We can use the separate function to split these into separate columns. Right now, the first and last names are combined into one column. We can then name the data frame employee, indicate the column names as id, name and job title, and print the whole data frame. Our data contains employee information, including names and job titles. If you want to use the same data to follow along, check out the earlier reading. For our dataset, we are going to copy and paste some data to create our own data frame. You'll learn more about tribbles in a reading. But you could also make a tribble here since we're manually inputting the data. For this example, we'll create a standard data frame, so that we can test out other functions. To start, we'll create a data frame from scratch. Let's open RStudio Cloud and check them out. Luckily, the packages already downloaded into our library have some tools we can use to do just that. Coming up, we'll use the separate, unite and mutate functions to transform our data in R. Sometimes you need to be able to break up a variable across multiple columns or combine existing columns, or even add new values to your data frame. Now, let's talk about how to transform data. So far, we've started cleaning and now working with data in R. Learn about R Markdown for documenting R programming. Discover the options for generating visualizations in R. Gain an understanding of dataframes and their use in R. Explore the contents and components of R packages including the Tidyverse package. Explore the fundamental concepts associated with programming in R. Discover how to use RStudio to apply R to your analysis. Examine the benefits of using the R programming language.
Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources. You’ll discover how R lets you clean, organize, analyze, visualize, and report data in new and more powerful ways. This course will also cover the software applications and tools that are unique to R, such as R packages. You’ll find out how to use RStudio, the environment that allows you to work with R. In this course, you’ll learn about the programming language known as R. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs.
This course is the seventh course in the Google Data Analytics Certificate.
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