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Data Munging.mkd

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.

Raw
football.csv
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
Raw
weather.csv
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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