How to average first 7 values of all the column and put into new row then next 7 untill the end of data

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Hi,
I have been looking around the internet how to insert the empty row after 7 rows vice versa but failed to find any thing. Attached is the excel. Can anyone help!

采纳的回答

Voss
Voss 2022-7-13
Does this work for what you want to do?
% read the file, skipping the first 8 lines, and make a table t
% using the variable names on line 9:
t = readtable('Export.6u55jl8n.000000.csv', ...
'NumHeaderLines',8, ...
'PreserveVariableNames',true)
t = 21306×12 table
x y x (pix)[pix] y (pix)[pix] x (mm)[mm] y (mm)[mm] U pix[pix] V pix[pix] U[m/s] V[m/s] Length[m/s] Status __ _ ____________ ____________ __________ __________ __________ __________ ______ ______ ___________ ______ 0 0 -1173.5 -248.5 -218.58 -46.287 0 0 0 0 0 4 1 0 -1157.5 -248.5 -215.6 -46.287 0 0 0 0 0 4 2 0 -1141.5 -248.5 -212.62 -46.287 0 0 0 0 0 4 3 0 -1125.5 -248.5 -209.64 -46.287 0 0 0 0 0 4 4 0 -1109.5 -248.5 -206.66 -46.287 0 0 0 0 0 4 5 0 -1093.5 -248.5 -203.68 -46.287 0 0 0 0 0 4 6 0 -1077.5 -248.5 -200.7 -46.287 0 0 0 0 0 4 7 0 -1061.5 -248.5 -197.72 -46.287 0 0 0 0 0 4 8 0 -1045.5 -248.5 -194.74 -46.287 0 0 0 0 0 4 9 0 -1029.5 -248.5 -191.76 -46.287 0 0 0 0 0 4 10 0 -1013.5 -248.5 -188.78 -46.287 0 0 0 0 0 4 11 0 -997.5 -248.5 -185.8 -46.287 0 0 0 0 0 4 12 0 -981.5 -248.5 -182.82 -46.287 0 0 0 0 0 4 13 0 -965.5 -248.5 -179.84 -46.287 0 0 0 0 0 4 14 0 -949.5 -248.5 -176.86 -46.287 0 0 0 0 0 4 15 0 -933.5 -248.5 -173.88 -46.287 0 0 0 0 0 4
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Voss
Voss 2022-7-13
OK
t = readtable('Export.6u55jl8n.000000.csv', ...
'NumHeaderLines',8, ...
'PreserveVariableNames',true);
% easier to work with a matrix of data:
data = table2array(t);
% in case the total number of rows is not a multiple of 7,
% add rows of NaNs to fill it out:
[N,M] = size(data);
n = mod(N,7);
if n ~= 0
data = [data; NaN(7-n,M)];
N = N+7-n;
end
% reshape data to have size 7 in the third dimension
data = permute(reshape(data.',[M 7 N/7]),[3 1 2]);
size(data)
ans = 1×3
3044 12 7
% calculate the mean in the third dimension
% and append it to the end of data
% (using 'omitnan' to prevent NaNs from affecting the mean)
data(:,:,end+1) = mean(data,3,'omitnan');
% reshape back to 2D with M columns
data = reshape(permute(data,[3 1 2]),[],M)
data = 24352×12
1.0e+03 * 0 0 -1.1735 -0.2485 -0.2186 -0.0463 0 0 0 0 0 0.0040 0.0010 0 -1.1575 -0.2485 -0.2156 -0.0463 0 0 0 0 0 0.0040 0.0020 0 -1.1415 -0.2485 -0.2126 -0.0463 0 0 0 0 0 0.0040 0.0030 0 -1.1255 -0.2485 -0.2096 -0.0463 0 0 0 0 0 0.0040 0.0040 0 -1.1095 -0.2485 -0.2067 -0.0463 0 0 0 0 0 0.0040 0.0050 0 -1.0935 -0.2485 -0.2037 -0.0463 0 0 0 0 0 0.0040 0.0060 0 -1.0775 -0.2485 -0.2007 -0.0463 0 0 0 0 0 0.0040 0.0030 0 -1.1255 -0.2485 -0.2096 -0.0463 0 0 0 0 0 0.0040 0.0070 0 -1.0615 -0.2485 -0.1977 -0.0463 0 0 0 0 0 0.0040 0.0080 0 -1.0455 -0.2485 -0.1947 -0.0463 0 0 0 0 0 0.0040
