🔥 Pandas Interview Q&A (Frequently Asked 🔥)

📊 Q1. What is Pandas and why is it used?

👉 Python library for data manipulation & analysis
👉 Provides powerful data structures like DataFrame & Series
👉 Used for cleaning, transforming, and analyzing data

📊 Q2. What is the difference between Series and DataFrame?

👉 Series → 1D labeled array (single column)
👉 DataFrame → 2D tabular structure (rows & columns)
👉 DataFrame is a collection of multiple Series

📊 Q3. How do you handle missing values in Pandas?

👉 isnull() / notnull() to detect missing values
👉 fillna() to replace missing data
👉 dropna() to remove missing records

📊 Q4. What is the difference between loc[] and iloc[]?

👉 loc[] → Label-based indexing
👉 iloc[] → Integer position-based indexing
👉 Use loc for named indexes, iloc for numeric positions

📊 Q5. What is groupby() in Pandas?

👉 Used for splitting data into groups
👉 Apply aggregation functions (sum, mean, count)
👉 Essential for data summarization

📊 Q6. What is the difference between merge() and concat()?

👉 merge() → SQL-like joins (inner, left, right, outer)
👉 concat() → Stacks data vertically or horizontally
👉 Use merge for relational data combining

📊 Q7. How do you filter data in Pandas?

👉 Use boolean conditions (df[df['col'] > value])
👉 Multiple conditions using & and |
👉 Helps in extracting specific insights

📊 Q8. What is apply() function?

👉 Applies a function across rows or columns
👉 Used for custom transformations
👉 More flexible than built-in functions

🔥 React with ♥️ for more such questions