🔥 Python Interview Q&A for Data Analysts (Frequently Asked)

Q1️⃣ Difference between loc and iloc in Pandas?

✅ loc → Label-based indexing (column/row names)
✅ iloc → Integer-position based indexing

Q2️⃣ How do you handle missing values when deletion is not allowed?

✅ Use fillna() with mean/median/mode or forward/backward fill based on data context.

Q3️⃣ Difference between apply(), map() and applymap()?

✅ map() → Element-wise on Series
✅ apply() → Row/column-wise on DataFrame
✅ applymap() → Element-wise on entire DataFrame

Q4️⃣ How do you remove duplicate records based on specific columns?

✅df.drop_duplicates(subset=['col1','col2'])

Q5️⃣ Explain groupby() with a real use case.

✅ Used for aggregation like sales by region:
df.groupby('region')['sales'].sum()

Q6️⃣ Difference between merge() and join()?

✅ merge() → SQL-style joins on columns
✅ join() → Index-based joining

Q7️⃣ How do you optimize memory usage of a large DataFrame?

✅ Downcast dtypes, convert object to category, drop unused columns.

Q8️⃣ What is vectorization and why is it important?

✅ Performing operations on entire arrays instead of loops → much faster execution.

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