It would help to know what the data are, and what you want to do with the NaN values.
That aside, just plot all but the first column as a matrix —
A1 = readmatrix('IDT results.xlsx')
A1 =
1.0000 NaN -10.7900 -10.7000 -10.8700 -11.4100 -12.1600 -12.5300 -12.2800 -11.5000
2.0000 -11.7000 -11.2000 -11.0700 -11.4700 -12.0000 -12.5500 -12.3000 -11.0400 NaN
3.0000 NaN -12.3000 -11.9000 -12.0000 -12.2000 -12.3900 -12.5000 -12.2500 -11.0400
4.0000 -13.9000 -13.2100 -13.1500 -13.2000 -12.8700 -12.8700 -12.2700 -11.8600 NaN
5.0000 NaN -14.9300 -14.5000 -14.3000 -13.6000 -12.9000 -12.3000 -11.6700 -10.3700
6.0000 -18.0700 -16.9600 -16.4300 -15.9200 -13.9000 -12.8400 -12.3500 -12.1100 NaN
7.0000 NaN -19.8000 -18.2300 -16.9200 -14.5000 -13.1000 -12.8000 -12.2000 -11.2000
8.0000 -23.6000 -21.8900 -19.2000 -15.8000 -13.6000 -12.6000 -12.3000 -12.2000 NaN
9.0000 NaN -24.6100 -22.2400 -18.4900 -15.0200 -13.2500 -12.4500 -12.5000 -12.1000
10.0000 -26.2000 -26.0000 -23.9000 -18.2000 -14.0500 -12.7000 -12.7000 -12.9000 NaN
An alternative approach would be to create ‘x’ and ‘y’ vectors or lengths 17 and 9 and then use that with meshgrid or ndgrid to create (17x9) matrices to use with the scatteredInterpolant function.and the last 9 columns of the matrix (all reshaped to produce column vectors) to create an interpolated matrix.
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