9ce23c4a10
new general processing structure just before splitting off the projects folder from this repo
53 lines
1.7 KiB
Matlab
53 lines
1.7 KiB
Matlab
function resultTable = groupIt(fixedVars, dataTable, aggregationFunction)
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% groupIt Groups data in a table based on fixedVars and applies aggregationFunction to numeric data.
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%
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% resultTable = groupIt(fixedVars, dataTable, aggregationFunction)
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%
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% Inputs:
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% fixedVars - Cell array of variable names to group by
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% dataTable - Input MATLAB table
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% aggregationFunction - Function handle (e.g., @mean, @min, @max)
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%
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% Output:
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% resultTable - Grouped and aggregated table
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[G, groupKeys] = findgroups(dataTable(:, fixedVars));
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varNames = dataTable.Properties.VariableNames;
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nVars = numel(varNames);
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aggData = cell(height(groupKeys), nVars);
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groupCount = zeros(height(groupKeys), 1);
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for i = 1:height(groupKeys)
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idx = (G == i);
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groupCount(i) = sum(idx);
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for j = 1:nVars
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colData = dataTable.(varNames{j});
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if isnumeric(colData)
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if any(idx)
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aggData{i, j} = aggregationFunction(colData(idx));
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else
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aggData{i, j} = NaN;
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end
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else
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if iscell(colData)
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nonEmptyIdx = find(idx & ~cellfun(@isempty, colData), 1);
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if ~isempty(nonEmptyIdx)
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aggData{i, j} = colData{nonEmptyIdx};
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else
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aggData{i, j} = [];
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end
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else
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nonEmptyIdx = find(idx, 1);
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if ~isempty(nonEmptyIdx)
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aggData{i, j} = colData(nonEmptyIdx);
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else
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aggData{i, j} = [];
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end
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end
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end
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end
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end
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resultTable = cell2table(aggData, 'VariableNames', varNames);
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resultTable.nRows = groupCount;
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end |