comparing between two cell arrays
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we have two cell arrays that we would like to compare. the first of size 3x67 call it A and the second is of size 3x2 call it B. each row of the two cell arrays represent the data for the same day so we would like to compare the cells in the first row of A by the cell in the first row of B and so on. we are looking after the columnS "fof2" and "hmf2" from the cell in B, we will check the timimg in hours and minutes from the Date columns between this cell and the cells in A, and add to each cell in A the corresponding data for the columns "fof2" and "hmf2", it is not neccesary that we find exactly matching timings it is enough for them to be with in +-15mins range from each other. I am having an issue with the comparison between cell arrays, so if anyoe can help me in finding an effecient and easy way to do this, I attach the two cell array that I am working with.
Thanks in advance.
採用された回答
Star Strider
2022 年 12 月 11 日
I am not certain what result you want.
Try this, and if it works, loop through the elements of ‘A’ and ‘B’ for all the necessary combinations. Note that in at least one for the ‘B’ table, ‘hmF2’ is actually 'hmF2 ' with an extra space that creates problems with the variable name referencing. If all the resulting timetables have the same variables in the same locations, numerical referencing will work.
LD = load(websave('A&B','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1227457/A&B.mat'))
LD = struct with fields:
A: {3×67 cell}
B: {3×2 cell}
A = LD.A
A = 3×67 cell array
{[254]} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } { 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} { 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} { 0×0 double} { 0×0 double} { 0×0 double} { 0×0 double} { 0×0 double}
{[255]} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table }
{[256]} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} { 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} { 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} { 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} { 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} { 0×0 double} { 0×0 double} { 0×0 double} { 0×0 double} { 0×0 double} { 0×0 double} { 0×0 double} { 0×0 double}
B = LD.B
B = 3×2 cell array
{[254]} {63×10 table}
{[255]} {20×10 table}
{[256]} {22×10 table}
A12 = A{1,2}
A12 = 103×9 table
YEAR MONTH DAY HOUR MIN GDALT NE8 Date DoY
____ _____ ___ ____ ___ _____ _________ ________________ ___
2007 9 11 15 20 105 NaN 2007-09-11-15:20 254
2007 9 11 15 20 120 NaN 2007-09-11-15:20 254
2007 9 11 15 20 135 6.7e+11 2007-09-11-15:20 254
2007 9 11 15 20 150 1.789e+12 2007-09-11-15:20 254
2007 9 11 15 20 165 3.58e+11 2007-09-11-15:20 254
2007 9 11 15 20 180 1.95e+11 2007-09-11-15:20 254
2007 9 11 15 20 195 1.9e+11 2007-09-11-15:20 254
2007 9 11 15 20 210 2.07e+11 2007-09-11-15:20 254
2007 9 11 15 20 225 2.35e+11 2007-09-11-15:20 254
2007 9 11 15 20 240 2.64e+11 2007-09-11-15:20 254
2007 9 11 15 20 255 2.87e+11 2007-09-11-15:20 254
2007 9 11 15 20 270 3.08e+11 2007-09-11-15:20 254
2007 9 11 15 20 285 3.34e+11 2007-09-11-15:20 254
2007 9 11 15 20 300 3.66e+11 2007-09-11-15:20 254
2007 9 11 15 20 315 3.69e+11 2007-09-11-15:20 254
