Write a academic easy to understand python program that does the following:

$1.$ Reads the olympics.csv file. Column headers $($Name$,$ Sex, Age, Height, NOC, Year, Season, Sport, Medal$)-$ some of the boxes can have $"$NA$"$ if no existing data is present.

$2.$ Prints the medal count by decade of age.

$3.$ Prints the average overall age of medal winners of each medal type

You may not use any of the following pandas functions: group$\_$by$(),$ pivot$\_$table$(),$ read$\_$csv$().$

I would like the python code to be formatted as the example below:

Example:

import pandas as pd

import csv

class Vehicle:

def $\_\_$init$\_\_($self$,$ make, model, year, mpgCity, mpgHwy$)$:

self.make $=$ make

self.model $=$ model

self.year $=$ year

self.mpgCity $=$ int$($float$($mpgCity$.$strip$()))$

self.mpgHwy $=$int$($float$($mpgHwy$.$strip$()))$

def $\_\_$str$\_\_($self$)$:

return self.make $+""+$ self.model $+""+$ self.year $+""+$ str$($self$.$mpgCity$)+""+$ str$($self$.$mpgHwy$)$

mpgCity $=$ pd$.$Series$()$

mpgCityAvg $=$ pd$.$Series$()$

mpgHwy $=$ pd$.$Series$()$

mpgHwyAvg $=$ pd$.$Series$()$

with open$(\text{'}$mpg$.$csv$\text{'})$ as infile:

reader $=$ csv$.$reader$($infile$)$

reader.$\_\_$next$\_\_()$

for rec in reader:

veh $=$ Vehicle$($rec$[4],$ rec$[5],$ rec$[10],$ rec$[7],$ rec$[8])$

if veh.make in mpgCity:

mpgCity$[$veh$.$make$]=$ mpgCity$[$veh$.$make$]+1$

mpgCityAvg$[$veh$.$make$]=$ mpgCityAvg$[$veh$.$make$]+$ veh.mpgCity

mpgHwy$[$veh$.$make$]=$ mpgHwy$[$veh$.$make$]+1$

mpgHwyAvg$[$veh$.$make$]=$ mpgHwyAvg$[$veh$.$make$]+$ veh.mpgHwy

else:

mpgCity$[$veh$.$make$]=1$

mpgCityAvg$[$veh$.$make$]=$ veh.mpgCity

mpgHwy$[$veh$.$make$]=1$

mpgHwyAvg$[$veh$.$make$]=$ veh.mpgHwy

mpgCityAvg $=($mpgCityAvg $/$ mpgCity$).$agstype$($int$)$

print$($mpgCityAvg$.$to$\_$string$())$

print$(\text{'}---------------------------------------------------------------\text{'})$

mpgHwyAvg $=($mpgHwyAvg $/$ mpgHwy$).$astype$($int$)$

print$($mpgHwyAvg$.$to$\_$string$())$

df $=$ pd$.$DataFrame$(\{\text{'}$mpg city':mpgCityAvg, $\text{'}$mpg hwy$\text{'}$:mpgHwyAvg$\})$

print$($df$)$

mpgAvg $=(($mpgCityAvg $+$ mpgHwyAvg$)/2).$astype$($int$)$

print$($mpgAvg$)$

df$[\text{'}$mpg avg'$]=$ mpgAvg

print$($df$)$