• Screenshot your code AND console output as appropriate.
• Include the source code screenshot and the output screenshot as appropriate
• Remember to comment your code and think about code style.
• You will submit as a PDF. It shouldn’t have to be very long (as a guide, number of lines of code in
my answers is given in [brackets] for the longer questions)
• If you are unsure how to code a part, try to explain in pseudocode what you are trying to do for partial marks
• Remember to answer as much as you can for each part and question. Partial marks will be given if you are on the right track but haven’t finished a question.
Part A – Basic Python knowledge (worth 50% of Patch 1)
1. A for loop to print a times-table. For loops are useful when we know how many times we want to run a chunk of code. Write a for loop which prints out a number starting at 0 and counts up in 8’s (ie. the “eight times table”!). Print out up to and including 10 x 8. Format the output so each line reads :
X times 8 is Y
where X and Y depend on the current loop. [5%]
2. Translate the following pseudocode into equivalent Python code:
For x = count from 100 to 104 (inclusive) Print x
Create variable y, make y equal to value of x Double value of y
Print “y = “ [value of y] [10%]
Print “Finished.”
3. Using a while loop to produce a sequence of numbers. [Guide: my answer = 10 lines long] Create a while loop which will generate numbers in the Fibonacci sequence (see below), and stop after it has produced a value greater than 1000. You cannot use a list to do this!
Background: The Fibonacci sequence is a famous sequence of numbers which starts 0, 1, 1, 2, 3, 5,
8, 13, 21, 34…
It is generated by the following formula:
F0 = 0, F1 = 1
From then, Fn = Fn-1 + Fn-2 So, the first few terms are:
0 (Given by F0) 1 (Given by F1)
1 (Calculated by 0+1)
2 (Calculated by 1+1)
3 (Calculated by 1+2)
5 (Calculated by 2+3)
…. Note: you may have to handle the first two terms in a special way [15%]
4. A Lottery simulation. [Guide: my complete answer = 25 lines long] Your task is to use the random library to help simulate a lottery competition.
In this competition there are 10,000 tickets, each with a unique ID number. Every week there is one draw, and there are 10 winners (ie. 10 winning numbers are picked).
Each ticket is identified by a unique integer number between 1 and 10,000. In this lottery, a ticket CAN win twice (unusually!), i.e. we replace a ticket back in the draw after it has been pulled out.
a) Write a function which takes as a parameter a ticket ID number, and simulates a lottery draw by picking 10 random winners, and returns True if the specified ticket is a winner, and False otherwise (True and False are Boolean datatypes in Python)
b) Use this function to simulate a million (ie. 1,000,000) lottery draws. Assume each time a different ticket is purchased. How many times did you win in this simulation?
c) Discuss the following two points:
i. Do you think it makes a difference if the person buys a different ticket number each week, or if they keep the same number for the million draws? (use your simulation to provide evidence to your answer if you can)
ii. How could you improve your answer to part (b) to give you more confidence in the amount of wins you would expect after a million draws? [20%]
Part B – Working with data (worth 50% of Patch 1)
1. Loading and sorting a simple data file [40%]
– Load the “ages.txt” file from Moodle – read the numbers into a list. You can code this manually (as we did in class) or you can find a function (e.g. NumPy loadtxt) to help you do this.
– Print out the number of items in the file
– Sort the items into ascending order. You can use a sort function which we saw in class, write your own, or find a library function to do this.
– Print out the sorted list.
Screenshot your code, and the console output, and add to your patchwork.
2. Loading and plotting a more complex data file [60%] [Guide: my complete answer = 25 lines of code]
• Download historic weather data for Sutton Bonington Weather Station
– This is on Moodle: suttonboningtondata_moodle.csv.
If you’re interested, originally it came from https://www.metoffice.gov.uk/public/weather/climate- historic/#?tab=climateHistoric. I tidied it up in Excel, replacing special characters like ‘*’ and ‘---‘, and saved it as CSV format.
– If you get stuck loading the file, you can further pre-process the data into a format you are more comfortable reading into Python, perhaps using Excel. Please explain in the patchwork what you have done to the data. This will lose some marks, but will allow you to attempt all the sections below.
• Write a python program to:
– Load the data file. I would recommend the NumPy loadtxt function to help you do this. You will need to look up how to use this function’s parameters.
– Print to screen how many items (rows of data, not including headers) are loaded from the data file
– Work out the minimum temperature recorded in this data. Write your own code or use a library function to help you. Print out this value.
– The Sun column is currently in hours. Recalculate this column so the values are in days (assume a day is 24 hours).
• Re-save this file as a new filename– you may want to use numpy.savetxt, but you don’t have to.*
– Lastly, plot the 2017 monthly max temperatures as a line graph, using matplotlib. Remember to label axes, add a title etc. Add a copy of this figure to your PDF
*Also please upload your new saved file, if you attempted that element
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