Top 25+ Pandas Interview Questions for Your Tech Interview

Pandas is a popular software library created to perform high-level data analysis and data manipulation in Python. Technical interview rounds at top companies often involve answering basic to advanced-level Panda interview questions and questions around other popular Python tools.

Pandas allows developers and data engineers to manipulate time series characteristics, tables, and other aspects by offering data structures and other advanced features to run complex data programs. Pandas interview questions that you can expect at Python interviews are typically around the tool’s features, data structures, and functions. In this article, we’ll look at some of these Panda interview questions.

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Let’s go ahead and look at some common Panda interview questions asked in technical interviews.

Here’s what we’ll cover:

• Top Pandas Interview Questions
• Advanced Pandas Interview Questions
• Panda Interview Questions for Data Scientists
• Pandas Coding Interview Questions
• FAQs on Panda Interview Questions

Top Pandas Interview Questions

In this section, we’ll look at the top Pandas interview questions to prepare you for the Python interview.

1. Which are the different types of data structures in Pandas?
2. What is a Series in Pandas?
3. What are DataFrames in Pandas?
4. Mention the core features of Pandas.
5. What is categorical data in Panda?
6. How do you create a copy of a given Series in Pandas?
7. How to add columns in Panda DataFrames?
8. How would you add and delete columns and rows in Pandas?
9. How will you iterate actions within a Pandas DataFrame?
10. What do you understand about the NumPy array?

Advanced Pandas Interview Questions

Let’s go ahead and look at some advanced Panda interview questions for your next Python interview. You can expect these questions in your tech interview if you're a senior Python developer.

1. How would you index a DataFrame using the indexing operator?
2. How would you index a DataFrame with the help of .loc[]?
3. How would you perform indexing through DataFrame.ix[]?
4. What do you understand by ReIndexing in Pandas?
5. What is Multiple Indexing in Pandas?
6. How do you set indexes in Pandas?
7. How do you reset indexes in Pandas?
8. What do you understand about Data Operations in Pandas?
9. How would you append new rows in DataFrames?
10. What is the Pandas ML package?

Pandas Interview Questions for Data Scientists

Data scientists and data engineers are often expected to be adept with data-oriented programming languages, particularly Python. In this section, we’ll look at some common Pandas interview questions for data scientists to help you understand the type of questions asked at data interviews.

1. How to create an empty DataFrame in Pandas?
2. How do you use range() and xrange() functions in Pandas?
3. How will you interchange values between two tables in Pandas?
4. What is categorical data in Pandas? Explain with an example.
5. Explain the GroupBy function in Pandas
6. How will you convert a DataFrame into a structured file format in Pandas?
7. Explain Data Aggregation in Pandas
8. How do you adjust time periods in Pandas?

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Pandas Coding Interview Questions

Pandas allows developers to perform certain functions by writing code. Below are some common Pandas Coding interview questions to practice for your upcoming interview.

1. How will you sort Dataframes in Pandas?
2. How will you convert a string to data in Pandas?
3. How would you find the missing elements in an array in Pandas?
4. How do you convert an int data type into a string data type in Pandas?
5. How would you convert a series into a DataFrame in Pandas?
6. How will you convert a NumPy array into a DataFrame in Pandas?
7. How will you compute the percentile of a numerical series in Pandas?

Practicing these Pandas interview questions will help you prepare for python interviews, data analyst interviews, and data science interviews.

FAQs on Pandas Interview Questions

Q1. Which programming language is the Pandas tool designed for?

Pandas is a data analysis and manipulation tool explicitly written for the Python programming language.

Q2. Which are some domain interviews where recruiters ask Panda interview questions?

Pandas interview questions are asked at domain interviews for data scientists, python software developers, data engineers, and data analysts.

Q3. What are Panda interview questions asked at Python interviews?

Panda interview questions are typically around indexing, Panda DataFrames, Panda data structures, and Panda functions.

Q4. Which are the data structures available with Pandas?

Pandas supports two main types of data structures - DataFrame and Series. DataFrames are two-dimensional data structures, while Series is a one-dimensional data structure.

Q5. What is NumPy in Pandas?

NumPy in Pandas is a built-in package used to perform numerical calculations and process elements in one-dimensional and two-dimensional arrays.

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