% the first few new "average" rows:
data([8 16 24 32],:)
ans = 4×12
1.0e+03 * 0.0030 0 -1.1255 -0.2485 -0.2096 -0.0463 0 0 0 0 0 0.0040 0.0100 0 -1.0135 -0.2485 -0.1888 -0.0463 0 0 0 0 0 0.0040 0.0170 0 -0.9015 -0.2485 -0.1679 -0.0463 0 0 0 0 0 0.0040 0.0240 0 -0.7895 -0.2485 -0.1471 -0.0463 0 0 0 0 0 0.0040
Voss
Voss 2022-7-13
You can write the new data to file, with the same header, as follows:
% get the header separately:
C = readcell('Export.6u55jl8n.000000.csv');
header = C(1:9,:);
% with some conditioning to handle missing cells for writecell later on:
header(cellfun(@(x)all(ismissing(x)),header)) = {[]}
header = 9×12 cell array
{'>>*HEADER*<<' } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double} {0×0 double} {0×0 double } {0×0 double} {'FileID:DSExport.CSV' } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double} {0×0 double} {0×0 double } {0×0 double} {'Version:2' } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double} {0×0 double} {0×0 double } {0×0 double} {'GridSize:{Width=159' } {'Height=134}'} {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double} {0×0 double} {0×0 double } {0×0 double} {'Originator:exp4.Project 2021-12-02 13:18:27.Run 13:32:04.Adaptive PIV'} {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double} {0×0 double} {0×0 double } {0×0 double} {'CameraInfo:HiSenseZyla.0' } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double} {0×0 double} {0×0 double } {0×0 double} {'TimeStamp:#2' } {'0.067 s' } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double} {0×0 double} {0×0 double } {0×0 double} {'>>*DATA*<<' } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double } {0×0 double} {0×0 double} {0×0 double } {0×0 double} {'x' } {'y' } {'x (pix)[pix]'} {'y (pix)[pix]'} {'x (mm)[mm]'} {'y (mm)[mm]'} {'U pix[pix]'} {'V pix[pix]'} {'U[m/s]' } {'V[m/s]' } {'Length[m/s]'} {'Status' }
% this time, don't have to do readtable, just get the data from the
% cell array we already have:
data = cell2mat(C(10:end,:));
% ---- begin same averaging process as before ----
% in case the total number of rows is not a multiple of 7,
% add rows of NaNs to fill it out:
[N,M] = size(data);
n = mod(N,7);
if n ~= 0
data = [data; NaN(7-n,M)];
N = N+7-n;
end
% reshape data to have size 7 in the third dimension
data = permute(reshape(data.',[M 7 N/7]),[3 1 2]);
% calculate the mean in the third dimension
% and append it to the end of data
% (using 'omitnan' to prevent NaNs from affecting the mean)
data(:,:,end+1) = mean(data,3,'omitnan');
% reshape back to 2D with M columns
data = reshape(permute(data,[3 1 2]),[],M);
% ---- end same averaging process as before ----
% now combine the header with the new data and write to file:
writecell([header; num2cell(data)],'new_Export.csv');
% check the contents (note the average rows are there):
type new_Export.csv
