Part $2-$ more dplyr

I have uploaded a data set called dr$4.$ Rdata. It contains the dates that fictional users visited a fictional website. The

website is able to track if the same user visited the site more than once. For the particular date range, the site had

$395$ visitors, and $130$ of them visited more than once. Some of them $(13$ people$)$ visited the site $5$ times.

Using dplyr$,$ find the average time between repeated visits to the site.

You will want to find the total average.

Be careful when calculating this.

For example, the first user to visit the site more than once $($row $2,,$YPELGRZNOQUTNPOH$)$ visited on $6-29,7-27,$

$8-3,$ and $8-11.$ The time difference for the repeated visits are: $28$ days, $7$ days, and $8$ days, respectively, for an average

of $14\mathrm{.}33$ days.

The next user with repeated visits is row $3($SNTCUXUDIHCCSPJA$).$ This person visited on $6-15$ and $8-17,$ a

difference of $63$ days.

If your data set had only these two rows, the average time between visits would be $\frac{28+7+8+63}{4}=26\mathrm{.}5$

days. It is not $\frac{14\mathrm{.}33+63}{2}=38\mathrm{.}66$ days.

When I first attempted this, I used filter$(),$ mutate$(),$ rowwise$(),$ ungroup$(),$ and summarise$().$ Upon further

review, I realized that it is entirely possible to complete this task using only filter $()$ and mutate$()$ commands. I

do not care what combination of commands you use. I do care that you get the correct final result.

Make sure your final output shows the desired average number of days between visits.