show python codes for $4\mathrm{.}1$ to $4\mathrm{.}7$

Consider the data provided in the streaming tutorial $($namely users.csv$)$ alongside orders data $($namely orders.csv$).$ Combine these $2$ input files in order to provide insights into the purchasing behaviours of the retailer$$s customers.

$4\mathrm{.}1)$ Join the input files as streams using CoGroupByKey. $(1)$

$4\mathrm{.}2)$ Perform a transformation that determines the average number of orders for female and male customers, respectively. Output the result as text in the notebook. $(3)$

$4\mathrm{.}3)$ Verify the result of Question $4\mathrm{.}2$ using Python Pandas. $(1)$

$4\mathrm{.}4)$ Duplicate the code of previous question $($in a new cell$)$ and split your pipe to produce$/$emit the total number or orders processed as an additional text output $($i$.$e$.$ output the number of orders processed as well the average orders for female and male customers$).(2)$

$4\mathrm{.}5)$ Generate a graph $($using the Beam library$)$ of your pipeline.

$4\mathrm{.}6)$ Determine the total number of orders placed by male and female customers in the age groups $[18-27),[28-37),[37-46),[46-55).(3)$

$4\mathrm{.}7)$ Modify the pipeline$/$directed$-$acyclic$-$graph $($DAG$)$ of Question $4\mathrm{.}6$ to display the total number of yams purchased across the genders within the $[18-27),[28-37)$ age groups. $(3)$