Solving Real-World Data Science Interview Questions with Python Pandas

Dive into a comprehensive video tutorial that tackles real-world data science interview questions using Python Pandas. Work through a series of coding challenges, starting with easy problems and progressing to more difficult ones. Explore topics such as finding updated records, analyzing text with regex, handling datetime objects, and applying lambda functions to data frames. After the coding section, engage with five non-coding interview questions that test high-level thinking skills. Gain practical experience in grouping and aggregating DataFrames, filtering by conditionals, and solving problems from companies like Microsoft, Airbnb, Google, Meta, Amazon, and Uber. Perfect for aspiring data scientists looking to sharpen their skills and prepare for technical interviews.

- Intro & Video Overview
- Check out this Video’s Sponsor, Brilliant!
- Coding #1 Microsoft, Easy - Finding Updated Records
- Coding #2 Airbnb, Easy - Number of Bathrooms and Bedrooms
- Coding #3 Google, Medium - Counting Instances in Text
- Coding #4 Meta/Facebook, Medium - Customer Revenue in March
- Coding #5 Amazon, Hard - Monthly Percentage Difference
- Coding #6 Microsoft, Hard - Premium vs Freemium
- Non-Coding #1 Visa, Easy - Credit Card Activity
- Non-Coding #2 IBM, Easy - Outliers Detection
- Non-Coding #3 Google, Medium - Probability of Having a Sister
- Non-Coding #4 Uber, Medium - Uber Black Rides
- Non-Coding #5 Capital One, Hard - Terabyte of Data
- Video Conclusion & Recap