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How to average first 7 values of all the column and put into new row then next 7 untill the end of data
조회 수: 2 (최근 30일)
이전 댓글 표시
muhammad choudhry
2022년 7월 13일
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!
채택된 답변
Voss
2022년 7월 13일
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)
댓글 수: 3
muhammad choudhry
2022년 7월 13일
No VOSS, that is not what I want. I want to add an empty row after every 7th row across the columns in the file until the end of the data, and average previous 7 values of each column and put into the that empty row ?
for example: 1 2 3 4 5 6 7 average value 8 9 10 11 12 13 14 average value until the data finish
Voss
2022년 7월 13일
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
2022년 7월 13일
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
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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
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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
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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
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48,0,-405.5,-248.5,-75.53014904,-46.2866649,0,0,0,0,0,4
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60,0,-213.5,-248.5,-39.76741806,-46.2866649,0,0,0,0,0,4
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62,0,-181.5,-248.5,-33.80696103,-46.2866649,0,0,0,0,0,4
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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
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120,0,746.5,-248.5,139.0462667,-46.2866649,0,0,0,0,0,4
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122,0,778.5,-248.5,145.0067163,-46.2866649,0,0,0,0,0,4
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118,5,714.5,-168.5,133.085804328571,-31.38552606,0,0,0,0,0,4
122,5,778.5,-168.5,145.0067163,-31.38552606,0,0,0,0,0,4
123,5...
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