>>*HEADER*<<,,,,,,,,,,, FileID:DSExport.CSV,,,,,,,,,,, Version:2,,,,,,,,,,, GridSize:{Width=159,Height=134},,,,,,,,,, Originator:exp4.Project 2021-12-02 13:18:27.Run 13:32:04.Adaptive PIV,,,,,,,,,,, CameraInfo:HiSenseZyla.0,,,,,,,,,,, TimeStamp:#2,0.067 s,,,,,,,,,, >>*DATA*<<,,,,,,,,,,, x,y,x (pix)[pix],y (pix)[pix],x (mm)[mm],y (mm)[mm],U pix[pix],V pix[pix],U[m/s],V[m/s],Length[m/s],Status 0,0,-1173.5,-248.5,-218.5810953,-46.2866649,0,0,0,0,0,4 1,0,-1157.5,-248.5,-215.6008631,-46.2866649,0,0,0,0,0,4 2,0,-1141.5,-248.5,-212.6206309,-46.2866649,0,0,0,0,0,4 3,0,-1125.5,-248.5,-209.6404135,-46.2866649,0,0,0,0,0,4 4,0,-1109.5,-248.5,-206.6601813,-46.2866649,0,0,0,0,0,4 5,0,-1093.5,-248.5,-203.679949,-46.2866649,0,0,0,0,0,4 6,0,-1077.5,-248.5,-200.6997317,-46.2866649,0,0,0,0,0,4 3,0,-1125.5,-248.5,-209.640409257143,-46.2866649,0,0,0,0,0,4 7,0,-1061.5,-248.5,-197.7194995,-46.2866649,0,0,0,0,0,4 8,0,-1045.5,-248.5,-194.7392672,-46.2866649,0,0,0,0,0,4 9,0,-1029.5,-248.5,-191.759035,-46.2866649,0,0,0,0,0,4 10,0,-1013.5,-248.5,-188.7788177,-46.2866649,0,0,0,0,0,4 11,0,-997.5,-248.5,-185.7985854,-46.2866649,0,0,0,0,0,4 12,0,-981.5,-248.5,-182.8183532,-46.2866649,0,0,0,0,0,4 13,0,-965.5,-248.5,-179.8381358,-46.2866649,0,0,0,0,0,4 10,0,-1013.5,-248.5,-188.7788134,-46.2866649,0,0,0,0,0,4 14,0,-949.5,-248.5,-176.8579036,-46.2866649,0,0,0,0,0,4 15,0,-933.5,-248.5,-173.8776714,-46.2866649,0,0,0,0,0,4 16,0,-917.5,-248.5,-170.8974391,-46.2866649,0,0,0,0,0,4 17,0,-901.5,-248.5,-167.9172218,-46.2866649,0,0,0,0,0,4 18,0,-885.5,-248.5,-164.9369895,-46.2866649,0,0,0,0,0,4 19,0,-869.5,-248.5,-161.9567573,-46.2866649,0,0,0,0,0,4 20,0,-853.5,-248.5,-158.97654,-46.2866649,0,0,0,0,0,4 17,0,-901.5,-248.5,-167.917217528571,-46.2866649,0,0,0,0,0,4 21,0,-837.5,-248.5,-155.9963077,-46.2866649,0,0,0,0,0,4 22,0,-821.5,-248.5,-153.0160755,-46.2866649,0,0,0,0,0,4 23,0,-805.5,-248.5,-150.0358433,-46.2866649,0,0,0,0,0,4 24,0,-789.5,-248.5,-147.0556259,-46.2866649,0,0,0,0,0,4 25,0,-773.5,-248.5,-144.0753937,-46.2866649,0,0,0,0,0,4 26,0,-757.5,-248.5,-141.0951614,-46.2866649,0,0,0,0,0,4 27,0,-741.5,-248.5,-138.1149441,-46.2866649,0,0,0,0,0,4 24,0,-789.5,-248.5,-147.055621657143,-46.2866649,0,0,0,0,0,4 28,0,-725.5,-248.5,-135.1347119,-46.2866649,0,0,0,0,0,4 29,0,-709.5,-248.5,-132.1544796,-46.2866649,0,0,0,0,0,4 30,0,-693.5,-248.5,-129.1742623,-46.2866649,0,0,0,0,0,4 31,0,-677.5,-248.5,-126.19403,-46.2866649,0,0,0,0,0,4 32,0,-661.5,-248.5,-123.2137978,-46.2866649,0,0,0,0,0,4 33,0,-645.5,-248.5,-120.233573,-46.2866649,0,0,0,0,0,4 34,0,-629.5,-248.5,-117.2533408,-46.2866649,0,0,0,0,0,4 31,0,-677.5,-248.5,-126.194027914286,-46.2866649,0,0,0,0,0,4 35,0,-613.5,-248.5,-114.273116,-46.2866649,0,0,0,0,0,4 36,0,-597.5,-248.5,-111.2928838,-46.2866649,0,0,0,0,0,4 37,0,-581.5,-248.5,-108.312659,-46.2866649,0,0,0,0,0,4 38,0,-565.5,-248.5,-105.3324342,-46.2866649,0,0,0,0,0,4 39,0,-549.5,-248.5,-102.3522019,-46.2866649,0,0,0,0,0,4 