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Post🐍 π—£π˜†π˜π—΅π—Όπ—» π—™π˜‚π—»π—°π˜π—Άπ—Όπ—»π˜€ π—˜π˜ƒπ—²π—Ώπ˜† 𝗕𝗲𝗴𝗢𝗻𝗻𝗲𝗿 π—¦π—΅π—Όπ˜‚π—Ήπ—± π—žπ—»π—Όπ˜„

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🐍 π—£π˜†π˜π—΅π—Όπ—» π—™π˜‚π—»π—°π˜π—Άπ—Όπ—»π˜€ π—˜π˜ƒπ—²π—Ώπ˜† 𝗕𝗲𝗴𝗢𝗻𝗻𝗲𝗿 π—¦π—΅π—Όπ˜‚π—Ήπ—± π—žπ—»π—Όπ˜„ πŸ“Š Numeric: abs(), round(), min(), max(), sum(), pow() πŸ”€ String: len(), upper(), lower(), split(), join(), replace() πŸ“‹ Lists: append(), extend(), insert(), pop(), remove(), sort() πŸ”— Tuples & Sets: count(), index(), add(), update(), remove(), clear() πŸ” Control Flow: print(), input(), type(), range(), enumerate() 🎲 Random & Conversion: randint(), choice(), shuffle(), int(), float(), str() βš™οΈ Functions: def, lambda, return, map() ⚠️ Error Handling: try, except, raise, assert, finally πŸ’‘ Don't just memorize themβ€”use them in projects, automation, and data analysis. πŸš€ Strong Python fundamentals are the foundation of Data Science, AI, and Software Development.
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