I have a set of voter-list PDFs released by the election commission. The layout across all files is identical, so positional parsing is reliable. Right now I simply need the current batch converted, but long-term I want a reusable Python utility that pulls the following six columns straight into Excel: • Name • FathersName • Age • Gender • VoterID • SerialNumber . Section Name . Polling Station Name .etc. Scope of work 1. Run the first extraction and hand me the .xlsx file so I can verify accuracy. 2. Package the underlying code (Python 3.x) with clear instructions and any requirements.txt so I can repeat the conversion on future lists without further help. Technical notes – Consistent layout means you can lean on libraries like pdfplumber, camelot, tabula-py or even a custom regex approach—whatever you judge fastest and most reliable. – Output can be a straightforward table—no styling needed. Acceptance criteria • 100 % of pages processed with every row correctly aligned to the all columns. • Script runs from the command line in one step: `python extract_voters.py input.pdf output.xlsx`. • Clear README covering setup and a short comment block in the code explaining the parsing logic. If you have experience dissecting structured PDFs and enjoy building clean, repeatable tools, this should be quick work. Let me know your timeline and any dependencies you plan to use.