Should You Practice Pandas for Data Science Interviews? A Complete Guide for New Grads

Should You Practice Pandas for Data Science Interviews? A Complete Guide for New Grads The Dilemma That's Keeping You Up at Night You're staring at your LeetCode problems, and your palms are getting sweaty. You've crushed medium-level tree problems, you understand dynamic programming, and your algorithm chops are getting sharper by the day. But then a nagging question creeps in: Am I missing something? You keep hearing about "data manipulation," "real-world scenarios," and "working with actual datasets" in data science interviews. Meanwhile, your LeetCode grind feels abstract—sorting arrays, finding cycles in graphs, reversing linked lists. None of that involves .groupby() or .merge(). The anxiety is real. You have limited time before graduation and tons of competition. Should you pivot and start grinding Pandas interview problems? Or is LeetCode enough? Is your reliance on cheat sheets going to torpedo your chances of landing that dream role at a tech company or AI startup? Here's the