Analyzing gas prices data

Contents

Double click on "gas1.xls" to import data

[data, textdata] = xlsread('Gas1.xls');

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Extract dates

dates = textdata(2:end,1);
disp(dates(1:5))

    '01/01/1996'
    '08/01/1996'
    '15/01/1996'
    '22/01/1996'
    '29/01/1996'

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Extract category names

cats = textdata(1, 2:end)

cats = 

    'Belgium '    'France'    'Germany'    'Italy'    'Netherlands'    'UK'    'US'

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Keep track of the size of the original matrix

originalsize = size(data)

originalsize =

   608     7

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Smooth the data (turning it into a vector)

data = smooth(data);
size(data)

ans =

        4256           1

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Restore the data's shape as a matrix

data = reshape(data, originalsize);
disp(data(1:5,:))

    3.9555    3.9330    4.0732    3.8908    4.3223    3.1996    1.2680
    3.9270    3.9193    4.0321    3.9310    4.3117    3.2321    1.2767
    3.8936    3.8847    3.9926    3.9340    4.2746    3.1904    1.2807
    3.8426    3.8309    3.9554    3.9057    4.2239    3.0937    1.2783
    3.8165    3.8004    3.9478    3.9010    4.2021    3.0311    1.2729

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Plot

plot(data)
set(gca, 'xTickLabel', dates);
legend(cats, 'Location', 'Best');
set(gcf, 'Position', [100 100 800 600]);

Plot example

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Look for correlations

corr(data)

ans =

    1.0000    0.9930    0.9823    0.9934    0.9856    0.9033    0.9416
    0.9930    1.0000    0.9904    0.9953    0.9928    0.9203    0.9503
    0.9823    0.9904    1.0000    0.9933    0.9966    0.9083    0.9377
    0.9934    0.9953    0.9933    1.0000    0.9939    0.9116    0.9369
    0.9856    0.9928    0.9966    0.9939    1.0000    0.9171    0.9433
    0.9033    0.9203    0.9083    0.9116    0.9171    1.0000    0.9320
    0.9416    0.9503    0.9377    0.9369    0.9433    0.9320    1.0000

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Published with MATLAB® 7.4