n this data, variables are stored in rows instead of columns. The different modes of transportation $($commuter

rail, bus, subway, boat, $...)$ are variables, providing information about each month$$s average ridership. The

months themselves are observations$\mathrm{.}2$ You can tell which is which because as you go through time, the month

changes, but the modes of transport offered by the T do not.

As is customary, you want to represent variables in columns rather than rows.

$1.$ Pivot the rows and columns of the mbta data so that all columns are variables of the data. This

should result in $3$ columns $-$ mode, date, and number of riders in thousands $($thou$\_$riders$).$

$2.$ What are the new dimensions of this data?

mbta $<-$ mbta $\%>\%$

pivot$\_$longer$(\_\_\_\_\_\_\_\_\_\_)$ # Pivot the rows and columns of the mbta data so that all

# columns are variables of the data. This should result in

# $3$ columns $-`$mode$`,`$date$`,$ and number of riders in

# thousands $(`$thou$\_$riders$`).$

$\_\_\_\_($mbta$)$ # Now what is the dimensions of this new data frame