In this post, we’ll look at the pandas interview questions and answers. This will help you prepare for the upcoming pandas interview and give you a head start on how to approach them. If you are preparing for the pandas data science interview, then you must be familiar with the concepts like Pandas Data Frame and Pandas Series. So, in this post, we’ll look at some of the pandas interview questions and answers that are based on these two. Pandas Interview Questions and Answers:
1. What is a pandas data frame?
A pandas data frame is a tabular data structure that stores data in rows and columns. It provides the functionality to manipulate, transform, join, filter, and summarize data. This data structure is very useful for analyzing, manipulating, and visualizing large amounts of data. Pandas data frames are created using the PD.DataFrame() function which takes a list of series as an argument. Pandas data frame is a data structure that is based on two-dimensional arrays. These arrays can store any type of data.
2. What are the advantages of using pandas?
Pandas is a free, open-source library for Python. The library has been built with the aim of making data manipulation easy and intuitive. With pandas, you can easily manipulate data in tables, perform statistical analysis, and visualize your data. Some of the advantages of using pandas are: • It’s easy to use and learn. • It makes the code compact and understandable. • It is easy to create custom functions. • It allows users to use a wide variety of data types.
3. What is the difference between a pandas data frame and a python dictionary?
The main difference between a pandas data frame and a dictionary is that data frames are tabular data structures, while dictionaries are unordered associative data structures. Also, data frames support row indexing whereas dictionaries do not.
4. How do pandas save data?
Data frames are used to store tabular data. When you load a data frame from a file or database, it will create a new data frame object. This new data frame is created with the columns and rows of the input data.
5. What is the difference between a pandas Series and a Pandas DataFrame?
A series is a special kind of data frame that is indexed by its own index. It is used for time series analysis.
6. How do I convert a Pandas DataFrame to a CSV file?
You can use the to_csv() method on a data frame to write it to a csv file.
7. How do I read data from a CSV file in pandas?
Pandas have built-in functionality for reading data from CSV files.
8. Describe how you will get the names of columns of a DataFrame in Pandas
The names of the column that make up a data frame can be obtained using the colname()function.
9. What is monkey patching in Python?
Monkey patching is a technique for modifying the behavior of existing classes in Python. It is a way to extend the functionality of a class without having to write a new class.
10. Which tool in Python will you use to find bugs if any?
Pytest is a modern, open-source unit testing library for Python. It’s a fork of a nose and has a lot of the same features. It also has some additional features like being able to run tests in parallel, or running them in debug mode.