# Save table with cell arrays in csv

조회 수: 7(최근 30일)
Oliver Steiner 2023년 2월 1일
댓글: Image Analyst 2023년 2월 3일
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

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### 채택된 답변

Stephen23 2023년 2월 2일
편집: Stephen23 2023년 2월 2일
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" "282.08,230,178.75,123.75,121.25,221.67,-1376.25,224.58,130.42,-1374.17,278.33,227.92,177.5,132.92,285,-1355.83,-1350.42,149.58,-1350.42,298.75,252.5,299.58,205,155.42,152.5,-1355,240,182.92,181.25,184.58,-1367.08,-1370.83,131.67,275.83,282.5,-1364.58,135.83,245,133.75,132.5,229.58,277.5,269.58,169.17,118.33,-1380.42,162.5,211.25,212.08,164.17,165,-1382.5,261.67,210.42,205.42,-1395.42,251.25,200,95.83,144.17,245,144.17,197.5,98.75,247.08,247.5,144.58,-1402.5,96.25,-1403.33,253.75,103.75,-1398.75,201.25,149.58,201.25,242.08,90,245.42,145.42,197.08,250,99.58,-1401.67,241.25,90,192.5,146.67,198.75,194.58,245,248.33,-1401.25,152.92,96.25,97.08,150.83,205.83,-1393.75" "1,1,0,1,1,1,1,1,0,1,1,1,1,0,1,0,0,1,1,1,0,1,1,0,1,1,1,1,0,1,0,0,1,1,1,0,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,0,1,1,1,0,1,0,1,1,1,1,1,0,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1" 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"258.33,108.33,157.92,-1390,205,153.33,150.83,151.67,-1397.92,200.42,252.5,201.25,252.5,110.83,112.5,215,-1386.25,113.33,264.17,215.83,262.92,-1387.5,162.5,-1390,109.58,110.42,159.17,219.17,-1382.08,-1391.25,213.75,162.92,164.58,263.75,-1388.75,262.5,112.08,212.08,263.33,222.92,126.25,-1373.33,280,280,-1371.67,122.92,124.58,-1380.83,177.92,171.25,120.42,218.75,167.92,223.75,121.67,221.25,272.08,-1387.5,168.75,127.08,174.58,229.58,-1369.17,184.17,181.25,277.92,279.17,271.25,-1380,270.83,121.67,-1384.17,215,-1385.42,211.67,114.58,215,117.08,212.92,264.17,214.17,117.5,217.08,-1384.58,-1385.42,-1385.83,122.5,-1376.25,180.83,181.25,-1375.83,124.58,272.08,173.33,229.58,130,230,-1369.17,280,182.08,130,273.33,176.67,223.75,119.58,217.92,116.25,164.17,-1395,157.92,112.92,106.67,-1395.42,156.67,254.58,105.42,153.33,-1397.08,255.42,-1396.67,197.92,101.25,251.25,251.25,198.33,150,251.25,249.17,-1400.42,192.5,-1409.17" 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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" "339.58,282.92,-1325,220.83,270.42,315,158.75,206.67,261.25,261.67,255.83,305.42,-1338.33,321.25,269.58,222.08,174.17,325,172.5,165.42,-1332.92,-1332.08,-1331.67,222.5,175.83,-1320,233.33,333.33,234.58,235,285,332.5,325.42,171.67,-1327.92,-1329.58,172.5,224.58,223.75,277.08,185.42,-1320.42,183.75,179.17,-1330,317.08,268.33,269.58,311.67,210.83,-1336.67,315,262.92,216.67,213.75,161.25,264.58,-1340.83,312.92,314.58,-1329.17,220.83,164.58,317.5,167.5,-1333.75,270.42,-1334.17,267.08,221.25,271.25,