If you want to have a career in data science, knowing Python is a must.
Ill also show you several example questions and give you solutions to push you in the right direction.
Technical Concepts of Python Interview Questions
This guide is not company-specific.
Additionally, you should also attempt to find some company-specific questions and attempt to solve them too.
Knowing general concepts and practicing them on real-life questions is a winning combination.
Ill not bother you with theoretical questions.
It’s free, every week, in your inbox.
Data Types
Data types are the concept you should be familiar with.
Built-in Data Structures
These are list, dictionary, tuple, and sets.
These are arrays, stack, queue, trees, linked lists, graphs, HashMaps.
Built-in Functions
Python has over 60 built-in functions.
They do that until the conditionals (true/false tests) tell them to stop.
External Libraries (Pandas)
While there are several external libraries used, Pandas is probably the most popular.
It is designed for practical data analysis in finance, social sciences, statistics, and engineering.
Those are:
Data manipulation and analysis
Algorithms
Lets have a closer look at each of them.
for successfully 2FA they must confirm they received the SMS text message.
Confirmation texts are only valid on the date they were sent.
These message types should not be in the table.
Calculate the percentage of confirmed SMS texts for August 4, 2020.
Output just the difference in salaries.
Algorithms
When it comes to Python algorithm interview questions, they test your problem-solving using the algorithms.
Return the answer in any order.
A mapping of digit to letters (just like on the telephone buttons) is given below.
Note that 1 does not map to any letters.
Each of the digits 1-9 must occur exactly once in each column.
Each of the digits 1-9 must occur exactly once in each of the 9 33 sub-boxes of the grid.
character indicates empty cells.
This would be quite a complex algorithm and good for you if you knew how to solve it!
Conclusion
For a data science interview, the six technical concepts Ive mentioned are a must.
Of course, its recommended you dive even deeper into Python and broaden your knowledge.
For the first one, there are plenty of examples onStrataScratch.
You could probably find the questions from the company where you applied for a job.
AndLeetCodeis a good choice when you decide to practice writing Python algorithms before your interviews.
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.cult by Honeypot is a Berlin-based community platform for developers.
