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Analytics Interview Questions | Day 1

Analytics Interview Questions
In this series we will try to solve as many questions as possible in 4 areas, SQL, Python, Machine Learning Algorithms, and Miscellaneous. All you need to do is to comment your answers below and the best answer will get an extra e-book for free 😛

You need to attempt these questions, put everything in one comment, we will evaluate and will announce the winner in the next day’s post

Analytics Interview Questions

Analytics Interview Questions

We will follow the below pattern:
– SQL (3 Questions)
– Python (2 Questions)
– Case Study (1 Question)
– Machine Learning and Statistics (2 Questions)

SQL

  1. There are two tables X and Y, X has a column A that contains 4 rows -1,-1,-1,-1. Y has a column B that contains -1,-1,-1 (Most asked interview question)
    How many rows will be there if we do X left join Y
  2. What is the use of partition in a table?
  3. What is the difference between the Drop and Delete table? (Meesho, OYO rooms)

Python

  1. What is a mutable and immutable data type? (Most Asked Questions)
  2. How do you read a CSV file in Python?
  3. What is the syntax of group by in Python ?

Case Study

  1. For a particular e-commerce company, there has been a decline in the number and value of items stored in the cart. Tell all the possible reasons for this decline?

Machine Learning Concepts

  1. What is the p-value? Explain in a very layman term with simple example
  2. What is correlation? Explain with simple example

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 nitinkamal132@gmail.com

About TheDataMonkGrand Master

I am the Co-Founder of The Data Monk. I have a total of 6+ years of analytics experience 3+ years at Mu Sigma 2 years at OYO 1 year and counting at The Data Monk I am an active trader and a logically sarcastic idiot :)

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Comments ( 2 )

  1. SQL
    1. 12 rows
    2. Partition is used in window functions, for doing aggregation or operations in a particular window. For example, rank() over(partition by customer) would organize the data customer wise and the rank operation will work customer window-wise.
    3. delete is used for manipulating data within a table whereas drop is used to delete an entire table from the schema.

    Python
    1. Mutable datatype is one in which the elements can be changed and immutable is one in which the elements or the structure cannot be changed. For example, a list is mutable – you can append, extend or pop elements in it. A tuple is immutable – you cannot make any changes to it.
    2. import pandas as pd
    file = pd.read_csv(‘file_name.csv’)
    3. for example, df is the name of the dataframe and col is the column by which we need to group our data.
    df.groupby(col).sum()

    Case Study
    Some clarification questions-
    1. What category do these items belong to? General or a particular category only?
    2. Were there any changes made (in the UI or otherwise) on the platform?
    3. What is the magnitude and timeline of the decline?
    4. Items stored in the cart – Does this mean that checkout has increased? Or they do not checkout at all?
    Reasons-
    1. External – A competitor has these items in a better price or quality, hence users are switching to them. Another possible reason is that the general demand of those items (if they are of a particular category), is dropping.
    2. Internal – Our delivery time. item price and quality are not upto the customers’ expectations.
    3. Internal – The path to checkout, till adding items to the cart, is not too clear to customers. Some UI related issue.

    Machine Learning Concepts
    2. Correlation, simply explained, shows the strength and direction of the relation between two numerical variables. For example, if the correlation between number of hours studied and marks scored is 0.8, it means that the more hours studied. more will be the marks scored (positive correlation).