Making a graph with multiple different colors

I am trying to make a graph where the x values is "number" and the y values are " Amplitude, PSD, Recurrance_Rate, Recurrance_Points, Determinism, Ratio_Determinism_Recurrance_Rate, Average_Diagonal_Length, Average_Vertical_Length, Laminarity, Divergence, Entropy, Trapping_Time, OSA_Label" with different colors for each one. This is the code i have so far.
data = xlsread('project.xlsx')
Number = data(:, 1)
Amplitude = data(:, 2)
PSD = data(:, 3)
Recurrance_Rate = data(:, 4)
Recurrance_Points = data(:, 5)
Determinism = data(:, 6)
Ratio_Determinism_Recurrance_Rate= data(:, 7)
Average_Diagonal_Length = data(:, 8)
Average_Vertical_Length = data(:, 9)
Laminarity = data(:, 10)
Divergence = data(:, 11)
Entropy = data(:, 12)
Trapping_Time= data(:, 13)
OSA_Label = data(:, 14)
The data waas originally in an excel spreadsheet and i assigned each column its own name. Please help

2 个评论

i basically have an excel spreadsheet with 14 columbs and 1085 rows and need to find a way to compare it all. Any suggestions?

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回答(1 个)

Just use plot with a legend
data = readmatrix('project.xlsx')
varNames = ["Number","Amplitude","PSD","Recurrance_Rate","Recurrance_Points","Determinism","Ratio_Determinism_Recurrance_Rate","Average_Diagonal_Length","Average_Vertical_Length","Laminarity","Divergence","Entropy","Trapping_Time","OSA_Label"];
plot(data)
colororder(parula(length(varNames)));
legend(varNames)

3 个评论

would there be a way to use the LDA, Naive Bayes, Nearest Neighbor, or Classification Tree?
You can convert the matrix into a table, which will make it compatible as an input to many functions that can do what you mentioned.
data = readmatrix('project.xlsx')
Tbl = array2table(data);
varNames = ["Number","Amplitude","PSD","Recurrance_Rate","Recurrance_Points","Determinism","Ratio_Determinism_Recurrance_Rate","Average_Diagonal_Length","Average_Vertical_Length","Laminarity","Divergence","Entropy","Trapping_Time","OSA_Label"];
Tbl.Properties.VariableNames = {varNames}
Are you doing a classification or regression problem and need to perform machine learning? If so, you could use the Classification Learner app or the Regression Learner App depending on what you would want to do. See video below:
Or just use readtable.
Your question seems to be wandering from the original one on creating a graph with multiple lines. What is the new question?

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