I can't open that file in Excel to see how many rows it has, but readcell reads 2886 rows, the first 5 or 6 of which look like the header.
C = readcell('n_fot2017-01-12.xls')
C = 2886×12 cell array
Columns 1 through 7
{'Report template (Ra…'} {[01-Jan-2017 00:00:00]} {[<missing> ]} {[<missing> ]} {[<missing> ]} {[<missing> ]} {[<missing> ]}
{'Report template (Ra…'} {[01-May-2017 00:00:00]} {[<missing> ]} {[<missing> ]} {[<missing> ]} {[<missing> ]} {[<missing> ]}
{'Report template (Pr…'} {[22-Sep-2017 19:47:43]} {[<missing> ]} {[<missing> ]} {[<missing> ]} {[<missing> ]} {[<missing> ]}
{'Time series product…'} {'Kärnkraft prod. per…'} {'Gasturbin/diesel…'} {'Vindkraft prod. …'} {'Netto Exp/imp. p…'} {'Ospec. prod. per…'} {'Total prod. per …'}
{'Numeric time series…'} {'M273_x_SWE_x_x_x_1' } {'M275_x_SWE_x_x_x…'} {'M272_x_SWE_x_x_x…'} {'M645_x_SWE_x_x_x…'} {'M270_x_SWE_x_x_x…'} {'M500_x_SWE_x_x_x…'}
{'Numeric time series…'} {[<missing> ]} {[<missing> ]} {[<missing> ]} {[<missing> ]} {[<missing> ]} {[<missing> ]}
{[01-Jan-2017 00:00:00]} {[ 9.0744e+03]} {[ 0.8574]} {[ 3.6378e+03]} {[ -2.9196e+03]} {[ 0.9204]} {[ 1.6256e+04]}
{[01-Jan-2017 01:00:00]} {[ 9.0747e+03]} {[ 0.8508]} {[ 3.4295e+03]} {[ -2.9203e+03]} {[ 1.1083]} {[ 1.5964e+04]}
{[01-Jan-2017 02:00:00]} {[ 9.0749e+03]} {[ 0.8447]} {[ 3.2900e+03]} {[ -2.9965e+03]} {[ 1.0244]} {[ 1.5817e+04]}
{[01-Jan-2017 03:00:00]} {[ 9.0774e+03]} {[ 0.8266]} {[ 3.0532e+03]} {[ -2.8781e+03]} {[ 0.9999]} {[ 1.5543e+04]}
{[01-Jan-2017 04:00:00]} {[ 9.0780e+03]} {[ 0.8007]} {[ 2.9322e+03]} {[ -2.8557e+03]} {[ 0.8734]} {[ 1.5481e+04]}
{[01-Jan-2017 05:00:00]} {[ 9.0799e+03]} {[ 0.6707]} {[ 2.7872e+03]} {[ -2.6600e+03]} {[ 0.6983]} {[ 1.5365e+04]}
{[01-Jan-2017 06:00:00]} {[ 9.0826e+03]} {[ 0.6390]} {[ 2.6617e+03]} {[ -2.5739e+03]} {[ 0.0041]} {[ 1.5496e+04]}
{[01-Jan-2017 07:00:00]} {[ 9.0827e+03]} {[ 0.5710]} {[ 2.6110e+03]} {[ -2.3826e+03]} {[ 0.6768]} {[ 1.5607e+04]}
{[01-Jan-2017 08:00:00]} {[ 9.0827e+03]} {[ 0.5523]} {[ 2.5535e+03]} {[ -2.0771e+03]} {[ 0.6103]} {[ 1.5663e+04]}
{[01-Jan-2017 09:00:00]} {[ 9.0847e+03]} {[ 0.6233]} {[ 2.3920e+03]} {[ -2.0789e+03]} {[ 0.1009]} {[ 1.5974e+04]}
Columns 8 through 12
{[<missing> ]} {[<missing> ]} {[<missing> ]} {[<missing> ]} {[<missing> ]}
{[<missing> ]} {[<missing> ]} {[<missing> ]} {[<missing> ]} {[<missing> ]}
{[<missing> ]} {[<missing> ]} {[<missing> ]} {[<missing> ]} {[<missing> ]}
{'Solkraft prod. p…'} {'Vågkraft prod. p…'} {'Summa förbr. per…'} {'Övr.värmekraft p…'} {'Vattenkraft prod…'}
{'M301_x_SWE_x_x_x…'} {'M302_x_SWE_x_x_x…'} {'M501_x_SWE_x_x_x…'} {'M274_x_SWE_x_x_x…'} {'M271_x_SWE_x_x_x…'}
