Data, Code & RStudio

Lab 1A

Directions: Follow along with the slides and answer the questions in red font in your journal.

Welcome to the labs!

  • Throughout the year, you'll be putting your data science skills to work by completing the labs.
  • You'll learn how to program in the R programming language.
    • The programming language used by actual data scientists.
  • Your code will be written in RStudio which is an easy to use interface for coding using R.

So let's get started!

  • The data for our first few labs comes from the Centers for Disease Control (CDC)
    • The CDC is a federal institution that studies public health.
  • Type these two commands into the your console:
data(cdc)
View(cdc)
  • Describe the data that appeared after running View(cdc):
    • Who is the information about?
    • What sorts of information about them was collected?

Data: Variables & Observations

  • Data can be broken up into two parts.
    1. Observations
    2. Variables
  • If need be, re-type the command you used to View your data. Then answer the following:
    • How are our observations represented in our data?
    • What does the first column tell us about our observations?
    • How often did our first observation wear a seatbelt while riding in a car?

Uncovering our Data's Structure

  • Now that we've looked at our data, let's look at how RStudio is organized.
  • RStudio's main window is composed of four panes
  • Find the pane that has a tab titled Environment and click on the tab.
    • This pane contains a list of everything that's currently available for R to use.
    • Notice that R knows we have our cdc data loaded.
  • How many students are in our cdc data set?
  • How many variables were measured for each student?

Type the following commands into the console

dim(cdc)
nrow(cdc)
ncol(cdc)
names(cdc)
  • Which of these functions tell us the number of observations in our data?
  • Which of these functions tell us the number of variables?

First Steps

  • Typing commands into the console is your first step into the larger world of programming or coding (terms which are often used interchangeably).
  • Coding is all about learning how to send instructions to your computer.
    • We call the way we speak to the coding language, syntax.
  • Capitalization, spelling and punctuation are REALLY important.

Syntax matters

  • Run the following commands and write down what happens after each. Which does R understand?
Names(cdc)
NAMES(cdc)
names(cdc)
names(CDC)

R's most important syntax

function (y~x, data = ____ )

  • Search through the different panes. Find and then click on the Plots tab.
    • To get back to the slides, find and then click on the Viewer tab.

Syntax in action

function (y~x, data = ____ )

  • Which one of these plots would be useful for answering the question: Is it unusual for students in the CDC dataset to be taller than 1.8 meters?
histogram(~height, data = cdc)
bargraph(~drive_text, data = cdc)
xyplot(weight~height, data = cdc)
  • Do you think it's unusual for students in the data to be taller than 1.8 meters? Why or why not?

On your own:

  • After completing the lab, answer the following questions:
    • What is public health and do we collect data about it?
    • How do you think our data was collected? Does it include every high school aged student in the US?
    • How might the CDC use this data? Who else could benefit from using this data?
    • Write the code to visualize the distribution of weights of the students in the CDC data with a histogram. What is the typical weight?
    • Write the code to create a barplot to visualize the distribution of how often students wore a helmet while bike riding. About how many students never wore a helmet?