R Tutorial: The counties dataset
Key Takeaways
This video tutorial covers the basics of using dplyr verbs, specifically select, filter, arrange, and mutate, to explore and transform the counties dataset from the 2015 United States Census in R.
Full Transcript
in this first chapter you'll learn to use for basic dir verbs to explore and transform a data set this course has some similarities to other data camp courses especially introduction to the tie Devers and if you've taken those courses this material might be review the for verbs you'll learn our select filter arrange and mutate by the end of this chapter you'll be comfortable using these verbs in various combinations throughout this course you're going to work with a real data set where you'll not only be able to practice the deeply our transformation verbs but also learn how to explore and draw insights from data this particular data set is from the 2015 United States Census a C is one of 50 regions within the United States such as New York California or Texas a county is a sub region of one of those states like Los Angeles County in California you can access this data by typing counties into your R console this dataset has loads of information but don't worry you're only going to work with a few variables at a time this table includes information about people living in each county such as the population the unemployment rate their income and their racial and gender breakdown so there are a lot of questions we can ask of our data there are 40 variables in this data and only the first few are previewed in the table if you want to see a few values from all the columns you can use glimpse datasets often come with more variables than you need and we're not going to need all of them let's collect only a few variables the state the county the total population and the unemployment rate we can do this using the Select verb select extracts only particular variables from a data set in this case you can type counties then the pipe operator then select then the variables of interest sometimes you want to keep the data you've selected you can use assignment to create a new table recall that you use the arrow operator written as less than - for this this gives you a new table called two counties underscore selected you can print that data set just as you did the first one let's practice
Original Description
Want to learn more? Take the full course at https://learn.datacamp.com/courses/data-manipulation-with-dplyr at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work.
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In this first chapter, you'll learn to use four basic dplyr verbs to explore and transform a dataset.
This course has some similarities to other DataCamp courses, especially Introduction to the Tidyverse, and if you've taken those courses, this material might be review.
The four verbs you'll learn are select(), filter(), arrange(), and mutate(). By the end of this chapter, you'll be comfortable using these verbs in various combinations.
Throughout this course, you're going to work with a real dataset, where you'll not only be able to practice the dplyr transformation verbs but also learn how to explore and draw insights from data. This particular dataset is from the 2015 United States Census.
A state is one of 50 regions within the United States, such as New York, California, or Texas. A county is a subregion of one of those states, like Los Angeles county in California.
You can access this data by typing counties into your R console.
This dataset has loads of information, but don't worry, you're only going to work with a few variables at a time! This table includes information about people living in each county, such as the population, the unemployment rate, their income, and their racial and gender breakdown, so there are a lot of questions we can ask of our data.
There are 40 variables in this data, and only the first few are previewed in the tibble.
If you want to see a few values from all the columns, you can use glimpse().
Datasets often come with more variables than you need, and we're not going to need all of them. Let's collect only a few variables: the state, the county, the total population, and the unemployment rate.
We can do this using the select() verb. select() extracts only particular variables from a dataset. In this c
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