Python Interview Questions for Freshers 1. What is __init__? 2. What is the difference between Python Arrays and lists? 3. Explain how can you make a Python Script executable on Unix? 4. What is slicing in Python? 5. What is docstring in Python? 6. What are unit tests in Python...
It’s commonly employed in programming languages like Python to perform arithmetic operations on dates and times, facilitating tasks such as calculating intervals or scheduling events. 19. How can we convert DataFrame to an Excel file? To convert a DataFrame to an Excel file in Python, you can...
The Pandas library, in contrast to the NumPy library, which provides objects for multi-dimensional arrays, provides an in-memory two-dimensional table object called DataFrame.Discuss this Question 4. Amongst which of the following is true with reference to Pip in Python?Pip is a standard package...
77. You have a dataframe (df) with columns 'Age' and 'Salary', How would you calculate the average salary for each age group? average_salary_by_age = df.groupby('Age')['Salary'].mean() print(average_salary_by_age) Here we are grouping the dataFrame based on the ‘Age’ column ...
What are the main data structures in Python?50 XP List methods100 XP Operations on sets50 XP Storing data in a dictionary100 XP What are common ways to manipulate strings?50 XP String indexing and concatenation100 XP Operations on strings100 XP Fixing string errors in a DataFrame100 XP How ...
25. Quelle est la méthode pandas pour obtenir le résumé statistique de toutes les colonnes d'un DataFrame ? df.describe() Cette méthode renvoie des statistiques telles que la moyenne, les valeurs de percentile, min, max, etc. de chaque colonne du DataFrame. 26. Qu'entend-on par "roul...
One advantage of an interpreted language like Python is that it can be run on any platform with a Python interpreter installed. This makes Python a very portable language and one that is widely used in a variety of different applications, including web development, data analysis, machine learning...
Can PyMongo Load the Results of a Query as a Pandas DataFrame? PyMongoArrow Pandas DataFrames NumPy ndarrays Apache Arrow Tables. How Does Connection Pooling Work in PyMongo? EveryMongoClientinstance has a built-in connection pool for each server in your MongoDB topology. Connection pools open ...
Pandasis a powerful Python library for data analysis. In a nutshell, it's designed to make the manipulation and analysis of structured data intuitive and efficient. Key Features Data Structures:Offers two primary data structures:Seriesfor one-dimensional data andDataFramefor two-dimensional tabular da...
Let's start by importing necessary libraries and sine, cosine, arccosine, and radian functions. The next step is to merge the available DataFrame with itself on the user ID, session ID, and day of the session. Also, add the suffixes to IDs so you can distinguish between them. ...