R Tutorial: The gapminder dataset

Want to learn more? Take the full course at https://learn.datacamp.com/courses/introduction-to-the-tidyverse at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- Hi, I'm Dave Robinson and I'll be your instructor. I'm a data scientist and I love using R to dive into a dataset and discover interesting things. This course will get you started on the path to exploring and visualizing your own data with the R programming language. This course introduces you To the tidyverse, a collection of data science tools within R for transforming and visualizing data. This is not the only set of tools in R, but it's a powerful and popular approach for exploring data. At every step, you'll be analyzing a real dataset called Gapminder. Gapminder tracks economic and social indicators like life expectancy and the GDP per capita of countries over time. The experience you gain in this example will help you in analyzing your own data. You'll learn to draw specific insights and Communicate them through informative visualizations with the ggplot2 package. This course is interactive: between the short videos, you'll complete exercises by typing in code, with help from us along the way. The The first code you'll write is to load two R packages, which is done by writing "library parenthesis, the name of the package, then end parenthesis". R packages are tools that aren't built into the language but were created later by other programmers. Each of them provides tools that you don't have to write yourself. The first package is gapminder, created by Jenny Bryan, which contains the dataset that you'll be analyzing. The second package is dplyr, created by Hadley Wickham, which provides step-by-step tools for transforming this data, such as filtering, sorting, and summarizing it. You type Gapminder to display the contents of the gapminder object, which is structured as a data frame. A data frame keeps rectangular data in rows and col