Merge a large number of tables with different lengths aligned by specific column variable

I have a spreadsheet that was imported using the following code:

filename = 'Baseline ROI analysis SOMA.xlsx'; %identify name of the file
sheets = sheetnames(filename); %load string of sheet names
disp(sheets)

raw_data = [] %initialize

%loop through and load each sheet into a raw_data (cell format)
for k = 1:length(sheets)
    raw_data{k} = readtable(filename,'Sheet',sheets(k));
end

The 1x20 cell contains 20 tables with 6 column variables per table.

I manually extracted each table to a variable, removing 3 variables that I do not need. (I assume there's a faster way to do this, but I can only think of dynamic variable names which I believe are frowned upon).

Example:

data1 = removevars(raw_data{1,1},{'Name','ND_M','ND_Z'})

data2 = removevars(raw_data{1,2},{'Name','ND_M','ND_Z'})

data3 = removevars(raw_data{1,3},{'Name','ND_M','ND_Z'})

The remaining variables - time(Time_s_), video frame #(ND_T), and average intensity(x_1_470Nm_) are output into the individual tables.

I've tried using outerjoins, but since I can't set an index (like a pandas dataframe), I can't merge on the frame values.

testmerge = outerjoin(data1,data2)

Is there a way to merge the tables so that all values are retained, and they can be aligned by frame #?

Also, would there be a way to do so without chaining outerjoin(data1,outerjoin(data2,outerjoin(data3,outerjoin(data4,data5))))... ?

Thanks in advance!