Finding average data from a large data matrix

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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

采纳的回答

Benjamin Thompson
Benjamin Thompson 2022-11-18
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 个评论
Matlab_G
Matlab_G 2022-11-20
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 2022-11-21
The index vector can use a more complex logic test:
I_two_conditions = (A(1,:) == 2000) & (A(2,:) == 1)

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更多回答(2 个)

Cris LaPierre
Cris LaPierre 2022-11-18
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 2022-11-18
tData=array2table(X.','VariableNames',{'Year','Month','Day','Data'});
tMonthAvg=rowfun(@mean,tData,'GroupingVariables',{'Month'}, ...
'InputVariables','Data','OutputVariableNames','MonthAverage');
  1 个评论
Cris LaPierre
Cris LaPierre 2022-11-21
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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