Python Interview Questions Every Data Scientist Should Know

Python in Data Science Interviews

Python has become the lingua franca of data science. Interview questions range from basic data manipulation to complex algorithm design. Here's your guide to what matters most.

Core Python Concepts

Data Structures

Know when to use each and their time complexities:

• Lists — ordered, mutable, O(1) append, O(n) search
• Dictionaries — O(1) lookup, great for counting and grouping
• Sets — O(1) membership testing, useful for deduplication

# Common pattern: counting with defaultdict
from collections import defaultdict, Counter

words = ["apple", "banana", "apple", "cherry", "banana", "apple"]
counts = Counter(words)
# Counter({'apple': 3, 'banana': 2, 'cherry': 1})

List Comprehensions

Interviewers expect fluency with comprehensions:

# Filter and transform in one line
squared_evens = [x**2 for x in range(20) if x % 2 == 0]

# Nested comprehension for flattening
matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
flat = [x for row in matrix for x in row]

Pandas — The Most Tested Library

Key Operations

• groupby() and aggregation
• Merging and joining DataFrames
• Handling missing data
• Apply, map, and vectorized operations

import pandas as pd

# GroupBy with multiple aggregations
summary = (df.groupby('department')
             .agg(avg_salary=('salary', 'mean'),
                  headcount=('id', 'count'),
                  max_salary=('salary', 'max'))
             .reset_index())

Pivot Tables and Reshaping

# Create a pivot table
pivot = df.pivot_table(
    values='revenue',
    index='region',
    columns='quarter',
    aggfunc='sum',
    fill_value=0
)

Tips for Success

1. Think out loud — explain your approach before coding
2. Start simple — get a working solution, then optimize
3. Know pandas AND base Python — some companies test both
4. Handle edge cases — empty DataFrames, NaN values, duplicates

Practice Now

Build your confidence with our Python data science problems — real questions from Netflix, Airbnb, Google, and more.