{[<missing> ]} {[<missing> ]} {[<missing> ]} {[<missing> ]} {[<missing> ]}
{[ 0.0359]} {[ 0]} {[ -1.3339e+04]} {[ 1.1257e+03]} {[ 2.4158e+03]}
{[ 0.0353]} {[ 0]} {[ -1.3047e+04]} {[ 1.0765e+03]} {[ 2.3812e+03]}
{[ 0.0262]} {[ 0]} {[ -1.2824e+04]} {[ 1.0955e+03]} {[ 2.3551e+03]}
{[ 0.0196]} {[ 0]} {[ -1.2668e+04]} {[ 1.1423e+03]} {[ 2.2680e+03]}
{[ 0.0181]} {[ 0]} {[ -1.2629e+04]} {[ 1.1585e+03]} {[ 2.3110e+03]}
{[ 0.0174]} {[ 0]} {[ -1.2708e+04]} {[ 1.1691e+03]} {[ 2.3275e+03]}
{[ 0.0191]} {[ 0]} {[ -1.2924e+04]} {[ 1.1955e+03]} {[ 2.5557e+03]}
{[ 0.0235]} {[ 0]} {[ -1.3227e+04]} {[ 1.1842e+03]} {[ 2.7278e+03]}
{[ 0.0258]} {[ 0]} {[ -1.3588e+04]} {[ 1.1659e+03]} {[ 2.8600e+03]}
{[ 0.1066]} {[ 0]} {[ -1.3897e+04]} {[ 1.1959e+03]} {[ 3.3006e+03]}
Evidently, readtable is interpreting 5 header rows and putting the remaining rows into a table with 2886-5 = 2881 rows.
T = readtable('n_fot2017-01-12.xls')
Warning: Column headers from the file were modified to make them valid MATLAB identifiers before creating variable names for the table. The original column headers are saved in the VariableDescriptions property.
Set 'VariableNamingRule' to 'preserve' to use the original column headers as table variable names.
Set 'VariableNamingRule' to 'preserve' to use the original column headers as table variable names.
T = 2881×12 table
TimeSeriesProductInstance_Beskrivning_ K_rnkraftProd_PerCO__SWE___ Gasturbin_dieselProd_PerCO__SWE___ VindkraftProd_PerCO__SWE___ NettoExp_imp_PerCO__SWE___ Ospec_Prod_PerCO__SWE___ TotalProd_PerCO__SWE___ SolkraftProd_PerCO__SWE___ V_gkraftProd_PerCO__SWE___ SummaF_rbr_PerCO__SWE___ x_vr_v_rmekraftProd_PerCO__SWE___ VattenkraftProd_PerCO__SWE___
______________________________________ ___________________________ __________________________________ ___________________________ __________________________ ________________________ _______________________ __________________________ __________________________ ________________________ _________________________________ _____________________________
NaT NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
01-Jan-2017 00:00:00 9074.4 0.85744 3637.8 -2919.6 0.92037 16256 0.035938 0 -13339 1125.7 2415.8
01-Jan-2017 01:00:00 9074.7 0.85076 3429.5 -2920.3 1.1083 15964 0.035288 0 -13047 1076.5 2381.2
01-Jan-2017 02:00:00 9074.9 0.84465 3290 -2996.5 1.0244 15817 0.026189 0 -12824 1095.5 2355.1
01-Jan-2017 03:00:00 9077.4 0.82665 3053.2 -2878.1 0.9999 15543 0.019635 0 -12668 1142.3 2268
01-Jan-2017 04:00:00 9078 0.80068 2932.2 -2855.7 0.87338 15481 0.018089 0 -12629 1158.5 2311
01-Jan-2017 05:00:00 9079.9 0.67075 2787.2 -2660 0.69828 15365 0.017403 0 -12708 1169.1 2327.5
