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Data Munging

Adapted from CodeKata.

Last month, James showed us how to parse CSV. Here's a chance to practice, and to try something more like a real-world programming problem. You'll want to check out the CSV class in Ruby's standard library to help you.

Part One: Weather Data

In weather.csv you’ll find daily weather data for Morristown, NJ for June 2002. Download this file, then write a program to output the day number with the smallest temperature spread. The day number is in a column labeled Dy, the max temperature is MxT and the min temperature is MnT.

Part Two: Soccer League Table

The file football.csv contains the results from the English Premier League for 2001/2. The columns labeled F and A contain the total number of goals scored for and against each team in that season (so Arsenal scored 79 goals against opponents, and had 36 goals scored against them). Write a program to print the name of the team with the smallest difference in ‘for’ and ‘against’ goals.

Part Three: DRY Fusion

Take the two programs written previously and factor out as much common code as possible, leaving you with two smaller programs and some kind of shared functionality.

Team P W L D F A Pts
Arsenal 38 26 9 3 79 36 87
Liverpool 38 24 8 6 67 30 80
Manchester_U 38 24 5 9 87 45 77
Newcastle 38 21 8 9 74 52 71
Leeds 38 18 12 8 53 37 66
Chelsea 38 17 13 8 66 38 64
West_Ham 38 15 8 15 48 57 53
Aston_Villa 38 12 14 12 46 47 50
Tottenham 38 14 8 16 49 53 50
Blackburn 38 12 10 16 55 51 46
Southampton 38 12 9 17 46 54 45
Middlesbrough 38 12 9 17 35 47 45
Fulham 38 10 14 14 36 44 44
Charlton 38 10 14 14 38 49 44
Everton 38 11 10 17 45 57 43
Bolton 38 9 13 16 44 62 40
Sunderland 38 10 10 18 29 51 40
Ipswich 38 9 9 20 41 64 36
Derby 38 8 6 24 33 63 30
Leicester 38 5 13 20 30 64 28
We can make this file beautiful and searchable if this error is corrected: It looks like row 2 should actually have 17 columns, instead of 15. in line 1.
Dy,MxT,MnT,AvT,HDDay,AvDP,1HrP,TPcpn,WxType,PDir,AvSp,Dir,MxS,SkyC,MxR,MnR,AvSLP
1,88,59,74,53.8,0.00,F,280,9.6,270,17,1.6,93,23,1004.5
2,79,63,71,46.5,0.00,330,8.7,340,23,3.3,70,28,1004.5
3,77,55,66,39.6,0.00,350,5.0,350,9,2.8,59,24,1016.8
4,77,59,68,51.1,0.00,110,9.1,130,12,8.6,62,40,1021.1
5,90,66,78,68.3,0.00,TFH,220,8.3,260,12,6.9,84,55,1014.4
6,81,61,71,63.7,0.00,RFH,030,6.2,030,13,9.7,93,60,1012.7
7,73,57,65,53.0,0.00,RF,050,9.5,050,17,5.3,90,48,1021.8
8,75,54,65,50.0,0.00,FH,160,4.2,150,10,2.6,93,41,1026.3
9,86,32*,59,6,61.5,0.00,240,7.6,220,12,6.0,78,46,1018.6
10,84,64,74,57.5,0.00,F,210,6.6,050,9,3.4,84,40,1019.0
11,91,59,75,66.3,0.00,H,250,7.1,230,12,2.5,93,45,1012.6
12,88,73,81,68.7,0.00,RTH,250,8.1,270,21,7.9,94,51,1007.0
13,70,59,65,55.0,0.00,H,150,3.0,150,8,10.0,83,59,1012.6
14,61,59,60,5,55.9,0.00,RF,060,6.7,080,9,10.0,93,87,1008.6
15,64,55,60,5,54.9,0.00,F,040,4.3,200,7,9.6,96,70,1006.1
16,79,59,69,56.7,0.00,F,250,7.6,240,21,7.8,87,44,1007.0
17,81,57,69,51.7,0.00,T,260,9.1,270,29*,5.2,90,34,1012.5
18,82,52,67,52.6,0.00,230,4.0,190,12,5.0,93,34,1021.3
19,81,61,71,58.9,0.00,H,250,5.2,230,12,5.3,87,44,1028.5
20,84,57,71,58.9,0.00,FH,150,6.3,160,13,3.6,90,43,1032.5
21,86,59,73,57.7,0.00,F,240,6.1,250,12,1.0,87,35,1030.7
22,90,64,77,61.1,0.00,H,250,6.4,230,9,0.2,78,38,1026.4
23,90,68,79,63.1,0.00,H,240,8.3,230,12,0.2,68,42,1021.3
24,90,77,84,67.5,0.00,H,350,8.5,010,14,6.9,74,48,1018.2
25,90,72,81,61.3,0.00,190,4.9,230,9,5.6,81,29,1019.6
26,97*,64,81,70.4,0.00,H,050,5.1,200,12,4.0,107,45,1014.9
27,91,72,82,69.7,0.00,RTH,250,12.1,230,17,7.1,90,47,1009.0
28,84,68,76,65.6,0.00,RTFH,280,7.6,340,16,7.0,100,51,1011.0
29,88,66,77,59.7,0.00,040,5.4,020,9,5.3,84,33,1020.6
30,90,45,68,63.6,0.00,H,240,6.0,220,17,4.8,200,41,1022.7
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