Data Science Portfolio - Kaggle Datasets & AI Projects | Artificial Intelligence

✅ Data Science Interview Questions with Answers Part-4 • 31. Why is Python popular in data science? Python is popular because it is simple to read, easy to write, and fast to prototype. It has strong libraries for data analysis, machine learning, and visualization. It integrates well with databases, cloud platforms, and production systems. This makes it practical for both experimentation and deployment. • 32. Difference between list, tuple, set, and dictionary? A list is an ordered and mutable collection used to store items that can change. A tuple is ordered but immutable, useful for fixed data. A set stores unique elements and is unordered, useful for removing duplicates. A dictionary stores key-value pairs and is used for fast lookups and structured data. • 33. What is NumPy and why is it fast? NumPy is a library for numerical computing that provides efficient array operations. It is fast because operations run in optimized C code instead of Python loops. It uses contiguous memory and vectorized operations, which reduces execution time significantly for large datasets. • 34. What is Pandas and where do you use it? Pandas is a data manipulation library used for cleaning, transforming, and analyzing structured data. It provides DataFrame and Series objects to work with tabular data. It is used for data cleaning, feature engineering, aggregation, and exploratory analysis before modeling. • 35. Difference between loc and iloc? loc is label-based indexing, meaning it selects data using column names and row labels. iloc is position-based indexing, meaning it selects data using numeric row and column positions. loc is more readable, while iloc is useful when working with index positions. • 36. What are vectorized operations? Vectorized operations apply computations to entire arrays at once instead of using loops. They are faster and more memory efficient. NumPy and Pandas rely heavily on vectorization to handle large datasets efficiently. • 37. What is lambda function? A lambda function is an anonymous, single-line function used for short operations. It is commonly used with functions like map, filter, and sort. Lambdas improve readability when logic is simple and used only once. • 38. What is list comprehension? List comprehension is a concise way to create lists using a single line of code. It combines looping and condition logic in a readable format. It is faster and cleaner than traditional for-loops for simple transformations. • 39. How do you handle large datasets in Python? Large datasets are handled by reading data in chunks, optimizing data types, and using efficient libraries like NumPy and Pandas. For very large data, distributed frameworks such as Spark or Dask are used. Memory usage is monitored to avoid crashes. • 40. What are common Python libraries used in data science? Common libraries include NumPy for numerical computing, Pandas for data manipulation, Matplotlib and Seaborn for visualization, Scikit-learn for machine learning, SciPy for scientific computing, and TensorFlow or PyTorch for deep learning. Double Tap ♥️ For Part-5