or frameworks are designed in Python only. This gives leverage on text analytics. Once you extract the useful information from PDF you can easily use that data into any Machine Learning or Natural Language Processing Model.

Common Python Libraries

Here is the list of some Python Libraries could be used to handle PDF files

PDFMiner is a tool for extracting information from PDF documents. Unlike other PDF-related tools, it focuses entirely on getting and analyzing text data.
PyPDF2 is a pure-python PDF library capable of splitting, merging together, cropping, and transforming the pages of PDF files. It can also add custom data, viewing options, and passwords to PDF files. It can retrieve text and metadata from PDFs as well as merge entire files together.
Tabula-py is a simple Python wrapper of tabula-java, which can read the table of PDF. You can read tables from PDF and convert into pandas’ DataFrame. tabula-py also enables you to convert a PDF file into CSV/TSV/JSON file.
Slate is wrapper Implementation of PDFMiner
PDFQuery is a light wrapper around pdfminer, lxml and pyquery. It’s designed to reliably extract data from sets of PDFs with as little code as possible.
xpdf Python wrapper for xpdf (currently just the “pdftotext” utility)

Extracting Text from pdf

First, we need to Install the

!pip install PyPDF2

Following is the code to extract simple Text from pdf using PyPDF2

# modules for 
import PyPDF2
# pdf file object
# you can find find the pdf file with complete code in below
pdfFileObj = open('example.pdf', 'rb')
# pdf reader object
pdfReader = PyPDF2.PdfFileReader(pdfFileObj)
# number of pages in pdf
print(pdfReader.numPages)
# a page object
pageObj = pdfReader.getPage(0)
# extracting text from page.
# this will print the text you can also save that into String
print(pageObj.extractText())

You can read more Details from here

Reading the Table data from pdf

In order to work with the Table data in Pdf, we can use Tabula-py

pip install tabula-py

Following is the code to extract simple Text from pdf using PyPDF2

import tabula
# readinf the PDF file that contain Table Data
# you can find find the pdf file with complete code in below
# read_pdf will save the pdf table into Pandas Dataframe
df = tabula.read_pdf("offense.pdf")
# in order to print first 5 lines of Table
df.head()

import PyPDF2

PDFfilename = "Sammamish.pdf" #filename of your PDF/directory where your PDF is stored

pfr = PyPDF2.PdfFileReader(open(PDFfilename, "rb")) #PdfFileReader object

pg4 = pfr.getPage(126) #extract pg 127

writer = PyPDF2.PdfFileWriter() #create PdfFileWriter object
#add pages
writer.addPage(pg4)

NewPDFfilename = "allTables.pdf" #filename of your PDF/directory where you want your new PDF to be
with open(NewPDFfilename, "wb") as outputStream:
    writer.write(outputStream) #write pages to new PDF

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#the table will be returned in a list of dataframe,for working with dataframe you need pandas
import pandas as pd
import tabula
file = "filename.pdf"
path = 'enter your directory path here'  + file
df = tabula.read_pdf(path, pages = '1', multiple_tables = True)
print(df)

Your question is near similar with:

If you Pdf file contain Multiple Table

df = tabula.read_pdf(“offense.pdf”,multiple_tables=True)

you can extract Information from the specific part of any specific page of PDF

tabula.read_pdf("offense.pdf", area=(126,149,212,462), pages=1)

If you want the output into JSON Format

tabula.read_pdf("offense.pdf", output_format="json")

Export Pdf into Excel

you can us Below code to convert the PDF Data into Excel or CSV

tabula.convert_into("offense.pdf", "offense_testing.xlsx", output_format="xlsx")