学習内容

Understand the principles of effective data visualization in R.

Combine multiple plots and arrange them for comparative analysis.

Create and customize basic plots such as scatter plots, bar charts, histograms, and boxplots.

Export and share your visualizations for reports and presentations.

Leverage color, shape, and size to enhance data interpretation.

コース内容

Master the foundational techniques of data visualization in R. This course guides you through the most important plotting tools and concepts, helping you create clear, insightful, and publica…

Explore the essential plotting tools and visualization strategies in R, focusing on practical skills for creating and customizing a wide range of charts and graphs.

Introduction to Data Visualization in R

Challenge: Introduction to Data Visualization

Scatter Plots: Visualizing Relationships

Challenge: Scatter Plots

Bar Charts: Comparing Categories

Challenge: Bar Charts

Histograms: Visualizing Distributions

Challenge: Histograms

Boxplots: Summarizing Distributions

Challenge: Boxplots

Customizing Plots: Colors, Labels, and Legends

Arranging Multiple Plots

Challenge: Arranging Multiple Plots

Exporting Plots: Saving Your Work

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R Introduction

Gain a solid understanding of R, one of the most widely used languages for data analysis. Explore fundamental data types and one-dimensional values, then advance to multi-dimensional structures, including matrices, data frames, and lists. Build the skills needed to apply R effectively in statistical analysis and data-driven decision-making.

Data Analysis with R

Gain practical experience in data analysis with R by learning how to clean, transform, and visualize datasets. Explore essential workflows such as selecting and filtering data, handling missing values, and summarizing results. Build confidence in preparing data for insights, reporting, and deeper statistical exploration.

Control Flow in R

Master the essentials of control flow in R, including conditional statements, loops, and the powerful apply family of functions. This course is designed for beginners and will guide you through practical, real-world examples to help you write efficient and readable R code.

R for Data Scientists

Master practical data science in R by learning data cleaning, modeling, evaluation, and machine learning workflows through hands-on code. Build fluency with R syntax, functions, and outputs for real-world data science tasks.

R for Economists

Learn how economists use R to analyze macroeconomic and market data, build econometric models, and interpret results for policy and market decisions. Focus on regression, time series, and forecasting using real economic datasets.

Working with Data Structures in R

Master the essential data structures in R, including lists, data frames, and factors. Learn how to create, manipulate, and analyze data using R's powerful tools, with engaging explanations and real-world challenges designed for beginners.

Visualization and Reporting with R

Master the essentials of data visualization and reporting in R. Learn to create compelling graphics, perform exploratory data analysis, and communicate insights effectively using R's powerful tools.

R Introduction

Gain a solid understanding of R, one of the most widely used languages for data analysis. Explore fundamental data types and one-dimensional values, then advance to multi-dimensional structures, including matrices, data frames, and lists. Build the skills needed to apply R effectively in statistical analysis and data-driven decision-making.

Data Analysis with R

Gain practical experience in data analysis with R by learning how to clean, transform, and visualize datasets. Explore essential workflows such as selecting and filtering data, handling missing values, and summarizing results. Build confidence in preparing data for insights, reporting, and deeper statistical exploration.

Control Flow in R

Master the essentials of control flow in R, including conditional statements, loops, and the powerful apply family of functions. This course is designed for beginners and will guide you through practical, real-world examples to help you write efficient and readable R code.

R for Data Scientists

Master practical data science in R by learning data cleaning, modeling, evaluation, and machine learning workflows through hands-on code. Build fluency with R syntax, functions, and outputs for real-world data science tasks.

R for Economists

Learn how economists use R to analyze macroeconomic and market data, build econometric models, and interpret results for policy and market decisions. Focus on regression, time series, and forecasting using real economic datasets.

Working with Data Structures in R

Master the essential data structures in R, including lists, data frames, and factors. Learn how to create, manipulate, and analyze data using R's powerful tools, with engaging explanations and real-world challenges designed for beginners.

Visualization and Reporting with R

Master the essentials of data visualization and reporting in R. Learn to create compelling graphics, perform exploratory data analysis, and communicate insights effectively using R's powerful tools.

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Sherry Barnes-Fox

My first course was 4 hours, I did it in a few days, "nugget-style". The instructions are very clear and easy to understand. There is even a hint to help you get the answer. I love the learning style that is used, it engages me.

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The learning was progressive and made it easy to follow along and make progress. I could feel my skills increasing and building on each other as the course went along.

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Stephanie Chan

As I went through the first course of the Python track, I liked the way the course was lay out (in easy and digestible modules) with little exercises at the end of each concept.