Omit nans from data set when calculating weights

Question

Callie 2024-4-11

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2105671-omit-nans-from-data-set-when-calculating-weights

编辑： Star Strider 2024-4-11

Hello!

I currently have data from 5 rain gages and am trying to calulated weighted averages for each to better represent how much rain fell in certain areas. Some of the rows have NaNs in them so when I calulate the weighted average across the five gages the product = NaN. I would like to ignore the NaNs in the calculation but cannot figure out how to do this. I have tried the 'omitnan' but maybe I am not putting it in the right place? Thank you in advance!!

%Doing all precipitation
Precip1 = table2timetable(P1);
Precip2 = table2timetable(P2);
Precip3 = table2timetable(P3);
Precip4 = table2timetable(P4);
Precip5 = table2timetable(P5);
AllPrecip=synchronize(Precip1, Precip2,Precip3,Precip4,Precip5);
Weight_HQ=[0.003365661397
0.1528054559
0.3846818121
0.2268942917
0.2322527789];
Weight_N1B=[0
0
0.01912681913
0.9064449064
0.07442827443]
Weight_N2B=[0
0.8899179677
0.1100820323
0
0]
Weight_N4D=[0
0.03316776158
0.8987341772
0.06809806121
0]
Weight_N20B=[0
0
0.001316655695
0.6356155365
0.3630678078]
AllPrecip.HQ_Precip=Weight_HQ(1)*AllPrecip.ppt_Precip1+Weight_HQ(2)*AllPrecip.ppt_Precip2+Weight_HQ(3)*AllPrecip.ppt_Precip3+Weight_HQ(4)*AllPrecip.ppt_Precip4+Weight_HQ(5)*AllPrecip.ppt_Precip5;
AllPrecip.N1B_Precip=Weight_N1B(1)*AllPrecip.ppt_Precip1+Weight_N1B(2)*AllPrecip.ppt_Precip2+Weight_N1B(3)*AllPrecip.ppt_Precip3+Weight_N1B(4)*AllPrecip.ppt_Precip4+Weight_N1B(5)*AllPrecip.ppt_Precip5;
AllPrecip.N2B_Precip=Weight_N2B(1)*AllPrecip.ppt_Precip1+Weight_N2B(2)*AllPrecip.ppt_Precip2+Weight_N2B(3)*AllPrecip.ppt_Precip3+Weight_N2B(4)*AllPrecip.ppt_Precip4+Weight_N2B(5)*AllPrecip.ppt_Precip5;
AllPrecip.N4D_Precip=Weight_N4D(1)*AllPrecip.ppt_Precip1+Weight_N4D(2)*AllPrecip.ppt_Precip2+Weight_N4D(3)*AllPrecip.ppt_Precip3+Weight_N4D(4)*AllPrecip.ppt_Precip4+Weight_N4D(5)*AllPrecip.ppt_Precip5;
AllPrecip.N20B_Precip=Weight_N20B(1)*AllPrecip.ppt_Precip1+Weight_N20B(2)*AllPrecip.ppt_Precip2+Weight_N20B(3)*AllPrecip.ppt_Precip3+Weight_N20B(4)*AllPrecip.ppt_Precip4+Weight_N20B(5)*AllPrecip.ppt_Precip5;

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Answer 1

Voss 2024-4-11

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2105671-omit-nans-from-data-set-when-calculating-weights#answer_1439726

在 MATLAB Online 中打开

You can use fillmissing to replace any NaN with 0, so that it doesn't contribute to the weighted sum.

Give the resulting timetable a different name if you want to preserve your original timetable.

T = fillmissing(AllPrecip,'constant',0);
AllPrecip.HQ_Precip = Weight_HQ(1)*T.ppt_Precip1+Weight_HQ(2)*T.ppt_Precip2+Weight_HQ(3)*T.ppt_Precip3+Weight_HQ(4)*T.ppt_Precip4+Weight_HQ(5)*T.ppt_Precip5;
% etc. for the other calculated columns

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Callie 2024-4-11

Thank you so much!

Voss 2024-4-11

You're welcome!

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Answer 2

Star Strider 2024-4-11

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2105671-omit-nans-from-data-set-when-calculating-weights#answer_1439716

Since NaN values are considered to be ‘missing’, to remove them from a specific vector (or matrix), you can use the rmmissing function.

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Callie 2024-4-11

Great! I have a large data set but am going to try this method as well. Thank you!

Star Strider 2024-4-11

编辑：Star Strider 2024-4-11

在 MATLAB Online 中打开

My pleasure!

Note —

x = randi(9, 1, 5);
x([2 4]) = NaN
x = 1x5
     2   NaN     9   NaN     4
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w = 1:numel(x)
w = 1x5
     1     2     3     4     5
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x = fillmissing(x, 'Constant',0)
x = 1x5
     2     0     9     0     4
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mean_xw = mean(x.*w)                            % Counts Zeros As Vector Elements
mean_xw = 9.8000
x([2 4]) = NaN
x = 1x5
     2   NaN     9   NaN     4
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correct_mean_xw =  mean(x.*w,'omitnan')         % Omits 'NaN' Values
correct_mean_xw = 16.3333