📄 Doc_Analyzer (PDF Text & NLP Analyzer in Python)

DocAnalyzer is a command-line tool built with Python that:

• Extracts full text from PDF files
• Identifies and highlights named entities (like names, dates, places)
• Analyzes and visualizes word frequency
• Generates a word cloud
• Creates important sentences summary
• Saves output in organized files and images

This is a self-directed NLP + automation project designed for offline usage, perfect for researchers and students.

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Built With

pdfplumber

nltk

spaCy

matplotlib

wordcloud

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Demo

Word Cloud Example	Word Frequency Plot

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Sample Input

We used a publicly available sample AI-related PDF (sample.pdf) which contains natural language and technical content. You can replace it with any other document.

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Output Files

All results are saved in the output/ folder:

File	Description
full_text.txt	Complete text extracted from the PDF
summary.txt	Top most relevant sentences
wordcloud.png	Word cloud of frequent words
frequency_plot.png	Bar chart of top word frequencies

Make sure sample.pdf is placed in the project root directory, like this:

Files Arrangements

DocAnalyzer/
├── pdf_analyzer.py
├── sample.pdf 
├── requirements.txt
├── README.md
├── output/
│ ├── full_text.txt
│ ├── summary.txt
│ ├── frequency_plot.png
│ └── wordcloud.png
└── .gitignore

Setup (First Time)

Clone the repository

git clone https://github.com/Waleed99i/DocAnalyzer.git
cd DocAnalyzer

Create virtual environment

python3 -m venv venv
source venv/bin/activate

Install dependencies

pip install -r requirements.txt

Download NLTK + spaCy models

python -m nltk.downloader punkt stopwords
python -m spacy download en_core_web_sm

How to Run

Step 1: Activate virtual environment

source venv/bin/activate

Step 2: Run the analyzer

python pdf_analyzer.py

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Author

Muhammad Waleed Akram

Electrical Engineering Student | AI + Systems Enthusiast

Checkout my Linkedin profile

License

This project is free to use under the MIT License.