Gain insights into data manipulation, analysis, and visualization with R. Learn statistical concepts, create insightful visualizations, and empower decision-making to excel in data-centric roles.

tarball.tar.gz

R_lang

This course delves into data manipulation, analysis, and visualization with R. It demonstrates the power of R as open-source statistical software, unlocking valuable insights for decision-making across diverse fields.

You'll begin by mastering the basics of R programming, fundamental data structures in R, and file management. You will learn fundamental statistical concepts such as hypothesis testing and regression analysis. You will also learn to leverage well-structured data for creating insightful visualizations using R's robust graphics libraries.

After completing this course, you'll confidently approach data-driven challenges. With proficiency in R, you can efficiently manipulate and analyze data, positioning yourself as a sought-after asset in data-centric roles. Your ability to interpret statistical results and create compelling data visualizations will empower improved decision-making, paving the way for new opportunities for career growth and success across various industries.

Introduction to Data Analysis and Visualization with R

## Features
A pie chart is a circular statistical graphic, which is divided into slices to illustrate numerical proportions. Each slice in a pie chart represents a proportion or percentage of the whole. We use pie charts to visualize the relative sizes of different categories, such as market shares, survey results, or budget allocations.  

For example, a pie chart is a good option to represent the time we spend on different daily activities. We can show the share of each activity in a day, such as sleeping, eating, studying, and working out. 


# Features
A pie chart is a circular statistical graphic, which is divided into slices to illustrate numerical proportions. Each slice in a pie chart represents a proportion or percentage of the whole. We use pie charts to visualize the relative sizes of different categories, such as market shares, survey results, or budget allocations.  

For example, a pie chart is a good option to represent the time we spend on different daily activities. We can show the share of each activity in a day, such as sleeping, eating, studying, and working out. 


Learn how to generate pie charts and explore their best use cases.

Getting Started

File Management

Data Structures

Data Cleaning

Statistical Analysis

Data Transformation

Data Visualization

Conclusion

Evaluation

Netflix Shows

Pie Charts

Features