2007 9 11 15 20 330 3.69e+11 2007-09-11-15:20 254
A12 = A12(:,[8 1:7 9])
A12 = 103×9 table
Date YEAR MONTH DAY HOUR MIN GDALT NE8 DoY
________________ ____ _____ ___ ____ ___ _____ _________ ___
2007-09-11-15:20 2007 9 11 15 20 105 NaN 254
2007-09-11-15:20 2007 9 11 15 20 120 NaN 254
2007-09-11-15:20 2007 9 11 15 20 135 6.7e+11 254
2007-09-11-15:20 2007 9 11 15 20 150 1.789e+12 254
2007-09-11-15:20 2007 9 11 15 20 165 3.58e+11 254
2007-09-11-15:20 2007 9 11 15 20 180 1.95e+11 254
2007-09-11-15:20 2007 9 11 15 20 195 1.9e+11 254
2007-09-11-15:20 2007 9 11 15 20 210 2.07e+11 254
2007-09-11-15:20 2007 9 11 15 20 225 2.35e+11 254
2007-09-11-15:20 2007 9 11 15 20 240 2.64e+11 254
2007-09-11-15:20 2007 9 11 15 20 255 2.87e+11 254
2007-09-11-15:20 2007 9 11 15 20 270 3.08e+11 254
2007-09-11-15:20 2007 9 11 15 20 285 3.34e+11 254
2007-09-11-15:20 2007 9 11 15 20 300 3.66e+11 254
2007-09-11-15:20 2007 9 11 15 20 315 3.69e+11 254
2007-09-11-15:20 2007 9 11 15 20 330 3.69e+11 254
B12 = B{1,2}
B12 = 63×10 table
Date CS foF2 foF1 foEs foE hmE hmF2 hmF1 DoY
___________________ ___ ____ _____ ____ ___ ___ _____ _____ ___
11-09-2007 00:00:00 999 4.8 NaN NaN NaN NaN 350.3 NaN 254
11-09-2007 00:15:00 999 4.4 NaN NaN NaN NaN 302.4 NaN 254
11-09-2007 00:30:00 0 4.6 NaN NaN NaN 110 NaN NaN 254
11-09-2007 01:00:00 100 4.6 NaN NaN NaN 110 297.5 NaN 254
11-09-2007 01:15:00 100 4.3 NaN NaN NaN 110 264.1 NaN 254
11-09-2007 01:30:03 100 4.5 NaN NaN NaN 110 269.7 NaN 254
11-09-2007 01:45:02 100 4.6 NaN NaN NaN 110 286.4 NaN 254
11-09-2007 02:00:00 100 4.7 NaN NaN NaN 110 277.6 NaN 254
11-09-2007 02:15:00 100 4.4 NaN NaN NaN 110 272.6 NaN 254
11-09-2007 02:30:00 100 3.4 NaN NaN NaN 110 224.7 NaN 254
11-09-2007 02:45:00 100 4.6 NaN NaN NaN 110 271.7 NaN 254
11-09-2007 03:00:00 100 5.7 NaN NaN NaN 110 276 NaN 254
11-09-2007 03:15:00 100 5.8 NaN NaN NaN 110 275.3 NaN 254
11-09-2007 03:30:00 100 5.7 NaN NaN NaN 110 253.6 NaN 254
11-09-2007 03:45:00 100 4.2 NaN NaN NaN 110 245.4 NaN 254
11-09-2007 04:00:00 100 5.8 NaN NaN NaN 110 270.6 NaN 254
TTA12 = table2timetable(A12)
TTA12 = 103×8 timetable
Date YEAR MONTH DAY HOUR MIN GDALT NE8 DoY
________________ ____ _____ ___ ____ ___ _____ _________ ___
2007-09-11-15:20 2007 9 11 15 20 105 NaN 254
2007-09-11-15:20 2007 9 11 15 20 120 NaN 254
2007-09-11-15:20 2007 9 11 15 20 135 6.7e+11 254
2007-09-11-15:20 2007 9 11 15 20 150 1.789e+12 254
2007-09-11-15:20 2007 9 11 15 20 165 3.58e+11 254
2007-09-11-15:20 2007 9 11 15 20 180 1.95e+11 254
2007-09-11-15:20 2007 9 11 15 20 195 1.9e+11 254
2007-09-11-15:20 2007 9 11 15 20 210 2.07e+11 254
2007-09-11-15:20 2007 9 11 15 20 225 2.35e+11 254
2007-09-11-15:20 2007 9 11 15 20 240 2.64e+11 254
2007-09-11-15:20 2007 9 11 15 20 255 2.87e+11 254
2007-09-11-15:20 2007 9 11 15 20 270 3.08e+11 254
2007-09-11-15:20 2007 9 11 15 20 285 3.34e+11 254
2007-09-11-15:20 2007 9 11 15 20 300 3.66e+11 254
2007-09-11-15:20 2007 9 11 15 20 315 3.69e+11 254
2007-09-11-15:20 2007 9 11 15 20 330 3.69e+11 254
TTB12 = table2timetable(B12)
TTB12 = 63×9 timetable
Date CS foF2 foF1 foEs foE hmE hmF2 hmF1 DoY
___________________ ___ ____ _____ ____ ___ ___ _____ _____ ___
11-09-2007 00:00:00 999 4.8 NaN NaN NaN NaN 350.3 NaN 254
