Extracting Text from Georgia Legislative Bills
This PDF contains legal bills from the Georgia legislature, published yearly. Challenges include extracting marked-up text like underlines and strikethroughs. It has line numbers that complicate text extraction.
page.region(right=70).show()(
page
.region(right=70)
.find_all('text')
.show(crop='wide')
)(
page
.region(right=70)
.find_all('text')
.right()
.show(crop='wide')Natural PDF basics with text and tables
Learn the fundamentals of Natural PDF - opening PDFs, extracting text with layout preservation, selecting elements by criteria, spatial navigation, and managing exclusion zones. Perfect starting point for PDF data extraction.
top = page.region(top=0, left=0, height=80)
bottom = page.find_all("line")[-1].below()
(top + bottom).show()print("BEFORE EXCLUSION:", pdf.pages[0].extract_text()[:200])
# Add header exclusion to all pages
pdf.add_exclusion(lambda page: page.region(top=0, left=0, height=80))
print("AFTER EXCLUSION:", pdf.pages[0].extract_text()[:200])Working with page structure
Extract text from complex multi-column layouts while maintaining proper reading order. Learn techniques for handling academic papers, newsletters, and documents with intricate column structures using Natural PDF's layout detection features.
left = page.region(left=0, right=page.width/3, top=0, bottom=page.height)
mid = page.region(left=page.width/3, right=page.width/3*2, top=0, bottom=page.height)
right = page.region(left=page.width/3*2, right=page.width, top=0, bottom=page.height)
page.highlight(left, mid, right)