🐍 Python Interview Question (Data Analyst)

Question : What is the difference between apply() and map() in Pandas?

Answer:

map() works on Series only and is used for element-wise transformations.

apply() works on Series as well as DataFrames and can apply a function row-wise or column-wise.

Example :

df['salary_lakhs'] = df['salary'].map(lambda x: x / 100000)

df['total'] = df.apply(lambda row: row['sales'] - row['cost'], axis=1)

👉 Interview Tip:

Use map() for simple value replacement or transformation.

Use apply() when logic depends on multiple columns.

👉 Follow the channel and react ❤️ to this post for more Python & Data Analyst interview questions, tips, and cheat sheets shared regularly 🚀