10 Questions, 10 Minutes – 1/100

This is something which has been on my mind since a long time. We will be picking 10 questions per day and would like to simplify it.
We will make sure that the complete article is covered in 10 minutes by the reader. There will be 100 posts in the coming 3 months.

The articles/questions will revolve around SQL, Statistics, Python/R, MS Excel, Statistical Modelling, and case studies.

The questions will be a mix of these topics to help you prepare for interviews

You can also contribute by framing 10 questions and sending it to [email protected] or messaging me on Linkedin.

The questions will be updated late in the night ~1-2 a.m. and will be posted on Linkedin as well.

Let’s see how many can we solve in the next 100 posts

1. Write the syntax to create a new column using Row Number over the Salary column

SELECT *, ROW_NUMBER() OVER (Order By Salary) as Row_Num
FROM Employee

Output

2. What is PARTITION BY clause?
PARTITION BY clause is used to create a partition of ranking in a table. If you partition by Salary in the above table, then it will provide a ranking based on each unique salary. Example below:-

SELECT *, ROW_NUMBER() OVER (PARTITION BY Salary ORDER BY Salary) as Row_Num

3. What is a RANK() function? How is it different from ROW_NUMBER()?
– RANK() function gives ranking to a row based on the value on which you want to base your ranking. If there are equal values, then the rank will be repeated and the row following the repeated values will skip as many ranks as there are repeated values row. Confused?? Try out the example below:-

SELECT *, RANK() OVER (ORDER BY Salary) as Row_Num
FROM Employee

Output

As you can see, the rank 2 has been skipped because there were two employees with the same Salary and the result is ordered in ascending order by default.

4. What is Dense Ranking?
– DENSE_RANK() is similar to the RANK() function but it does not skip any rank, so if there are two equal values then both will be termed as 1, the third value will be termed as 3 and not 2.

Syntax:-
SELECT *, DENSE_RANK() OVER (PARTITION BY Salary ORDER BY Salary) as Row_Num
FROM Employee

Output:-

5. What is NTILE() function?
-NTILE() is similar to percentile NTILE(3) will divide the data in 3 parts.

SELECT *, NTILE() OVER (ORDER BY Salary) as Ntile
FROM Employee

The number of rows should be 6/3 = 2, therefore we need to divide the 2 rows for each percentile

6. How to get the second highest salary from a table?
Select MAX(Salary)
from Employee
Where Salary NOT IN (SELECT MAX(Salary) from Employee)

7. Find the 3rd Maximum salary in the employee table
-Select distinct sal
from emp e1
where 3 = ((select count(distinct sal) from emp e2 where e1.sal <= e2.sal);

8. Get all employee detail from EmployeeDetail table whose “FirstName” not start with any single character between ‘a-p’
– SELECT *
FROM EmployeeDetail
WHERE FirstName like ‘[^a-p]%’

9. How to fetch only even rows from a table?
-The best way to do it is by adding a row number using ROW_NUMBER() and then pulling the alternate row number using row_num%2 = 0

Suppose, there are 3 columns in a table i.e. student_ID, student_Name, student_Grade. Pull the even rows

SELECT *
FROM ( SELECT *, ROW_NUMBER() OVER (ORDER BY student_ID) as row_num FROM student) x
WHERE x.row_num%2=0

10. How to fetch only odd rows from the same table?
-Simply apply the x.row_num%2 <> 0 to get the odd rows

SELECT *
FROM ( SELECT *, ROW_NUMBER() OVER (ORDER BY student_ID) as row_num FROM student) x
WHERE x.row_num%2 <> 0

Let us know if you think I need to change any answer here.

Keep Learning 🙂

The Data Monk

The Data Monk services

We are well known for our interview books and have 70+ e-book across Amazon and The Data Monk e-shop page . Following are best-seller combo packs and services that we are providing as of now

1. YouTube channel covering all the interview-related important topics in SQL, Python, MS Excel, Machine Learning Algorithm, Statistics, and Direct Interview Questions
   Link – The Data Monk Youtube Channel
   
2. Website – ~2000 completed solved Interview questions in SQL, Python, ML, and Case Study
   Link – The Data Monk website
   
3. E-book shop – We have 70+ e-books available on our website and 3 bundles covering 2000+ solved interview questions. Do check it out
   Link – The Data E-shop Page
4. Instagram Page – It covers only Most asked Questions and concepts (100+ posts). We have 100+ most asked interview topics explained in simple terms
   Link – The Data Monk Instagram page
5. Mock Interviews/Career Guidance/Mentorship/Resume Making
   Book a slot on Top Mate

The Data Monk e-books

We know that each domain requires a different type of preparation, so we have divided our books in the same way:

1. 2200 Interview Questions to become Full Stack Analytics Professional – 2200 Most Asked Interview Questions
2.Data Scientist and Machine Learning Engineer -> 23 e-books covering all the ML Algorithms Interview Questions
3. 30 Days Analytics Course – Most Asked Interview Questions from 30 crucial topics

You can check out all the other e-books on our e-shop page – Do not miss it

For any information related to courses or e-books, please send an email to [email protected]