Top stories published by Foundational Data Science: Interview Questions in September of 2020

Homepage

Open in app

Top Stories published by Foundational Data Science: Interview Questions in September of 2020

All

2020

September

Abish Pius in Foundational Data Science: Interview Questions

Sep 14, 2020

Q#8: Drop rows in dataframe that are between two dates

Abish Pius in Foundational Data Science: Interview Questions

Sep 2, 2020

Q#4: First or Third Class Mailers?

Suppose you’re trying to optimize a mailing campaign where physical mail is sent to potential…

1 response

Abish Pius in Foundational Data Science: Interview Questions

Sep 12, 2020

Q#7: Defective gaskets

Suppose you’re working in a parts manufacturing plant, and you’re running quality analysis on the gasket production…

Abish Pius in Foundational Data Science: Interview Questions

Sep 7, 2020

Q#5: Airbnb Stays by Country

Suppose you work for Airbnb as an analyst. A team has come to you asking for a ranked list containing total #…

Abish Pius in Foundational Data Science: Interview Questions

Sep 1, 2020

Q#3: Chocolate Bar Reviews

You have the following dataset of chocolate bar ratings. You can assume you have this data in a table called…

Abish Pius in Foundational Data Science: Interview Questions

Sep 9, 2020

Q#6: Multiply array values, return the remainder

Suppose you’re given an array of varying length containing multiple #s, and a number x. Using these inputs, write a short program in Python find the remainder of the array multiplication divided by x.

Abish Pius in Foundational Data Science: Interview Questions

Sep 18, 2020

Q#9: Identity Matrix

Can you build a function that prints an identity matrix, given the identity matrix size?

Examples:

Input: 2
Output: 
       1 0
       0 1

Input: 4
Output: 
       1 0 0 0
       0 1 0 0
       0 0 1 0…

August 2020

December 2020

About

Foundational Data Science: Interview Questions

Data Science tutorial working through solutions to Data Science Interview Questions

More information