One rich seam of experimental data comes from meteorological measurements.  Thousands of measurements are recorded each day by the Australian Bureau of Meteorology (BoM). This assignment requires you to download and process some maximum daytime temperature measurements from the BoM and analyse them to form several pivot tables and charts. Ten Western Australian towns (or airports) are under consideration for this assignment:

0: ALBANY AIRPORT (9741)

1: BARROW ISLAND AIRPORT (5094)

2: BROOME AIRPORT (3003)

3: CHRISTMAS ISLAND AERO (200790)

4: ESPERANCE AERO (9542)

5: GERALDTON AIRPORT (8051)

6: MORAWA AIRPORT (8296)

7: PARABURDOO AERO (7185)

8: SHARK BAY AIRPORT (6105)

9: WYNDHAM AERO (1006)

Note that each town has two numbers associated with it, the first is a digit from 0-9 and the second (bracketted following the name) is a station number which uniquely identifies where the measurements are made.  You must choose three town depending on the final three (unique) digits of your student number.  If your number is 30165285 you must choose 2:Broome, 8:Shark Bay and 5:Geraldton.  If your number is 12347733 you must choose 4:Esperance, 7:Paraburdoo and 3:Christmas Island.

Create a single datalist by pasting together the measurements from the three CSVs. Record how many measurements in total you have available.  Process the station numbers to include the actual names of the stations.

(a)  Create a pivot table which shows the average maximum temperature for the three towns month by month through the year.  Put the months in the rows and the towns in the columns.  Adjust the number of decimal places to some sensible value.  Store your pivot table in a separate worksheet so that you can get your marks recorded.

(b)  Create a new pivot table which shows the maximum of the maximum temperature (ie. The hottest day in each of the months).  Which town has the greatest seasonal variation since the start of 2010?  Store your pivot table in a separate worksheet so that you can get your marks recorded.

(c) Create a pivot table that counts the number of temperature measurements, month by month for each of the three towns that have not been quality approved.  Which town has the greatest number of missings or low quality measurements available?  You will find more information about this in the BoM Note files supplied along with the CSV measurements.

(d) Create a pivot chart showing the standard deviation of the maximum temperature for your three towns.  Put the months in the columns and the towns in the rows.  What does the standard deviation tell you about climatic variations in each of the towns over the course of a year?  For full marks in this part of the question you must be able to draw some conclusions that would not be obvious by inspecting the data set alone.