defaultdict is how this is done. While for loops are largely essential, if statements aren’t. from collections import defaultdict groups = defaultdict(list) for obj in old_list: groups[obj.some_attr].append(obj) new_list = groups.values()
Reduce is great for situations like this. Given list below is your input data: const list = [{ ‘name’: ‘Display’, ‘group’: ‘Technical detals’, ‘id’: ’60’, ‘value’: ‘4’ }, { ‘name’: ‘Manufacturer’, ‘group’: ‘Manufacturer’, ‘id’: ’58’, ‘value’: ‘Apple’ }, { ‘name’: ‘OS’, ‘group’: ‘Technical detals’, ‘id’: ’37’, ‘value’: ‘Apple iOS’ } ]; const groups = list.reduce((groups, … Read more
This pattern became evident by experience with using both collectors. You’ll find several Q&As on Stackoverflow, where a problem could be solved with either collector, but one of them seems a better fit for the particular task. This is a variation of the difference between Reduction and Mutable Reduction. In the first case, we use … Read more
Use groupby + transform: df[‘max’] = df.groupby(‘group’)[‘odds’].transform(‘max’) This is equivalent to the verbose: maxima = df.groupby(‘group’)[‘odds’].max() df[‘max’] = df[‘group’].map(maxima) The transform method aligns the groupby result to the groupby indexer, so no explicit mapping is required.
Here is the Muenchian grouping solution you are looking for. Going from the original XML you provided, I thought grouping by AreaID would be enough, but it turns out that a second grouping by UnitID is also needed. Here is my modified XSLT 1.0 solution. It’s not a lot more complex than the original solution: … Read more
The Bioconductor package RBGL (an R interface to the BOOST graph library) contains a function, connectedComp(), which identifies the connected components in a graph — just what you are wanting. (To use the function, you will first need to install the graph and RBGL packages, available here and here.) library(RBGL) test <- data.frame(id1=c(10,10,1,1,24,8),id2=c(1,36,24,45,300,11)) ## Convert … Read more
In Java 8: Map<String, List<Student>> studlistGrouped = studlist.stream().collect(Collectors.groupingBy(w -> w.stud_location));
You can loop and sum it up var array = [ { Id: “001”, qty: 1 }, { Id: “002”, qty: 2 }, { Id: “001”, qty: 2 }, { Id: “003”, qty: 4 } ]; var result = []; array.reduce(function(res, value) { if (!res[value.Id]) { res[value.Id] = { Id: value.Id, qty: 0 }; result.push(res[value.Id]) … Read more
You can use groupBy of angular.filter module. so you can do something like this: JS: $scope.players = [ {name: ‘Gene’, team: ‘alpha’}, {name: ‘George’, team: ‘beta’}, {name: ‘Steve’, team: ‘gamma’}, {name: ‘Paula’, team: ‘beta’}, {name: ‘Scruath’, team: ‘gamma’} ]; HTML: <ul ng-repeat=”(key, value) in players | groupBy: ‘team'”> Group name: {{ key }} <li ng-repeat=”player … Read more
There is no native one, just use a loop. $result = array(); foreach ($data as $element) { $result[$element[‘id’]][] = $element; }