Question

Question 3: The following table shows the monthly minimum temperature (degree Celsius (C)) of a city in Australia for 3 consequent years Mean of Minimum Temperature 20102011 2012 18 15.5 12.9 12.5 10 Month Jan Feb Mar 15.6 17.7 17.7 13.5 12.3 9.5 7.3 7.6 7.2 10.1 10 11.9 13.7 16 14.5 11.8 9.8 7.9 Jun Jul Aug Sep Oct Nov Dec 6.4 7.6 8.7 7.8 9.2 10.6 12.6 14.1 12.2 13.9 1. Propose a visualisation method to compare the mean of minimum temperature in monthly manner for three given years. (10%) 2. Aggregate the information to provide a table and visualisation of the temperature in seasonal bases. (15%)

Answer 1

1 - We can use Python 3 and its module Matplotlib to visualise this data.

Here's the python 3 code. Just make sure you install Matplotlib before executing this code.

Note - You can install matplotlib using pip command - (pip install matlplotlib)

from matplotlib import pyplot as plt month= ['Jan', 'Feb ', 'Mar ', 'Apr', 'May ', 'Jun', 'Jul ', 'Aug ', 'Sep ', 'Oct', 'Nov ', 'Dec '] year 2010= [17.7, 17.7, 13.5, 12.3, 9.5, 7.3, 7.6, 7.2, 10.1, 10, 11.9, 13.7 year_2011- [15.6, 16, 14.5, 11.8, 9.8, 7.9, 7.1, 7.8, 9.2, 10.6, 12.6, 14.11 year_2012[18, 15.5, 12.9, 12.5, 10, 8.1, 6.4, 7.6, 8.7, 9, 12.2, 13.91 plt.plot (month, year_2010, 'r') plt.plot (month, year 2011, 'g' plt.plot (month, year_2012, 'b') plt.title ('Minimum temperature) plt.xlabel ( 'Months') plt.ylabel ('Temperatue (in degree Celcius' plt.show

This is the graph plot produced using the code.

a. ligure 1 Minimum temperature 18 16 o 14 드12 10 8 6 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Months

For second part I have modified the code to create seasons and calculated the mean of 3 months using the statistics module from Python 3. This library is pre-installed so you dont have to worry about installation.

from matplotlib import pyplot as pl from statistics import mean month= ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', year 2010 [17.7, 17.7, 13.5, 12.3, 9.5, 7.3, 7.6, 7.2, 10.1, 10, 11.9, 13.7] year 2011 [15.6, 16, 14.5, 11.8, 9.8, 7.9, 7.1, 7.8, 9.2, 10.6, 12.6, 14.1] year-2012 [18, 15.5, 12.9, 12.5, 10, 8.1, 6.4, 7.6, 8.7, 9, 12.2, 13.9] 'Dec'] 'Nov', season = ['Jan-Mar', 'Apr - Jun', 'Jul - Sep', 'Oct -Dec'] mean 2010 - [mean (year 2010[:3]), mean (year 2010 [3:6]), mean (year 2010 [6:9]), mean (year 2010 [9:1)] mean 2011- [mean (year 2011 [:3]), mean (year 2011 [3:6]) , mean (vear 2011 [6:91), mean (year_2011[9:])] mean 2012 [mean (year 2012[:3]) , mean (year 2012 [3:6]) , mean (year 2012 [6:9]), mean (year 2012 [9:])] plt.plot (season, mean 2010, 'r') plt.plot(season, mean 2011, 'g') plt.plot (season, mean 2012, 'b plt.title ( 'Aggregate Minimum temperature) plt.xlabel (' Seasons') plt.ylabel ('Temperatue (in degree Celcius') plt. show ()

And the following graph is produced.

Figure 1 Aggregate Minimum temperature 16 14 O 12 a 10 8 ul Sep Jan - Mar Apr-Jun Oct - Dec Seasons x= y= 13.0874

Note - If you want the code just use google lens or any online tool to extract the text with proper indentation or just cop the code manually, its up to you.