40,0,-533.5,-248.5,-99.37197715,-46.2866649,0,0,0,0,0,4 41,0,-517.5,-248.5,-96.39174491,-46.2866649,0,0,0,0,0,4 38,0,-565.5,-248.5,-105.332430994286,-46.2866649,0,0,0,0,0,4 42,0,-501.5,-248.5,-93.41152012,-46.2866649,0,0,0,0,0,4 43,0,-485.5,-248.5,-90.43129534,-46.2866649,0,0,0,0,0,4 44,0,-469.5,-248.5,-87.4510631,-46.2866649,0,0,0,0,0,4 45,0,-453.5,-248.5,-84.47083831,-46.2866649,0,0,0,0,0,4 46,0,-437.5,-248.5,-81.49060607,-46.2866649,0,0,0,0,0,4 47,0,-421.5,-248.5,-78.51038128,-46.2866649,0,0,0,0,0,4 48,0,-405.5,-248.5,-75.53014904,-46.2866649,0,0,0,0,0,4 45,0,-453.5,-248.5,-84.47083618,-46.2866649,0,0,0,0,0,4 49,0,-389.5,-248.5,-72.54992425,-46.2866649,0,0,0,0,0,4 50,0,-373.5,-248.5,-69.56969947,-46.2866649,0,0,0,0,0,4 51,0,-357.5,-248.5,-66.58946723,-46.2866649,0,0,0,0,0,4 52,0,-341.5,-248.5,-63.60924244,-46.2866649,0,0,0,0,0,4 53,0,-325.5,-248.5,-60.62901393,-46.2866649,0,0,0,0,0,4 54,0,-309.5,-248.5,-57.64878541,-46.2866649,0,0,0,0,0,4 55,0,-293.5,-248.5,-54.6685569,-46.2866649,0,0,0,0,0,4 52,0,-341.5,-248.5,-63.6092413757143,-46.2866649,0,0,0,0,0,4 56,0,-277.5,-248.5,-51.68832839,-46.2866649,0,0,0,0,0,4 57,0,-261.5,-248.5,-48.70809987,-46.2866649,0,0,0,0,0,4 58,0,-245.5,-248.5,-45.72787136,-46.2866649,0,0,0,0,0,4 59,0,-229.5,-248.5,-42.74764284,-46.2866649,0,0,0,0,0,4 60,0,-213.5,-248.5,-39.76741806,-46.2866649,0,0,0,0,0,4 61,0,-197.5,-248.5,-36.78718954,-46.2866649,0,0,0,0,0,4 62,0,-181.5,-248.5,-33.80696103,-46.2866649,0,0,0,0,0,4 59,0,-229.5,-248.5,-42.7476444414286,-46.2866649,0,0,0,0,0,4 63,0,-165.5,-248.5,-30.82673252,-46.2866649,0,0,0,0,0,4 64,0,-149.5,-248.5,-27.846504,-46.2866649,0,0,0,0,0,4 65,0,-133.5,-248.5,-24.86627735,-46.2866649,0,0,0,0,0,4 66,0,-117.5,-248.5,-21.88604884,-46.2866649,0,0,0,0,0,4 67,0,-101.5,-248.5,-18.90582033,-46.2866649,0,0,0,0,0,4 68,0,-85.5,-248.5,-15.92559367,-46.2866649,0,0,0,0,0,4 69,0,-69.5,-248.5,-12.94536516,-46.2866649,0,0,0,0,0,4 66,0,-117.5,-248.5,-21.8860488385714,-46.2866649,0,0,0,0,0,4 70,0,-53.5,-248.5,-9.965137579,-46.2866649,0,0,0,0,0,4 71,0,-37.5,-248.5,-6.984909065,-46.2866649,0,0,0,0,0,4 72,0,-21.5,-248.5,-4.004681483,-46.2866649,0,0,0,0,0,4 73,0,-5.5,-248.5,-1.024453319,-46.2866649,0,0,0,0,0,4 74,0,10.5,-248.5,1.955774613,-46.2866649,0,0,0,0,0,4 75,0,26.5,-248.5,4.936002661,-46.2866649,0,0,0,0,0,4 76,0,42.5,-248.5,7.916230708,-46.2866649,0,0,0,0,0,4 73,0,-5.5,-248.5,-1.024453352,-46.2866649,0,0,0,0,0,4 77,0,58.5,-248.5,10.89645829,-46.2866649,0,0,0,0,0,4 78,0,74.5,-248.5,13.8766868,-46.2866649,0,0,0,0,0,4 79,0,90.5,-248.5,16.85691439,-46.2866649,0,0,0,0,0,4 80,0,106.5,-248.5,19.8371429,-46.2866649,0,0,0,0,0,4 81,0,122.5,-248.5,22.81736955,-46.2866649,0,0,0,0,0,4 82,0,138.5,-248.5,25.79759806,-46.2866649,0,0,0,0,0,4 83,0,154.5,-248.5,28.77782658,-46.2866649,0,0,0,0,0,4 80,0,106.5,-248.5,19.8371423671429,-46.2866649,0,0,0,0,0,4 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