Given the above Python code, what will be printed?
Anonymous Quiz
14%
"hello"
70%
"olleh"
9%
"" (empty string)
7%
Error
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140+ Python Practice Programs - For Real Learning, Not Just Theory
Struggling with Python logic?
Here's over 140 real Python programs that will help you to understand how code actually works-beyond the tutorials.
From basics to interview-level logic:
Arithmetic & conversions
Loops, Recursion, Lists, Arrays
Prime, Fibonacci, Armstrong logic
Matrices, Sorting, Factorials & more
Python pdf
Struggling with Python logic?
Here's over 140 real Python programs that will help you to understand how code actually works-beyond the tutorials.
From basics to interview-level logic:
Arithmetic & conversions
Loops, Recursion, Lists, Arrays
Prime, Fibonacci, Armstrong logic
Matrices, Sorting, Factorials & more
Python pdf
❤5👏1
🚀 Free & Relevant Books for Data Science (2025) 📚
Want to sharpen your Python & DS skills without outdated material? Here are some modern, still-relevant free books 👇
1️⃣ Python Data Science Handbook – Jake VanderPlas
🔗 https://jakevdp.github.io/PythonDataScienceHandbook
Core libs: NumPy, Pandas, Matplotlib, Scikit-Learn. Updated + interactive notebooks.
2️⃣ Python for Data Analysis (3rd Ed.) – Wes McKinney
🔗 https://github.com/wesm/pydata-book
By the creator of Pandas. Modern data wrangling & cleaning.
3️⃣ Dive into Deep Learning (D2L.ai)
🔗 https://d2l.ai
Hands-on deep learning with PyTorch & TensorFlow. University-level, interactive.
4️⃣ Minimalist Data Wrangling with Python (2023) – Marek Gagolewski
🔗 https://arxiv.org/abs/2211.04630
Practical workflows for real-world messy data.
5️⃣ Machine Learning with PyTorch & Scikit-Learn – Raschka et al.
🔗 https://github.com/rasbt/machine-learning-book
End-to-end ML with clean, modern Python code.
✨ Start with VanderPlas & McKinney for core skills, then move to Raschka/D2L for ML.
Want to sharpen your Python & DS skills without outdated material? Here are some modern, still-relevant free books 👇
1️⃣ Python Data Science Handbook – Jake VanderPlas
🔗 https://jakevdp.github.io/PythonDataScienceHandbook
Core libs: NumPy, Pandas, Matplotlib, Scikit-Learn. Updated + interactive notebooks.
2️⃣ Python for Data Analysis (3rd Ed.) – Wes McKinney
🔗 https://github.com/wesm/pydata-book
By the creator of Pandas. Modern data wrangling & cleaning.
3️⃣ Dive into Deep Learning (D2L.ai)
🔗 https://d2l.ai
Hands-on deep learning with PyTorch & TensorFlow. University-level, interactive.
4️⃣ Minimalist Data Wrangling with Python (2023) – Marek Gagolewski
🔗 https://arxiv.org/abs/2211.04630
Practical workflows for real-world messy data.
5️⃣ Machine Learning with PyTorch & Scikit-Learn – Raschka et al.
🔗 https://github.com/rasbt/machine-learning-book
End-to-end ML with clean, modern Python code.
✨ Start with VanderPlas & McKinney for core skills, then move to Raschka/D2L for ML.
jakevdp.github.io
Python Data Science Handbook | Python Data Science Handbook
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