MagicPin Associate Interview Questions and Answers

Q1. Tell me about your last company experience.
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Q2. Explain your role and responsibilities with more in debt so that can understand more of your weightage.
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Q1. SQL: left join, right join and inner join questions find out the latest entry for an user when they log in to a app Python: few basic questions on python like count the characters in a word. Linux: what co...read more
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Q1. Why data? Why Tokopedia? Talk about bachelor's thesis?
Ans. 
Data analysis is crucial for making informed decisions. Tokopedia's vast data provides a great opportunity for analysis. My bachelor's thesis focused on data-driven insights.
• Data allows for informed decision-making and insights.

• Tokopedia's extensive data provides a valuable opportunity for analysis.

• My bachelor's thesis delved into data-driven insights and analysis.
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Q1. Walkthrough bachelor's thesis
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SQL, excel, tableau , looker studio

Q1. What is your notice period.
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Send assignment doings MS Excel

Q1. Asked about the previous project
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Q2. What about your roles in previous company
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Q1. Difference between rank and dense rank
Ans. 
Rank assigns unique ranks to each distinct value, while dense rank does not leave gaps between ranks.
• Rank assigns unique ranks to each distinct value in a dataset

• Dense rank does not leave gaps between ranks, assigning consecutive ranks to values with the same rank

• For example, if values are 10, 20, 20, 30, then rank would be 1, 2, 2, 4 and dense rank would be 1, 2, 2, 3
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Q2. How will merge multiple file in python
Ans. 
Merge multiple files in Python using pandas.concat() or pd.merge() functions.
• Use pandas.concat() function to merge multiple files vertically (row-wise).

• Use pd.merge() function to merge multiple files horizontally (column-wise) based on a common column.

• Ensure that the files have compatible column names and data types before merging.

• Handle any missing or duplicate values appropriately during the merging process.

• Consider ...read more
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Q3. Data frame explain in detail
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A data frame is a two-dimensional data structure in which data is stored in rows and columns.
• Data frames are commonly used in programming languages like R and Python for data analysis.

• Each column in a data frame represents a variable, while each row represents an observation.

• Data frames can contain different types of data, such as numeric, character, and factor.

• Data frames can be created from various sources like CSV f
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