01-Jan-2017 06:00:00 9082.6 0.63896 2661.7 -2573.9 0.00409 15496 0.019086 0 -12924 1195.5 2555.7
01-Jan-2017 07:00:00 9082.7 0.57101 2611 -2382.6 0.67683 15607 0.023495 0 -13227 1184.2 2727.8
01-Jan-2017 08:00:00 9082.7 0.55226 2553.5 -2077.1 0.61035 15663 0.025813 0 -13588 1165.9 2860
01-Jan-2017 09:00:00 9084.7 0.62331 2392 -2078.9 0.10089 15974 0.1066 0 -13897 1195.9 3300.6
01-Jan-2017 10:00:00 9085.5 1.0216 2243 -1612.9 0.00508 16105 0.90292 0 -14494 1212.7 3561.6
01-Jan-2017 11:00:00 9082.8 0.96721 2080.4 -1197 0.00387 16146 2.4625 0 -14951 1221 3758.2
01-Jan-2017 12:00:00 9085.3 1.0963 1968.2 -1153.4 0.00167 16371 2.5767 0 -15218 1217.6 4095.8
01-Jan-2017 13:00:00 9085.1 1.0842 2011.4 -1079 0.0002 16513 1.7942 0 -15435 1232.6 4181.4
01-Jan-2017 14:00:00 9084.7 0.97908 2076.3 -1023.3 9e-05 16764 0.43023 0 -15741 1246 4355.6
If you want to tell readtable that there are 6 header rows, you can do that, and then you'll get a table with 2886-6 = 2880 rows.
T = readtable('n_fot2017-01-12.xls','NumHeaderLines',6)
T = 2880×12 table
Var1 Var2 Var3 Var4 Var5 Var6 Var7 Var8 Var9 Var10 Var11 Var12
____________________ ______ _______ ______ _______ _______ _____ ________ ____ ______ ______ ______
01-Jan-2017 00:00:00 9074.4 0.85744 3637.8 -2919.6 0.92037 16256 0.035938 0 -13339 1125.7 2415.8
01-Jan-2017 01:00:00 9074.7 0.85076 3429.5 -2920.3 1.1083 15964 0.035288 0 -13047 1076.5 2381.2
01-Jan-2017 02:00:00 9074.9 0.84465 3290 -2996.5 1.0244 15817 0.026189 0 -12824 1095.5 2355.1
01-Jan-2017 03:00:00 9077.4 0.82665 3053.2 -2878.1 0.9999 15543 0.019635 0 -12668 1142.3 2268
01-Jan-2017 04:00:00 9078 0.80068 2932.2 -2855.7 0.87338 15481 0.018089 0 -12629 1158.5 2311
01-Jan-2017 05:00:00 9079.9 0.67075 2787.2 -2660 0.69828 15365 0.017403 0 -12708 1169.1 2327.5
01-Jan-2017 06:00:00 9082.6 0.63896 2661.7 -2573.9 0.00409 15496 0.019086 0 -12924 1195.5 2555.7
01-Jan-2017 07:00:00 9082.7 0.57101 2611 -2382.6 0.67683 15607 0.023495 0 -13227 1184.2 2727.8
01-Jan-2017 08:00:00 9082.7 0.55226 2553.5 -2077.1 0.61035 15663 0.025813 0 -13588 1165.9 2860
01-Jan-2017 09:00:00 9084.7 0.62331 2392 -2078.9 0.10089 15974 0.1066 0 -13897 1195.9 3300.6
01-Jan-2017 10:00:00 9085.5 1.0216 2243 -1612.9 0.00508 16105 0.90292 0 -14494 1212.7 3561.6
01-Jan-2017 11:00:00 9082.8 0.96721 2080.4 -1197 0.00387 16146 2.4625 0 -14951 1221 3758.2
01-Jan-2017 12:00:00 9085.3 1.0963 1968.2 -1153.4 0.00167 16371 2.5767 0 -15218 1217.6 4095.8
01-Jan-2017 13:00:00 9085.1 1.0842 2011.4 -1079 0.0002 16513 1.7942 0 -15435 1232.6 4181.4
01-Jan-2017 14:00:00 9084.7 0.97908 2076.3 -1023.3 9e-05 16764 0.43023 0 -15741 1246 4355.6
01-Jan-2017 15:00:00 9084.4 0.94576 2106.2 -799.64 0.00044 17276 0.047412 0 -16477 1242.9 4841