Not my data but

http://theconsciouslife.com/omega-3-6-9-ratio-cooking-oils.htm

Completely unrelated to anything but this is a super useful table and should be thought of as exemplary.

sparklines in a table in LaTeX

\begin{table} [h]

\begin{center}

\begin{tabular*}{\hsize}{@{\extracolsep{\fill}}| l | l l l|}

\hline

PlotID & Biomass 1980 & BA/Ha 1980 & $\%$ HW \\

\hline

Upper Quartile & & &\\

\textbf{110} & 17.5 Mg/Ha & 6.05 $\text{m}^2/\text{Ha}$ & \includegraphics[scale=0.3]{110sparkhw.png}\\

\textbf{316} & 10.86 Mg/Ha & 3.92 $\text{m}^2/\text{Ha}$ & \includegraphics[scale=0.2]{316sparkhw.png} \\

\textbf{212} & 7.31 Mg/Ha & 3.19 $\text{m}^2/\text{Ha}$ & \includegraphics[scale=0.3]{212sparkhw.png} \\

\textbf{213} & 7.23 Mg/Ha & 1.14 $\text{m}^2/\text{Ha}$ & \includegraphics[scale=0.3]{213sparkhw.png} \\

\textbf{109} & 6.31 Mg/Ha & 2.39 $\text{m}^2/\text{Ha}$ & \includegraphics[scale=0.3]{109sparkhw.png}\\

\textbf{108} & 4.85 Mg/Ha & 1.63 $\text{m}^2/\text{Ha}$ & \includegraphics[scale=0.3]{108sparkhw.png}\\

\textbf{214} & 4.10 Mg/Ha & 1.77 $\text{m}^2/\text{Ha}$ & \includegraphics[scale=0.3]{214sparkhw.png} \\

\hline

\end{tabular*}

\end{center}

\caption{Upper Quartile plots 1980 measurements and HW trajectory}

\label{tab:bioassay1}

\end{table}

In short, you can use insert graphic in the table.

Putting the "Upper Quartile" Line enables you to keep your graphic from eating your header. Which they like to do.

neat matlab program I wrote

%pcabio.m

% to compute and graph PCA for stand biometrics, as well as measure distances between points!
% this file has the 10 stand metrics currently measured. The first row is
% numeric. The first column is plot names.

%------------------------------------------------------------------------
% names of files to load-- comment in what you want
%load PCAEX80.dat;
load PCABIO1984.dat
%load PCABIO2007.dat;

format short g

% creation of the file headers and column numbers. Different columns in
% early file due to no ANPP

%For 2007
% fid = fopen('PCABIO2007.dat');
% C = textscan(fid,'%s %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32');
% fclose(fid);

%for 1984
fid = fopen('PCABIO1984.dat');
C = textscan(fid,'%s %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32');
fclose(fid);

%For files that are 80
%  fid = fopen('PCAEX80.dat');
%  C = textscan(fid,'%s %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32 %f32');
%  fclose(fid);

% these are the headings that correspond to the stand metrics, in order,

%2007
%headers = {'HARDWOOD' ,'BIO' ,'PERHARD','ANPP', 'BASAL', 'NUMT', 'STEMD', 'SHANNON', 'ASSAYNO','ASSAYBIO','NUMHW','PERNUMHW','STEMDHW','PERSTEMDHW'};

%1984
headers = {'HARDWOOD' ,'BIO' ,'PERHARD','ANPP', 'BASAL', 'NUMT', 'STEMD', 'ASSAYNO','ASSAYBIO','NUMHW','PERNUMHW','STEMDHW','PERSTEMDHW','SHANNON'};

% 1980
%headers = {'HARDWOOD' ,'BIO' ,'PERHARD','BASAL', 'NUMT', 'STEMD', 'ASSAYNO','ASSAYBIO','SHANNON','NUMHW','PERHWNUM','STEMDHW','PERSTEMDHW'};

% create a matrix that does not include the first row of PCAEX07 because it
% is text for the plot numbers (see above string in %s)

%X = PCAEX80(:,2:14);
X = PCABIO1984(:,2:15);
%X = PCABIO2007(:,2:15);

%------------------------------------------CONDUCTING PCA!!!------------

% if there are no NaN's!

[PC, scores, latent] = princomp(zscore(X));

% if NaN's are included, you must centralize and standardize each row
% individually, so comment in this code!

% % subtract out the mean
% for i = 1:length(X)
% thisRow = X(i,:);
% thisRow(isnan(thisRow)) = [];
% stdX(i) = std(thisRow);
% meanX(i) = mean(thisRow);
% centerX = X - repmat(meanX,10,1);
% centerStandardX = centerX./repmat(stdX,10,1);
% end


% % conduct principle components analysis
% [PC, scores, latent] = princomp(centerStandardX);

%----------------DISPLAYING THE CUMULATIVE OUTPUT OF THE VARIANCE!---

account = cumsum(latent)./sum(latent);
disp(account);

% name eigenvectors to the vectors that you are about.
vect1 = scores(:,1);
vect2 = scores(:,2);

% plot the principle components (FACTOR ANALYSIS PLOT) with the plot
% numbers-- must make sure these are STRINGS and not FLOATS/INTS
figure(1)
plot(vect1,vect2,'b.')
xlabel('1st Principal Component')
ylabel('2nd Principal Component')
title('Principal Components of Stand Biometerics')
text(vect1+0.1, vect2, C{1}, 'FontSize',8);

% plot a scree plot of cumulative variance explained
figure(2)
pareto(latent)
xlabel('Principal Component')
ylabel('Variance Explained (%)')
title('Scree plot of variance explained and CDF')

% plot a biplot for the first two axes... can be done for 3 as well, if
% needed, but is hard to interpret in my opinion. if disp(account)'s second
% entry is bigger than about 0.55, I don't do it.

figure(3)
biplot(PC(:,1:2), 'scores',scores(:,1:2),'varlabels',headers')


% for finding the distance between the sets of points and printing them out
% by labels! Will be used later in geostats

b = zeros(length(vect1),2);
for i = 1: length(vect1)
    b(i,1) = vect1(i);
    b(i,2) = vect2(i);
end

k = 0;
for i = 1:length(b)
    for j = 1:length(b)
        if j~=i
            k=k+1;
            index(k,:) = [i j];
        end;
    end;
end;

dist = ((b(index(:,2),1)-b(index(:,1),1)).^2 + (b(index(:,2),2)-b(index(:,2),2)).^2).^0.5;

% if you want to print it to the scree-- WARNING IT WILL OVERLOAD YOUR
% MEMORY IF YOU ARE RUNNING MUCH ELSE!

% fprintf(' #1 #2 distance\n');
% fprintf('%3d %3d %10.6f\n', ...
%    [index(:,1),index(:,2),dist].');
% fprintf('Total %11.6f\n',sum(dist));

m = [index(:,1),index(:,2),dist];

% output the distance matrix information to a file that saves in the Matlab
% directory. I think this format will be adaptable well to SPSS, but it
% would be better for Matlab to have in matrix form!

%dlmwrite('biometric_distances_80.csv',m,',');
dlmwrite('biometric_distances_804.csv',m,',');
%dlmwrite('biometric_distances_07.csv',m,',');