Csv

03 Jan, 2025

Most Frequently asked Interview Questions of csv(2024)

A CSV (Comma-Separated Values) file is a simple text-based data format used to store tabular data, where each line represents a record, and each field in the record is separated by a comma. It is commonly used for importing and exporting data between applications, such as spreadsheets and databases.

03 Jan, 2025

Most Frequently asked Interview Questions of csv

When working with CSV files, various programming languages offer libraries and tools to read, write, and manipulate CSV data efficiently. Below are some popular libraries and tools for processing CSV files in Python and other programming languages.

03 Jan, 2025

Most Frequently asked csv Interview Questions (2024)

When dealing with large CSV files, performance can become an issue, particularly in terms of memory usage and processing time. Optimizing how you read large CSV files in Python is crucial for handling big data efficiently. Here are several strategies to optimize reading large CSV files:

03 Jan, 2025

Most Frequently asked csv Interview Questions and Answers

The `csv` module in Python provides functionality for reading from and writing to CSV (Comma Separated Values) files. It is a part of Python’s standard library and offers a simple way to handle CSV data, which is a common format for data exchange.

03 Jan, 2025

Most Frequently asked csv Interview Questions

Processing CSV files in a distributed system or big data environment involves several challenges due to the size and scale of the data. These challenges include handling large volumes of data, managing parallelism, ensuring fault tolerance, and optimizing performance. The tools and techniques used to process CSV files in such environments are designed to handle these challenges efficiently.

30 Dec, 2024

Most Frequently asked dataframe Interview Questions (2024)

A DataFrame is a two-dimensional, size-mutable, and potentially heterogeneous tabular data structure in pandas, which is a widely used data analysis and manipulation library in Python. It is similar to a table in a database or an Excel spreadsheet, where data is organized in rows and columns. Each column can hold different data types (e.g., integers, floats, strings), making it more flexible and powerful than a regular 2D array.

28 Dec, 2024

Most Frequently asked pandas Interview Questions (2024)

Pandas is an open-source data manipulation and analysis library for Python. It provides fast, flexible, and expressive data structures, such as DataFrames and Series, that make working with structured data (e.g., tables, time-series data, CSV files, etc.) easy and efficient. Pandas is particularly well-suited for data wrangling, data cleaning, manipulation, and analysis.