10 Coding Questions Frequently Asked In Data Science Interviews

by Sayantani Sanyal

October 29, 2021

Data science is an emerging field in the tech world. When interviewing for the Data Scientist role, the industry hiring experts frequently asks questions related to SQL, Python, computer fundamentals, and other related areas. Hiring managers ask coding questions because data science is a highly technical field that requires the collection, cleaning, and processing of data to ensure that useful information can be gleaned from it. Coding skills can help data scientists collaborate with different stakeholders and projects and work closely with engineers to solve complex problems. In this article, we list the 10 most frequently asked coding questions in data science interviews.

• When can you use a subquery in the WHERE clause?

Subqueries in the WHERE clause help qualify a column against rows. This is useful for retrieving information from different tables. For example, a subquery displays the number of departments on the third floor, while the outer query retrieves the names of employees who work on the third floor.

• How are data analysis libraries used in Python?

One of the many reasons Python is a popular data science programming language is its large collection of data analysis libraries. These libraries include functions, tools, and methods for managing and analyzing data. There are also different libraries to perform other data functions such as data visualization and data mining.

• Describe JOIN

JOIN is an SQL operation performed to establish a connection between two or more database tables based on the corresponding columns, thereby creating a relationship between the tables. There are also different types of JOIN. Most complex queries in an SQL database management system involve JOIN commands.

• How is a negative index used in Python?

Negative indexes are used in Python to evaluate and index lists and arrays from the end, counting backwards. This means that the index value of -1 gives the last element and the index value of -2 describes the penultimate element of an array. The negative begins where the painting ends.

• Do you know the data manipulation language?

Data manipulation refers to the process of adjusting data to make it organized and easier to read. Data manipulation language is the type of programming language that adjusts data by inserting, deleting, and modifying data in a database, such as to cleanse or map data.

• Why do you think R is used in data visualization?

R is used in data visualization because it has several built-in functions and libraries that facilitate data visualizations. These libraries include ggplot2, brochure, lattice, and others. R helps in exploratory data analysis as well as functional engineering. Additionally, customizing graphics is easier in R than in Python.

• What are the main advantages of using window functions in SQL?

The main advantage of using window functions over regular aggregate functions is that window functions do not cause rows to be grouped into a single output row. The row can keep its separate identities and an aggregate value will be added to each row.

• Name the different built-in data types used in Python?

In Python, data types are used to classify and categorize data. The different built-in data types are Number, String, Tuple, Range, List, Set, and Dictionary.

• Discuss the decision tree algorithm.

A decision tree algorithm is a popular supervised machine learning algorithm, which is mainly used for regression and classification. It allows a data set to be broken down into smaller subsets. A decision tree algorithm can handle both categorical and numeric data.

• Explain the eigenvalue and the eigenvector.

Eigenvectors are used to understand linear transformations. Data scientists need to calculate the eigenvectors of a covariance matrix or correlation. While the eigenvalues ​​are the directions to use the acts of linear transformation by compressing, flipping or stretching.

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