B$\mathrm{.}5-$ Franchises with Best Win$/$Loss Ratios

In this subsection, we will identify the $10$ franchises who have the best win$/$loss ratios.

Sort the franchise$\_$summary DataFrame in decreasing order by WL$\_$ratio. Show that first $10$ rows of the

following columns $($in this order$)$: franchID, franchName, seasons, first$\_$year, last$\_$year,

WL$\_$ratio.

B$.6-$Win$/$Loss Ratios in Recent Years

In this subsection, we will calculate the win$/$loss ratio for each of the current franchises during the period since

$1998($which was when the newest franchises were added$).$

Apply a filter to the teams DataFrame keeping only records from $1998$ or later. Then apply transformations to

calculate the Win$/$Loss Ratio for each team currently active. You will repeat many $($but not all$)$ of the steps

from Subsection B$\mathrm{.}2.$ Sort the resulting DataFrame in increasing order by win$/$loss ratio and convert it to a

Pandas DataFrame.

Display the result as a horizontal bar chart. Use the same specifications stated in Subsection B$\mathrm{.}4,$ except that

the horizontal axis should represent Win$/$Loss Ratio.