In Python, Download the 'taxis' dataset from Seaborn sns$.$load$\_$dataset$($taxis$\text{'})$ and load it into a Pandas DataFrame.

a$.$ Load the 'taxis' dataset into a Pandas DataFrame.

b$.$ Display the first $5$ rows of the dataset.

c$.$ Check for missing values and comment about how would you handle them appropriately.

a$.$ Calculate the average trip duration.

b$.$ Visualize the distribution of trip fares using a histogram.

a$.$ Create a new column $\text{'}$is$\_$tipped' representing if there was any tip for the taxi ride. Display how many cash trips tipped the taxi driver.

b$.$ Display the average tip amounts based on the color of the taxi and number of passengers within a pivot table.

a$.$ List the top $5$ busiest pickup locations.

b$.$ Plot all the days in a week with number of total rides for each day. Use pickup day column for calculation.!

c$.$ Find which day of the week has the highest average tip amount.