How do I use specific columns from a csv file

Hi, I have a csv file and I am trying to use specific columns to input into a function. Below is the code that I have so far where FVC and Height are the names of two of the columns from my csv data.

%% Load data
fvc = readtable("fvc-2022.csv");
%% Fit linear model
fitLinearModel(FVC, Height)

Unrecognized function or variable 'FVC'.

btw, 'fitLinearModel' is the function that I am using and I have attached the csv data set. I know that the 'FVC, Height' part of the code is incorrect so I was wondering what the right code is to add in here.

Thanks.

Answer 1

[Star Strider]

I am not certain what you want to regress.

Perhaps one of these —

fvc = readtable('https://www.mathworks.com/matlabcentral/answers/uploaded_files/1117350/fvc-2022.csv')

fvc = 127×3 table
     FVC      Height    Weight
    ______    ______    ______

    2.8132       156      51  
    2.6895    141.94      37  
    2.2441    148.07      35  
    4.4088       178      58  
    2.6369    146.01      38  
    2.3772    143.93      35  
    3.3349       159      47  
    3.0284    150.07      52  
    2.7341    149.91      43  
    3.0715     156.1      46  
    4.3504    167.09      55  
     3.072    153.03      51  
    2.2389    148.08      39  
    2.6339    153.99      39  
    2.3419    148.04      43  
    2.9945    155.08      44  

mdl = fitlm(fvc, 'Weight~FVC+Height')

mdl = 
Linear regression model:
    Weight ~ 1 + FVC + Height

Estimated Coefficients:
                   Estimate      SE        tStat       pValue  
                   ________    _______    _______    __________

    (Intercept)    -60.355      12.623    -4.7814    4.8412e-06
    FVC             5.0559      1.5982     3.1636     0.0019603
    Height         0.58529     0.10432     5.6106    1.2504e-07


Number of observations: 127, Error degrees of freedom: 124
Root Mean Squared Error: 5.61
R-squared: 0.592,  Adjusted R-Squared: 0.586
F-statistic vs. constant model: 90.1, p-value = 6.93e-25

mdl = fitlm(fvc, 'FVC~Height')

mdl = 
Linear regression model:
    FVC ~ 1 + Height

Estimated Coefficients:
                   Estimate       SE         tStat       pValue  
                   ________    _________    _______    __________

    (Intercept)     -4.9119      0.55321    -8.8788    6.0377e-15
    Height         0.051196    0.0036219     14.135    1.0884e-27


Number of observations: 127, Error degrees of freedom: 125
Root Mean Squared Error: 0.314
R-squared: 0.615,  Adjusted R-Squared: 0.612
F-statistic vs. constant model: 200, p-value = 1.09e-27

mdl = fitlm(fvc, 'Height~FVC')

mdl = 
Linear regression model:
    Height ~ 1 + FVC

Estimated Coefficients:
                   Estimate      SE       tStat       pValue  
                   ________    _______    ______    __________

    (Intercept)     117.73      2.5002    47.088     2.083e-81
    FVC             12.016     0.85006    14.135    1.0884e-27


Number of observations: 127, Error degrees of freedom: 125
Root Mean Squared Error: 4.81
R-squared: 0.615,  Adjusted R-Squared: 0.612
F-statistic vs. constant model: 200, p-value = 1.09e-27

Make appropriate changes to get the desired result.

See the documentation on fitlm for details, and the links in See Also for related functions and documentation.

.

[Declan]

Hi, so basically I have a file called 'fvc-2022.csv' and in the file there are 3 columns. The first column is called 'FVC', the second is called 'Height', and the third is called 'Weight'. I also have a premade function called 'fitLinearModel' which uses two vectors and finds the intercept, slope and residual variance. What I want to do is use two columns from the csv file as the two vectors in that premade function but I'm not too sure on how to call it. I believe right now that the proper coding is the following

fitLinearModel(fvc.FVC, fvc.Height)

[Star Strider]

‘I also have a premade function called 'fitLinearModel' which uses two vectors and finds the intercept, slope and residual variance.’

I just found that function in an earlier Comment.

‘What I want to do is use two columns from the csv file as the two vectors in that premade function but I'm not too sure on how to call it. I believe right now that the proper coding is the following...’

The way you’re calling it is correct. However, it has three outputs, so you need to include them in the function call, for example:

[intercept, slope, resVar] = fitLinearModel(fvc.FVC, fvc.Height)

Otherwise, the call to it (without specifying the outputs) will return only the ‘Intercept’ output. Also, it’s ineffecient to do the regression twice as your function currently does. Use polyval with the returned polynomial and the ‘x’ vector, then calculate the residuals and their variance from that.

FWIW, using fitlm is likely easier to use and more robust. It does all the statistical calculations internally, and reports the results. If you want to get the residual variance from it yourself, use the predict function (there are several, the one I linked to appears to be the appropriate one, although MATLAB will likely choose the correct one given the correct arguments), then calculate the residuals and their variance from that.

.

Answer 2

[Image Analyst]

It's not finding your file. Your file lives in a different folder than your script, and it is also not on the search path. Use fullfile to specify the full path and base file name of your file.

[Declan]

Whoops, sorry, I just updated the code. The one you saw was before I added in the csv file

[Image Analyst]

MATLAB is case sensitive so FVC would be a different variable than fvc. Choose one or the other. Be consistent in your capitalization.

[Declan]

well the file name is in lowercase but in the csv file, it is upper case (name of the first column is FVC whereas name of file is fvc-2022)

[Image Analyst]

What toolbox is fitLinearModel() in? Whatever it is, I don't have it. Plus you didn't define Height. What kind of model do you want to fit? Do you have a formula for it?

[Declan]

have you checked the csv file? Height is the name of another column in the data set. Also, fitLinearModel is a function that I made beforehand. Ill paste it below.

function [intercept, slope, resVar] = fitLinearModel(x,y)
%intercept
P = polyfit(x,y,1);
intercept=P(2);

%slope
slope=P(1);

%resVar
A = [ones(numel(x),1),x.'];
b = y.';
c = A\b;

format long
resVar=var(y-(c(1)+c(2)*x))*(numel(x)-1)/(numel(x)-2);

end

[Image Analyst]

Try this:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 15;
t = readtable('fvc-2022.csv')
% Fit line through Heights
x = t.FVC;
y = t.Height;
[intercept, slope, resVar] = fitLinearModel(x,y)
% Fit line through Heights
x = t.FVC;
y = t.Weight;
[intercept, slope, resVar] = fitLinearModel(x,y)
function [intercept, slope, resVar] = fitLinearModel(x,y)
%intercept
P = polyfit(x,y,1);
intercept=P(2);
%slope
slope=P(1);
%resVar
A = [ones(numel(x),1), x(:)];
b = y(:);
c = A\b;
format long
resVar=var(y-(c(1)+c(2)*x))*(numel(x)-1)/(numel(x)-2);
end