11-09-2007 00:15:00 999 4.4 NaN NaN NaN NaN 302.4 NaN 254
11-09-2007 00:30:00 0 4.6 NaN NaN NaN 110 NaN NaN 254
11-09-2007 01:00:00 100 4.6 NaN NaN NaN 110 297.5 NaN 254
11-09-2007 01:15:00 100 4.3 NaN NaN NaN 110 264.1 NaN 254
11-09-2007 01:30:03 100 4.5 NaN NaN NaN 110 269.7 NaN 254
11-09-2007 01:45:02 100 4.6 NaN NaN NaN 110 286.4 NaN 254
11-09-2007 02:00:00 100 4.7 NaN NaN NaN 110 277.6 NaN 254
11-09-2007 02:15:00 100 4.4 NaN NaN NaN 110 272.6 NaN 254
11-09-2007 02:30:00 100 3.4 NaN NaN NaN 110 224.7 NaN 254
11-09-2007 02:45:00 100 4.6 NaN NaN NaN 110 271.7 NaN 254
11-09-2007 03:00:00 100 5.7 NaN NaN NaN 110 276 NaN 254
11-09-2007 03:15:00 100 5.8 NaN NaN NaN 110 275.3 NaN 254
11-09-2007 03:30:00 100 5.7 NaN NaN NaN 110 253.6 NaN 254
11-09-2007 03:45:00 100 4.2 NaN NaN NaN 110 245.4 NaN 254
11-09-2007 04:00:00 100 5.8 NaN NaN NaN 110 270.6 NaN 254
TTAB12 = synchronize(TTA12,TTB12)
TTAB12 = 64×17 timetable
Date YEAR MONTH DAY HOUR MIN GDALT NE8 DoY_TTA12 CS foF2 foF1 foEs foE hmE hmF2 hmF1 DoY_TTB12
________________ ____ _____ ___ ____ ___ _____ ___ _________ ___ ____ _____ ____ ___ ___ _____ _____ _________
2007-09-11-00:00 NaN NaN NaN NaN NaN NaN NaN NaN 999 4.8 NaN NaN NaN NaN 350.3 NaN 254
2007-09-11-00:15 NaN NaN NaN NaN NaN NaN NaN NaN 999 4.4 NaN NaN NaN NaN 302.4 NaN 254
2007-09-11-00:30 NaN NaN NaN NaN NaN NaN NaN NaN 0 4.6 NaN NaN NaN 110 NaN NaN 254
2007-09-11-01:00 NaN NaN NaN NaN NaN NaN NaN NaN 100 4.6 NaN NaN NaN 110 297.5 NaN 254
2007-09-11-01:15 NaN NaN NaN NaN NaN NaN NaN NaN 100 4.3 NaN NaN NaN 110 264.1 NaN 254
2007-09-11-01:30 NaN NaN NaN NaN NaN NaN NaN NaN 100 4.5 NaN NaN NaN 110 269.7 NaN 254
2007-09-11-01:45 NaN NaN NaN NaN NaN NaN NaN NaN 100 4.6 NaN NaN NaN 110 286.4 NaN 254
2007-09-11-02:00 NaN NaN NaN NaN NaN NaN NaN NaN 100 4.7 NaN NaN NaN 110 277.6 NaN 254
2007-09-11-02:15 NaN NaN NaN NaN NaN NaN NaN NaN 100 4.4 NaN NaN NaN 110 272.6 NaN 254
2007-09-11-02:30 NaN NaN NaN NaN NaN NaN NaN NaN 100 3.4 NaN NaN NaN 110 224.7 NaN 254
2007-09-11-02:45 NaN NaN NaN NaN NaN NaN NaN NaN 100 4.6 NaN NaN NaN 110 271.7 NaN 254
2007-09-11-03:00 NaN NaN NaN NaN NaN NaN NaN NaN 100 5.7 NaN NaN NaN 110 276 NaN 254
2007-09-11-03:15 NaN NaN NaN NaN NaN NaN NaN NaN 100 5.8 NaN NaN NaN 110 275.3 NaN 254
2007-09-11-03:30 NaN NaN NaN NaN NaN NaN NaN NaN 100 5.7 NaN NaN NaN 110 253.6 NaN 254
2007-09-11-03:45 NaN NaN NaN NaN NaN NaN NaN NaN 100 4.2 NaN NaN NaN 110 245.4 NaN 254
2007-09-11-04:00 NaN NaN NaN NaN NaN NaN NaN NaN 100 5.8 NaN NaN NaN 110 270.6 NaN 254
VN = TTAB12.Properties.VariableNames
VN = 1×17 cell array
{'YEAR'} {'MONTH'} {'DAY'} {'HOUR'} {'MIN'} {'GDALT'} {'NE8'} {'DoY_TTA12'} {'CS'} {'foF2'} {'foF1 '} {'foEs'} {'foE'} {'hmE'} {'hmF2 '} {'hmF1 '} {'DoY_TTB12'}
VN{15}
ans = 'hmF2 '
TTAB12_Result = TTAB12(:,[10 15])
TTAB12_Result = 64×2 timetable
Date foF2 hmF2
________________ ____ _____
2007-09-11-00:00 4.8 350.3
2007-09-11-00:15 4.4 302.4
2007-09-11-00:30 4.6 NaN
2007-09-11-01:00 4.6 297.5
2007-09-11-01:15 4.3 264.1
2007-09-11-01:30 4.5 269.7
2007-09-11-01:45 4.6 286.4
2007-09-11-02:00 4.7 277.6
2007-09-11-02:15 4.4 272.6
2007-09-11-02:30 3.4 224.7
2007-09-11-02:45 4.6 271.7
2007-09-11-03:00 5.7 276
2007-09-11-03:15 5.8 275.3
2007-09-11-03:30 5.7 253.6
2007-09-11-03:45 4.2 245.4
2007-09-11-04:00 5.8 270.6
.
