Uploaded January 2023 | Updated September 2026, 2 days ago
This video will walk you through the Airbnb 'Host Popularity Rental Prices' Python interview question solution. We'll guide you through the 3-step framework and cover how to use the drop duplicates () function and the lambda() function to find the solution to this complex Python coding interview question. If you're struggling to solve interview questions in Python, this tutorial will help you out!
🧑💻 Go to the question through the link below and follow along with me:
platform.stratascratch.com/coding/9632-host-popularity-rental-prices?utm_source=youtube&utm_medium=click&utm_campaign=YT+lambda+function+python
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👉 Subscribe to my channel: bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: bit.ly/3jifw81
👉 Playlist for data science interview tips: bit.ly/2G5hNoJ
👉 Practice more real data science interview questions: platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+lambda+function+python
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Timeline:
Intro: (0:00)
Interview Question: (0:27)
Exploring and understanding the dataset: (1:11)
Writing out the approach: (2:00)
Coding the solution: (3:40)
Conclusion: (8:30)
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About The Platform:
I'm using StrataScratch (platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+lambda+function+python), a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+lambda+function+python. All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, you can use ss15 for a 15% discount on the premium plans.
______________________________________________________________________
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
______________________________________________________________________
#StrataScratch #PythonInterviewQuestion
This video will walk you through the Airbnb 'Host Popularity Rental Prices' Python interview question solution. We'll guide you through the 3-step framework and cover how to use the drop duplicates () function and the lambda() function to find the solution to this complex Python coding interview question. If you're struggling to solve interview questions in Python, this tutorial will help you out!
🧑💻 Go to the question through the link below and follow along with me:
platform.stratascratch.com/coding/9632-host-popularity-rental-prices?utm_source=youtube&utm_medium=click&utm_campaign=YT+lambda+function+python
______________________________________________________________________
👉 Subscribe to my channel: bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: bit.ly/3jifw81
👉 Playlist for data science interview tips: bit.ly/2G5hNoJ
👉 Practice more real data science interview questions: platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+lambda+function+python
______________________________________________________________________
Timeline:
Intro: (0:00)
Interview Question: (0:27)
Exploring and understanding the dataset: (1:11)
Writing out the approach: (2:00)
Coding the solution: (3:40)
Conclusion: (8:30)
______________________________________________________________________
About The Platform:
I'm using StrataScratch (platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+lambda+function+python), a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+lambda+function+python. All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, you can use ss15 for a 15% discount on the premium plans.
______________________________________________________________________
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
______________________________________________________________________
#StrataScratch #PythonInterviewQuestion
![[Part 1]: Exploring and Visualizing Data For A Facebook Data Science Project of Movie Ratings](https://i.ytimg.com/vi/cM12QtrhdLo/mqdefault.jpg "[Part 1]: Exploring and Visualizing Data For A Facebook Data Science Project of Movie Ratings
Join us as we dive into a data science project from Facebook to predict Rotten Tomatoes movie ratings. We explored two different approaches. In the first approach, we focus on using numerical and categorical features, while in the second approach, we analyze the sentiment of movie reviews. Throughout the video, we compare our models predictions to actual data to evaluate their performance. By the end of this series, youll have a deeper understanding of how Rotten Tomatoes movie ratings can be predicted and gain valuable insights into machine learning techniques. Dont forget to subscribe to stay tuned and learn more about data science.
Watch the full tutorial:
📌[Part 2]: Exploring Decision Tree Classifiers For A Facebook Data Science Project of Movie Ratings: https://youtu.be/Ih6G5hnn30Q
📌 [Part 3]: Random Forest Classifier For A Facebook Data Science Project of Movie Ratings:
https://youtu.be/J4rheMtvu6g
Go to the project through the link below and follow along with me👇
https://platform.stratascratch.com/data-projects/rotten-tomatoes-movies-rating-prediction?utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+1
👉 Subscribe to my channel: https://bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ
👉 Playlist for data science projects: https://bit.ly/StrataScratchProjectsYouTube
👉 Practice more real data science interview questions: https://platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+1
Timeline:
Intro: (0:00)
Take-home assignment: (0:09)
Exploring the data: (1:48)
Summary of the data: (4:53)
Content rating variable visualization: (5:22)
Audience status visualization: (6:40)
Distribution of each audience status category: (7:04)
Take away: (10:03)
About The Platform:
Im using StrataScratch (https://platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+1), a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and Python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit https://platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+1. All questions are free and you can even execute SQL and Python code in the IDE. Still, if you want to check out the solutions from other users or from me, you can use ss15 for a 15% discount on the premium plans.
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
#datascienceproject")
