There are many ways to organize data. Today we learn one way: the "tidy data" format. It is rather simple, but deceptively powerful.

1. Each variable forms a column.
2. Each observation forms a row.
3. Each type of observational unit forms a table.

The third point means we don't mix apples and oranges, keep apples together with apples.

This slide added on Tue 10/4:

1. Each observation forms a row. In other words, each row corresponds to a single observational unit
2. Each variable forms a column:
   • Some of the variables may be used to identify the observational units. For organizational purposes, it's generally better to put these in the left-hand columns
   • Some of the variables may be observed values associated with each observational unit
3. Each type of observational unit forms a table.

This is just a spreadsheet!

But we are very strict about the previous three rules.

The nycflights13 package contains information about all flights that departed from NYC (e.g. EWR, JFK and LGA) in 2013: 336,776 flights in total. To help understand what causes delays, it also includes a number of other useful datasets:

• weather: hourly meterological data for each airport
• planes: construction information about each plane
• airports: airport names and locations
• airlines: translation between two letter carrier codes and names