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Save table with cell arrays in csv

7 Ansichten (letzte 30 Tage)
Oliver Steiner
Oliver Steiner am 1 Feb. 2023
Kommentiert: Image Analyst am 3 Feb. 2023
Hey! I created a table with cell arrays. In each cell is data from one condition. When I want to convert the table into csv this does not work. The table now looks like this:
"
time0 correct0 time1 correct1 time10 correct10
______________ ______________ ______________ ______________ ______________ ______________
{ 69×1 double} { 69×1 double} { 99×1 double} { 99×1 double} {127×1 double} {127×1 double}
"
In excel in shoul look like this:
"
time0 correct0 time1 correct1 time10 correct10
______________ ______________ ______________ ______________ ______________ ______________
{1,2,3......53,35} {1,2,3......53,35} {1,2,3......53,35} {1,2,3......53,35} {1,2,3......53,35} {1,2,3......53,35}
"
So that in each cell are the data from the array seperated by a comma.
Many thanks!
Best
Oliver

Akzeptierte Antwort

Stephen23
Stephen23 am 2 Feb. 2023
Bearbeitet: Stephen23 am 2 Feb. 2023
T = load('table.mat').table % !!! do NOT use "table" as a variable name !!!
T = 18×6 table
time0 correct0 time1 correct1 time10 correct10 ______________ ______________ ______________ ______________ ______________ ______________ { 69×1 double} { 69×1 double} { 99×1 double} { 99×1 double} {127×1 double} {127×1 double} {140×1 double} {140×1 double} {131×1 double} {131×1 double} {141×1 double} {141×1 double} {100×1 double} {100×1 double} {117×1 double} {117×1 double} {110×1 double} {110×1 double} { 41×1 double} { 41×1 double} { 60×1 double} { 60×1 double} { 55×1 double} { 55×1 double} {134×1 double} {134×1 double} {132×1 double} {132×1 double} {136×1 double} {136×1 double} {126×1 double} {126×1 double} {126×1 double} {126×1 double} {126×1 double} {126×1 double} { 61×1 double} { 61×1 double} { 85×1 double} { 85×1 double} { 96×1 double} { 96×1 double} { 52×1 double} { 52×1 double} { 65×1 double} { 65×1 double} { 73×1 double} { 73×1 double} {104×1 double} {104×1 double} {125×1 double} {125×1 double} {121×1 double} {121×1 double} { 74×1 double} { 74×1 double} { 68×1 double} { 68×1 double} { 54×1 double} { 54×1 double} { 97×1 double} { 97×1 double} { 95×1 double} { 95×1 double} {111×1 double} {111×1 double} { 70×1 double} { 70×1 double} { 74×1 double} { 74×1 double} { 72×1 double} { 72×1 double} {120×1 double} {120×1 double} {125×1 double} {125×1 double} {125×1 double} {125×1 double} {106×1 double} {106×1 double} { 99×1 double} { 99×1 double} {110×1 double} {110×1 double} {118×1 double} {118×1 double} {104×1 double} {104×1 double} {122×1 double} {122×1 double} {115×1 double} {115×1 double} {116×1 double} {116×1 double} {122×1 double} {122×1 double}
F = @(v)strjoin(string(v),',');
T = convertvars(T, @iscell, @(c)cellfun(F,c))
T = 18×6 table
time0 correct0 time1 correct1 time10 correct10 __________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________ __________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________ _________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________ __________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________ ___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________ "132.08,279.17,174.58,225.42,278.75,276.25,180.83,184.17,131.67,194.17,250.83,-1344.58,157.5,-1331.67,279.58,-1325.83,-1315.83,285.42,237.5,178.75,328.33,164.58,164.58,219.17,318.75,220,325.83,-1330.42,314.17,310.42,217.08,161.25,-1343.33,-1354.17,193.75,186.67,135.42,231.25,-1361.67,191.25,187.5,278.75,270.83,120.42,220.83,267.92,172.5,120,171.25,121.25,-1385.42,213.33,115.42,215.42,229.58,131.25,174.58,-1382.5,214.17,-1390.42,197.92,195.42,149.17,101.67,103.33,153.75,-1394.58,258.75,268.75" "1,0,1,1,1,0,0,1,0,1,0,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1" 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"136.25,184.17,235.42,84.58,-1415.42,233.33,-1413.75,-1414.58,83.75,75.83,175.42,218.33,-1432.5,167.92,66.67,216.25,214.58,114.17,218.33,217.5,-1425.83,70.42,123.75,123.33,78.33,-1421.25,230.83,-1420.83,135.83,82.5,233.75,184.17,231.25,184.17,185,185,86.25,236.67,136.67,85.83,234.17,134.58,181.25,135,89.58,188.75,189.58,139.58,90,86.25,235,138.33,242.92,242.5,185.42,185,235,134.17,234.17,182.5,81.67,80.83,182.5,77.92,177.5,125,71.67,75,230.83,81.67,137.5,235,136.25,185.83" "1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1" "180,183.75,-1415.42,-1413.75,134.58,233.75,231.25,231.25,232.08,182.08,81.25,82.5,232.5,134.58,230.42,-1420.83,228.75,127.08,227.5,177.5,129.17,177.08,126.67,176.25,177.08,229.17,-1417.5,132.92,83.33,80.83,232.92,185.42,-1412.92,237.5,89.58,190.42,139.58,136.67,187.92,-1411.67,84.17,77.08,178.75,71.67,220.83,221.25,121.25,222.92,71.67,172.08,223.75,-1428.33,122.92,226.25,174.58,75.42,227.5,178.33,76.67,128.75,180,229.58,179.58,130,127.5,180.42,79.58,-1420.42,79.58,230.42,228.75,75" "1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1" 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"-1317.5,-1332.5,164.17,312.5,259.58,300,149.58,199.17,192.92,293.75,248.33,292.08,239.17,187.08,181.67,182.5,129.58,231.25,185.83,137.5,286.67,234.17,-1365.83,235.42,-1367.5,-1367.92,-1368.75,230.42,271.25,275,175.42,171.25,-1377.08,270.83,268.75,118.75,-1377.5,-1379.17,224.58,173.75,120.83,222.92,130.42,230,132.5,283.75,235.42,289.58,189.17,190.83,140,142.92,192.92,189.58,234.17,183.75,-1367.08,-1364.17,140.42,242.5,185.83,-1365,233.33,238.33,137.92,187.08,232.08,-1368.75,280,132.92,-1367.92,284.17,-1365.83,285.42,230.83,177.5,280.42,179.17,177.08,129.58,232.92,130.42,282.92,-1359.58,298.33,153.75,-1346.67,295.83,195,245.42,297.08,-1352.92,137.92,-1361.25,190.42,243.33,195.42,142.92,191.25,189.58,187.5,280,277.5,172.08,122.5,222.5,124.17,174.17,127.08,-1377.08,122.08,-1376.67,-1378.75,167.92,115,224.58,234.58,-1362.08,295,-1352.5,298.75,-1352.08,150.42,300.42,254.17" 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writetable(T,'myfile.csv')