4 件のコメント
Salma fathi
2022 年 12 月 13 日
編集済み: Salma fathi
2022 年 12 月 13 日
Thank you very much for your reply. Yes this is exactly what I wanted, I did not now such function existed, it is realy so helpful. Another thing though,

in the above image (this is diffrent data from the one attached but serve the same goal), row 12 is from table A, and since there is no matching for it in B it will just have NaN values. so if insted we can customize the method to let row 12 have the values that we have in row 13 where it is the closest timing for it would be much better. Is there any method we can use to acheive this?
Thanks again.
Star Strider
2022 年 12 月 13 日
My pleasure!
LD = load(websave('A&B','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1227457/A&B.mat'))
LD = struct with fields:
A: {3×67 cell}
B: {3×2 cell}
A = LD.A
A = 3×67 cell array
{[254]} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } { 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} { 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} { 0×0 double} { 0×0 double} { 0×0 double} { 0×0 double} { 0×0 double}
{[255]} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table } {103×9 table }
{[256]} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} {103×9 table} { 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} { 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} { 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} { 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} { 0×0 double} { 0×0 double} { 0×0 double} { 0×0 double} { 0×0 double} { 0×0 double} { 0×0 double} { 0×0 double}
B = LD.B
B = 3×2 cell array
{[254]} {63×10 table}
{[255]} {20×10 table}
{[256]} {22×10 table}
A12 = A{1,2};
A12 = A12(:,[8 1:7 9]);
B12 = B{1,2};
TTA12 = table2timetable(A12);
TTB12 = table2timetable(B12);
TTAB12 = synchronize(TTA12,TTB12);
VN = TTAB12.Properties.VariableNames;
VN{15};
TTAB12_Result = TTAB12(:,[10 15])
TTAB12_Result = 64×2 timetable
Date foF2 hmF2
________________ ____ _____
2007-09-11-00:00 4.8 350.3
2007-09-11-00:15 4.4 302.4
2007-09-11-00:30 4.6 NaN
2007-09-11-01:00 4.6 297.5
2007-09-11-01:15 4.3 264.1
2007-09-11-01:30 4.5 269.7
2007-09-11-01:45 4.6 286.4
2007-09-11-02:00 4.7 277.6
2007-09-11-02:15 4.4 272.6
2007-09-11-02:30 3.4 224.7
2007-09-11-02:45 4.6 271.7
2007-09-11-03:00 5.7 276
2007-09-11-03:15 5.8 275.3
2007-09-11-03:30 5.7 253.6
2007-09-11-03:45 4.2 245.4
2007-09-11-04:00 5.8 270.6
TTAB12_Result = fillmissing(TTAB12_Result, 'nearest')
TTAB12_Result = 64×2 timetable
Date foF2 hmF2
________________ ____ _____
2007-09-11-00:00 4.8 350.3
2007-09-11-00:15 4.4 302.4
2007-09-11-00:30 4.6 302.4
2007-09-11-01:00 4.6 297.5
2007-09-11-01:15 4.3 264.1
2007-09-11-01:30 4.5 269.7
2007-09-11-01:45 4.6 286.4
2007-09-11-02:00 4.7 277.6
2007-09-11-02:15 4.4 272.6
2007-09-11-02:30 3.4 224.7
2007-09-11-02:45 4.6 271.7
2007-09-11-03:00 5.7 276
2007-09-11-03:15 5.8 275.3
2007-09-11-03:30 5.7 253.6
2007-09-11-03:45 4.2 245.4
2007-09-11-04:00 5.8 270.6
Here, I chose to fill with the 'nearest' value. Similar options are 'previous' and 'next'. (See the documentation I linked to for details.) Choose the method that works best in your application.
The code is unchanged from the previous version, with the addition of this assignment:
TTAB12_Result = fillmissing(TTAB12_Result, 'nearest')
Another option of course is:
TTAB12_Result = fillmissing(TTAB12(:,[10 15]), 'nearest')
It depends on whether you want to see the original result before calling fillmissing.
I am not certain what you want to do, so I stopped here. If this does what you want, it would be straightforward to create nested loops to synchronize each ‘A’ cell with each ‘B’ cell using this code, and save the resulting timetable to a new cell.
.
Salma fathi
2022 年 12 月 15 日
Thank you so much this helped a lot, exactly what I was looking for. I appreciate all the assisstance. Thank you
Star Strider
2022 年 12 月 15 日
As always, my pleasure!
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