Extracting data based on categories

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Allie
Allie 2019-7-11
编辑： Guillaume 2019-7-12
I have a table (z) with two columns, year and annual precipitation. I have a separate vector (E) of three categories (0,1,2) that correspond to the years in the first table. The categories are unevenly spaced. I would like to create three new tables of year and annual precipitation, one for each category. How do I extract the correct year and precipitation data for each category and populate new tables?
z=['01-Jan-1973' 0.0114583333333333
'01-Jan-1974' 0.0918518518518519
'01-Jan-1975' 0.0529032258064516
'01-Jan-1976' 0.213571428571429
'01-Jan-1977' 0.0857692307692308]
E=[0 1 0 2 1]
I would like to create three new tables in the same format as z, like below.
A=['01-Jan-1973' 0.0114583333333333
'01-Jan-1975' 0.0529032258064516]
B=['01-Jan-1974' 0.0918518518518519
'01-Jan-1977' 0.0857692307692308]
C=['01-Jan-1976' 0.213571428571429]
My actual tables and vectors are 1x79, making extracting the three new tables challenging to do by hand.
  2 个评论
Guillaume
Guillaume 2019-7-11
Can you give an example of inputs and desired output. Preferably using valid matlab syntax.
Allie
Allie 2019-7-11
I updated the question. Do you need more information still?

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Star Strider
Star Strider 2019-7-11
The splitapply function (R2015b and later releases) is perfect for this!
z = {'01-Jan-1973' 0.0114583333333333
'01-Jan-1974' 0.0918518518518519
'01-Jan-1975' 0.0529032258064516
'01-Jan-1976' 0.213571428571429
'01-Jan-1977' 0.0857692307692308};
E=[0 1 0 2 1];
Out = splitapply(@(x){x}, z, E(:)+1);
A = Out{1}
B = Out{2}
C = Out{3}
producing:
A =
2×2 cell array
{'01-Jan-1973'} {[0.0114583333333333]}
{'01-Jan-1975'} {[0.0529032258064516]}
B =
2×2 cell array
{'01-Jan-1974'} {[0.0918518518518519]}
{'01-Jan-1977'} {[0.0857692307692308]}
C =
1×2 cell array
{'01-Jan-1976'} {[0.213571428571429]}
  4 个评论
显示 2更早的评论
Star Strider
Star Strider 2019-7-12
I did not know your dates were in datetime format, so that is likely the reason the splitapply code failed.
I added the accumarray code later when I realised that you may not have splitapply. I’m glad it worked!
Guillaume
Guillaume 2019-7-12
编辑：Guillaume 2019-7-12
Note: If you are actually using a table (or a timetable, which would be better probably), the best solution might be not to split the table at all and just add the E as an extra table variable.
Matlab has plenty of aggregation functions (rowfun, varfun, splitapply as shown here, groupsummary) which allows you to apply the same function to each group of a table all at once. More often, the code is actually simpler and faster if the data is not split beforehand.
e.g:
%demo table
T = table(datetime({'01-Jan-1973'; '01-Jan-1974'; '01-Jan-1975'; '01-Jan-1976'; '01-Jan-1977'}), ...
[0.0114583333333333; 0.0918518518518519; 0.0529032258064516; 0.213571428571429; 0.0857692307692308], ...
'VariableNames', {'Date', 'Value'});
T.group = [0; 1; 0; 2; 1]
groupsummary(T, 'group', {'mean', 'sum', 'std'}, 'Value')
outputs:
ans =
3×5 table
group GroupCount mean_Value sum_Value std_Value
_____ __________ __________________ __________________ ___________________
0 2 0.0321807795698924 0.0643615591397849 0.0293059645132893
1 2 0.0888105413105414 0.177621082621083 0.00430106261490964
2 1 0.213571428571429 0.213571428571429 0

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