R Practice 🧮

Overview 📚

The R Practice.ipynb notebook provides a comprehensive set of challenging interview questions and answers related to the R programming language. This resource is designed to help individuals prepare for advanced R programming interviews by covering a wide range of topics and concepts.

Contents 🗂️

• Introduction to R: Basic concepts and differences with other programming languages.
• Data Manipulation: Using dplyr, tidyr, and data.table for data processing.
• Statistical Analysis: Performing regression analysis, PCA, and other statistical methods.
• Data Visualization: Creating plots with ggplot2 and interactive plots with plotly.
• Advanced Topics: Managing large datasets, debugging, and working with custom functions.
• Packages and Libraries: Using caret, shiny, lubridate, and other essential packages.

Notebook Details 📑

• File Name: R Practice.ipynb
• Description: A Jupyter notebook containing a curated list of 50 tough R interview questions along with their detailed answers.
• Image: R.jpeg - A visual representation related to R programming.

Key Sections 🔑

1. Introduction to R: Overview of R, its unique features, and differences from other languages.
2. Data Handling and Manipulation: Techniques for managing and manipulating data using various packages.
3. Statistical Methods: Implementation and explanation of regression analysis, PCA, and more.
4. Visualization: Creating static and interactive visualizations using ggplot2 and plotly.
5. Advanced Topics: Handling large datasets, debugging, and performance optimization.
6. Package Usage: Practical examples of using important R packages.

Usage 🚀

To get started with the notebook:

1. Clone or download this repository.
2. Open the R Practice.ipynb file in Jupyter Notebook or a compatible environment.
3. Follow along with the questions and answers to enhance your R programming skills.

Contribution 🤝

If you have suggestions for additional questions or improvements, please feel free to open an issue or submit a pull request.

License 📝

This repository is licensed under the MIT License.

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For more information on R programming and advanced topics, refer to the official R documentation.

Happy Coding! 🚀