Parsing Data - Code Test

parse.rb

require 'rspec'
require 'csv'

class DataParser

  def initialize(file)
    @file = file
    prepare_for_csv(@file)
  end

  #must be manually entered in because source data is not delimited by character but by number of spaces varying per column
  def col_breaks
    case
    when @file == 'w_data.dat'
      [4, 10, 16, 22, 28, 34, 39, 45, 52, 57, 62, 66, 70, 75, 79, 82]
    else @file == 'soccer.dat'
      [5, 21, 25, 31, 35, 39, 47, 53]
    end
  end

  def prepare_for_csv(file)
    @new_file = ""
    File.open(file).each_line do |line|
      if /D|T|\d/.match(line.strip[0]) #only parse if line starts with a digit, 'D' (header) or 'T' (header)
        #insert commas between data
        new_line = line.split('').each_with_index { |l,i| l.replace(',') if col_breaks.include?(i) }.join 
        new_line.gsub!('*',' ')
        new_line.gsub!(' ','')
        @new_file << new_line
      end
    end
  end

  def csv_file
    CSV.parse(@new_file, headers: true)
  end

  def min_difference(x, y)
    csv_file.min_by{ |m| m[x].to_i - m[y].to_i }
  end

end

soccer = DataParser.new('soccer.dat')
p soccer.min_difference('F','A')


weather = DataParser.new('w_data.dat')
p weather.min_difference('MxT','MnT')

parse_rspec.rb

require_relative 'parse'
require 'rspec'

describe DataParser do
  let(:csv_file) { DataParser.new("soccer.dat").csv_file }

  it "csv file parses headers correctly" do
    csv_file.headers.should == [nil, "Team", "P", "W", "L", "D", "F", "A", "Pts"]
  end

  it "csv file matches the team column correctly" do
    csv_file[0]['Team']== 'Arsenal'
  end

  it "csv file matches the Pts column correctly" do
    csv_file[0]['Pts']== '87'
  end
end

describe DataParser do
  let(:csv_file) { DataParser.new("w_data.dat").csv_file }

  it "csv file parses headers correctly" do
    csv_file.headers.should == ["Dy", "MxT", "MnT", "AvT", "HDDay", "AvDP", "1HrP", "TPcpn", "WxType", "PDir", "AvSp", "Dir", "MxS", "SkyC", "MxR", "Mn", "AvSLP"]
  end
end

describe DataParser do
  let(:parser) { DataParser.new("soccer.dat") }

  it "return the correct team with the minimum score difference" do
    parser.min_difference('F', 'A')['Team'].should == 'Leicester'
  end
end

describe DataParser do
  let(:parser) { DataParser.new("w_data.dat") }

  it "return the correct day with the minimum temperature difference" do
    parser.min_difference('MxT', 'MnT')['Dy'].should == '14'
  end
end

Questions.md

1. In the attached file (w_data.dat), you’ll find daily weather data. Download this text file, then write a program to output the day number (column one) with the smallest temperature spread (the maximum temperature is the second column, the minimum the third column).

2. The attached soccer.dat file contains the results from the English Premier League. 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.

Is the way you wrote the second program influenced by writing the first?

I used the same program for both questions.

soccer.dat

<pre>
       Team            P     W    L   D    F      A     Pts
    1. Arsenal         38    26   9   3    79  -  36    87
    2. Liverpool       38    24   8   6    67  -  30    80
    3. Manchester_U    38    24   5   9    87  -  45    77
    4. Newcastle       38    21   8   9    74  -  52    71
    5. Leeds           38    18  12   8    53  -  37    66
    6. Chelsea         38    17  13   8    66  -  38    64
    7. West_Ham        38    15   8  15    48  -  57    53
    8. Aston_Villa     38    12  14  12    46  -  47    50
    9. Tottenham       38    14   8  16    49  -  53    50
   10. Blackburn       38    12  10  16    55  -  51    46
   11. Southampton     38    12   9  17    46  -  54    45
   12. Middlesbrough   38    12   9  17    35  -  47    45
   13. Fulham          38    10  14  14    36  -  44    44
   14. Charlton        38    10  14  14    38  -  49    44
   15. Everton         38    11  10  17    45  -  57    43
   16. Bolton          38     9  13  16    44  -  62    40
   17. Sunderland      38    10  10  18    29  -  51    40
   -------------------------------------------------------
   18. Ipswich         38     9   9  20    41  -  64    36
   19. Derby           38     8   6  24    33  -  63    30
   20. Leicester       38     5  13  20    30  -  64    28
</pre>

w_data.dat

<pre>
 MMU June 2002

  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
  mo  82.9  60.5  71.7    16  58.8       0.00              6.9          5.3
</pre>

you inspired me to write an answer in python. i started with easier files to work with.

https://github.com/realpython/interview-questions/tree/master/parsing-data

nice! i was confused at first, as i didn't know how stylistically similar python was to ruby!