WhenDataTalks 📊🎬

Python projects exploring data, APIs, and machine learning through real-world entertainment datasets.

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🗂 Projects

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🎥 Day 4 — Bollywood vs Hollywood Dashboard

Scraped live box office data from the web and built a dark-themed dashboard comparing the two biggest film industries in the world.

✨ Highlights

• 🕸️ Live scraping with BeautifulSoup
• 🧹 Automated data cleaning pipeline
• 🌑 Dark-themed matplotlib dashboard
• 📊 Side-by-side industry comparison

🛠 Stack: Python · BeautifulSoup · pandas · matplotlib

python scraper.py
python clean.py
python dashboard.py

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🌐 Day 5 — Multi-API Analytics Terminal

A live data terminal that pulls from 4 different APIs simultaneously and generates automated weekly reports.

✨ Highlights

• ☁️ Live weather tracking
• 💻 GitHub profile analytics
• ₿ Cryptocurrency price monitoring
• 🎬 TMDB movie trend analysis
• 📋 Automated Friday digest report

🔗 APIs: OpenWeather · GitHub · CoinGecko · TMDB

🛠 Stack: Python · requests · pandas · python-dotenv

python live_data_terminal.py
python friday_report.py

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🤖 Day 6 — CinePredict AI

A machine learning web app that predicts whether a movie will be a HIT or FLOP — trained on real scraped data, enriched via TMDB, and deployed as an interactive Streamlit app.

✨ Highlights

• 🧹 Real box office data cleaned from scratch
• 🎯 Random Forest classifier — 96 movies, 7 features
• 📈 Confidence score + feature importance breakdown
• 🌐 Live Streamlit web app with sliders and dropdowns

🛠 Stack: Python · scikit-learn · pandas · Streamlit

python dataset.py        # build & enrich dataset
python train.py          # train model → model.pkl
python -m streamlit run app.py   # launch web app

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🧰 Full Stack

Python · BeautifulSoup · pandas · matplotlib · scikit-learn · Streamlit · REST APIs

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Built as a hands-on learning sprint in data analytics, APIs, and machine learning. 🚀