Produce a Python Program using the provided data, 'Broken$\_$Hill$\_$Solar$\_$Radiation. which contains the solar radiation data from Broken Hill Airport, during January and February $2023.$The daily values of Solar Radiation $($MJ$/$sq m$)$ were obtained from BOM $($Brocken hill airport$)$ Prior to starting Check the January $2023$ and February $2023.$Input:

Write a Python program that reads the data of the dates and solar radiation values into two separate lists.

Output:

$$The program must display the dates having the maximum and minimum solar radiation values. In addition, the program must display the average solar radiation value for each month and shows the month that Broken Hill has a higher solar radiation value.

Sample Output:

The month of $\_\_\_\_\_\_\_\_\_\_\_\_\_$ has the maximum solar radiation value of $\_\_\_\_\_\_\_\_\_\_\_\_\_\_.$

The month of $\_\_\_\_\_\_\_\_\_\_\_\_\_\_$ has the minimum solar radiation value of $\_\_\_\_\_\_\_\_\_\_\_\_\_\_.$

$($this is for both months$)$

The average solar radiation value of January is $\_\_\_\_\_\_\_\_\_\_\_\_\_\_$

The average solar radiation value of February is $\_\_\_\_\_\_\_\_\_\_\_\_\_\_$

Broken Hill Airport has higher solar radiation in $\_\_\_\_\_\_\_\_\_\_\_\_\_\_.$

$$

$$Coding requirements:

$$ Added comments to top of code with name, date and purpose of program.

$$ The program must use lists, strings and built$-$in list functions to complete the task.

$$ The program should include user defined functions to modularise the code.

$$ The program must include exception handling to handle IOError exception. $2023-01-1,28\mathrm{.}73$

$2023-01-2,26\mathrm{.}03$

$2023-01-3,31\mathrm{.}79$

$2023-01-4,31\mathrm{.}75$

$2023-01-5,31\mathrm{.}67$

$2023-01-6,31\mathrm{.}63$

$2023-01-7,31\mathrm{.}59$

$2023-01-8,26\mathrm{.}63$

$2023-01-9,27\mathrm{.}6$

$2023-01-10,22\mathrm{.}24$

$2023-01-11,3\mathrm{.}94$

$2023-01-12,22\mathrm{.}29$

$2023-01-13,25\mathrm{.}14$

$2023-01-14,23\mathrm{.}82$

$2023-01-15,30\mathrm{.}49$

$2023-01-16,27\mathrm{.}25$

$2023-01-17,28\mathrm{.}52$

$2023-01-18,9\mathrm{.}32$

$2023-01-19,30\mathrm{.}68$

$2023-01-20,29\mathrm{.}16$

$2023-01-21,30\mathrm{.}55$

$2023-01-22,29\mathrm{.}87$

$2023-01-23,26\mathrm{.}91$

$2023-01-24,23\mathrm{.}84$

$2023-01-25,30\mathrm{.}08$

$2023-01-26,26\mathrm{.}71$

$2023-01-27,29\mathrm{.}85$

$2023-01-28,25\mathrm{.}91$

$2023-01-29,4\mathrm{.}21$

$2023-01-30,14\mathrm{.}65$

$2023-01-31,29\mathrm{.}73$

$2023-02-1,29\mathrm{.}57$

$2023-02-2,29\mathrm{.}47$

$2023-02-3,21\mathrm{.}75$

$2023-02-4,29\mathrm{.}27$

$2023-02-5,29\mathrm{.}16$

$2023-02-6,29\mathrm{.}02$

$2023-02-7,28\mathrm{.}87$

$2023-02-8,28\mathrm{.}72$

$2023-02-9,28\mathrm{.}56$

$2023-02-10,27\mathrm{.}79$

$2023-02-11,28\mathrm{.}21$

$2023-02-12,28\mathrm{.}05$

$2023-02-13,26\mathrm{.}92$

$2023-02-14,27\mathrm{.}73$

$2023-02-15,27\mathrm{.}52$

$2023-02-16,27\mathrm{.}39$

$2023-02-17,27\mathrm{.}15$

$2023-02-18,26\mathrm{.}99$

$2023-02-19,26\mathrm{.}87$

$2023-02-20,26\mathrm{.}71$

$2023-02-21,26\mathrm{.}47$

$2023-02-22,26\mathrm{.}24$

$2023-02-23,25\mathrm{.}06$

$2023-02-24,23\mathrm{.}98$

$2023-02-25,20\mathrm{.}83$

$2023-02-26,24\mathrm{.}84$

$2023-02-27,25\mathrm{.}52$

$2023-02-28,24\mathrm{.}71$