Weitere Antworten (2)

dpb
dpb am 1 Feb. 2023
Verschoben: Image Analyst am 1 Feb. 2023
What do you propose to do with the spreadsheet when you have it? That'll be just a string of text, and to write it to a given cell like that you'll have to turn it to text first...something like
C={[1:5].'};
sprintf('%d,',C{:})
ans = '1,2,3,4,5,'
without the nicety of eliminating the trailing comma by counting the number elements and writing specific formatting string.
All in all, looks like abadidea™, would strongly suggest a data redesign is needed...
  1 Kommentar
Oliver Steiner
Oliver Steiner am 2 Feb. 2023
Bearbeitet: Oliver Steiner am 2 Feb. 2023
Thank you! I agree that a data redesign would be good. I am working on this... The basic idea is that I load data from participants and store them in a table in which each cell contains all the data from on condition. I found a smoothing code in python and therfore I want to safe the data in csv to convert it into a panda dataframe. The code looks like this:

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Image Analyst
Image Analyst am 1 Feb. 2023
I agree with @dpb if you want all those numbers in a single cell in Excel, you're going to have to turn the vector into a string and then put the string into a cell. Something like (untested)
t2 = table; % Create new table.
% Make columns have the same name as the original table.
t2.Properties.VariableNames = t.Properties.VariableNames
for row = 1 : height(t)
for col = 1 : width(t)
% Get cell contents.
vec = t{row, col}
% Turn into string. Assume numbers are integers.
% Otherwise use %f instead of %d.
str = sprintf('%d ')
t2{row, col} = {str};
end
end
writetable(t2, excelFullFileName);
You didn't attach your table so I didn't get a chance to test it. If it doesn't work, fix it or else attach your table in a .mat file.
  6 Kommentare
Oliver Steiner
Oliver Steiner am 3 Feb. 2023
Hey! I just added your code to the existening code. This is the "Filteringnoiseinmatlab .m" code. Many thx!
Image Analyst
Image Analyst am 3 Feb. 2023
>> Filteringnoiseinmatlab
Error using load
Unable to find file or directory 'expResEye_P01_AllB.mat'.
Error in Filteringnoiseinmatlab (line 41)
load(sprintf('expResEye_%s_AllB.mat', char(subs(1, sub))));

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