Finding average data from a large data matrix

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Matlab_G
Matlab_G el 18 de Nov. de 2022
Comentada: Cris LaPierre el 21 de Nov. de 2022
Hello,
I have a data matrix in the following format:
Row 1 is the years from 1990 to 2000
Row 2 is the month
Row 3 is the day
Row 4 is the data
Ex:
1990 1990 1990 1990…..until 2000
1 1 1 1 1 1 1 1…2 2 2 2 2 2….3 3 3 3
1 2 3 4 5 6
How can I calculate the average data of each month (ie. all the jan, feb, together)? The problem that I am encountering is finding a systematic way of dividing the data, given its format.
Thanks in advance

Respuesta aceptada

Benjamin Thompson
Benjamin Thompson el 18 de Nov. de 2022
An index vector over the available columns would work well here. Cannot be sure without a complete example of the data. Then pass the index vector as the second subscript argument for the submatrix of A that you want to pass to the "mean" function to get the average.
>> A = [1990 1990 1991 1991 1992 2000; 1 2 3 4 1 2; 1 2 3 4 5 6; 1 2 3 4 5 6]
A =
1990 1990 1991 1991 1992 2000
1 2 3 4 1 2
1 2 3 4 5 6
1 2 3 4 5 6
>> I_feb = A(2,:) == 2
I_feb =
1×6 logical array
0 1 0 0 0 1
>> mean(A(4,I_feb))
ans =
4
  2 comentarios
Matlab_G
Matlab_G el 20 de Nov. de 2022
how can i expand this to satisfy two rows
example:
A=
2000 2000 2000 2001 2001
1 1 2 1 1
5 3 8 9 7
I would like the average of row 3 elements when row 1==2000 and row 2==1, which in this case would be 4.
Benjamin Thompson
Benjamin Thompson el 21 de Nov. de 2022
The index vector can use a more complex logic test:
I_two_conditions = (A(1,:) == 2000) & (A(2,:) == 1)

Iniciar sesión para comentar.

Más respuestas (2)

Cris LaPierre
Cris LaPierre el 18 de Nov. de 2022
data = [1990 1990 1990 1990 1995 1995 1995 1995;
1 1 2 2 1 1 2 2;
1 2 1 2 1 2 1 2;
3 5 7 4 6 8 1 9]'
data = 8×4
1990 1 1 3 1990 1 2 5 1990 2 1 7 1990 2 2 4 1995 1 1 6 1995 1 2 8 1995 2 1 1 1995 2 2 9
avgData = groupsummary(data(:,4),[data(:,1),data(:,2)],'mean')
avgData = 4×1
4.0000 5.5000 7.0000 5.0000
This is probably easier to understand if you turn your data into a table.
dataT = array2table(data,'VariableNames',["Year","Month","Day","Data"])
dataT = 8×4 table
Year Month Day Data ____ _____ ___ ____ 1990 1 1 3 1990 1 2 5 1990 2 1 7 1990 2 2 4 1995 1 1 6 1995 1 2 8 1995 2 1 1 1995 2 2 9
avgDataT = groupsummary(dataT,["Year","Month"],"mean","Data")
avgDataT = 4×4 table
Year Month GroupCount mean_Data ____ _____ __________ _________ 1990 1 2 4 1990 2 2 5.5 1995 1 2 7 1995 2 2 5
One more may to do this is if you turn your date info into a datetime variable
dataT2 = table(datetime(data(:,1:3)),data(:,4),'VariableNames',["Date","Data"])
dataT2 = 8×2 table
Date Data ___________ ____ 01-Jan-1990 3 02-Jan-1990 5 01-Feb-1990 7 02-Feb-1990 4 01-Jan-1995 6 02-Jan-1995 8 01-Feb-1995 1 02-Feb-1995 9
avgDataT2 = groupsummary(dataT2,"Date","month","mean","Data")
avgDataT2 = 4×3 table
month_Date GroupCount mean_Data __________ __________ _________ Jan-1990 2 4 Feb-1990 2 5.5 Jan-1995 2 7 Feb-1995 2 5

dpb
dpb el 18 de Nov. de 2022
tData=array2table(X.','VariableNames',{'Year','Month','Day','Data'});
tMonthAvg=rowfun(@mean,tData,'GroupingVariables',{'Month'}, ...
'InputVariables','Data','OutputVariableNames','MonthAverage');
  1 comentario
Cris LaPierre
Cris LaPierre el 21 de Nov. de 2022
A= [2000 2000 2000 2001 2001;
1 1 2 1 1;
5 3 8 9 7]'
A = 5×3
2000 1 5 2000 1 3 2000 2 8 2001 1 9 2001 1 7
groupsummary(A(:,3),[A(:,1) A(:,2)],'mean')
ans = 3×1
4 8 8

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