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Lab 1A - Data, Code & RStudio

Lab 1A - Data, Code & RStudio

Directions: Follow along with the slides and answer the questions in bold in your IDS 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 R, 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 and Prevention (CDC), 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?