318.75,-1333.33,221.67,274.17,172.92,320.42,312.5,212.5,164.58,162.92,-1343.75,204.58,252.08,-1342.92,250,-1352.5,197.5,-1346.25,-1346.25,205.83,150,-1352.5,257.92,317.5,218.75,164.17,264.17,318.75,318.75,152.92,249.58,196.25,294.17,-1355.83,195,-1367.5,181.25,132.92,284.17,243.33,190.83,-1359.17,143.33,-1354.58,147.92,145.83,297.08,195.83,244.58" "1,1,1,0,1,0,0,1,1,0,1,1,1,0,0,1,0,1,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,0,1,1,1,1,1,1,0,1,0,1,1,0,0,0,1,0,1,1,0,0,1,1,1,0,0,0,0,1,0,0,1,1,0,0,1,0,1,1,1,1,1,1,1,0,1,0,1,0,1,0,1,1,0,0,1,1,1,1,1,1,1,0,0,1,1,0,0,0,1,1,0,0,1,1,0,0" "288.75,335,330.83,277.08,-1326.67,170,205.42,200.83,198.33,145.83,192.5,245.42,297.08,248.33,248.75,-1349.17,198.33,146.67,291.25,241.67,-1360,-1358.33,-1350.83,301.25,205,308.33,160,-1331.25,-1335.83,265,154.58,302.5,-1342.5,256.25,209.17,265.83,168.33,-1324.58,275,222.92,219.58,321.25,275.83,-1317.08,-1307.92,187.08,186.25,340,344.58,237.92,234.58,177.92,223.75,316.67,315.42,167.08,265.42,262.5,209.17,-1348.33,148.75,299.58,300.83,304.58,-1347.08,156.67,-1340.42,-1345.42,200.42,250.83,251.25,-1347.92,203.33,204.17,209.17,162.08,260.42,162.08,162.5,313.33,259.17,-1344.17,-1347.08,296.25,-1354.17,148.75,202.08,149.58,200,248.75,200,199.58,299.58,252.5,299.17,300.42,147.08,-1354.58,250.83,255.42,-1328.75,317.92,217.92,169.58,-1333.75,164.58,208.75,159.58,208.33,256.67,156.67,254.58,296.67,-1360.83,-1374.17,280,-1367.92,182.08,-1357.08,141.25,-1360.83,294.17,195,203.75,304.58" "1,0,1,1,1,1,1,1,0,0,1,0,0,1,1,0,0,1,1,1,1,1,0,0,0,1,1,1,0,0,0,1,0,0,1,0,1,0,0,0,1,1,1,0,0,1,1,1,0,1,1,1,1,0,0,1,0,1,1,1,0,1,1,0,0,0,0,1,0,1,1,0,1,1,0,1,1,0,1,0,0,0,1,1,0,0,0,0,0,1,1,1,1,1,0,0,0,1,0,0,1,0,0,1,1,1,1,1,0,1,1,0,0,1,0,0,1,1,0,1,0,0,0,0,1" "-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" "0,0,1,0,0,1,1,1,1,0,1,0,1,1,0,0,0,1,0,1,1,0,1,0,0,1,1,0,0,0,1,1,1,0,1,0,1,1,0,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,0,1,0,1,0,1,1,1,0,1,0,0,1,0,0,1,1,0,1,1,0,1,1,1,1,0,0,0,1,1,1,1,0,1,1,1,0,1,0,0,0,0,0,0,1,0,1,1,0,1,1,0,0,1,0,1,1,0,1,1,1,1,1,1,1,0,0,1,1,0,1"
writetable(T,'myfile.csv')
##### 댓글 수: 1표시숨기기 없음
Oliver Steiner 2023년 2월 2일
thank you!!!

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### 추가 답변(2개)

dpb 2023년 2월 1일
Moved: Image Analyst 2023년 2월 1일
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...
##### 댓글 수: 1표시숨기기 없음
Oliver Steiner 2023년 2월 2일
편집: Oliver Steiner 2023년 2월 2일
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 2023년 2월 1일
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.
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Image Analyst 2023년 2월 3일
>> Filteringnoiseinmatlab
Unable to find file or directory 'expResEye_P01_AllB.mat'.
Error in Filteringnoiseinmatlab (line 41)

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