我有一系列数据,如下所示,按月升序排序:
[{
org_id: "K83002",
percentile: 1,
date: "2013-11-01",
},
{
org_id: "K83059",
percentile: 33,
date: "2013-12-01",
},
{
org_id: "K83607",
percentile: 22,
date: "2013-12-01",
} ...
我想创建一个排序的组织列表,按其在数据中最近三个月的平均百分位数排名。
现在,我正在这样做:
var lastThreeMonths = _.uniq(_.pluck(data, 'date'), true).slice(-3);
var averages = {};
var lastMonths = _.each(data, function(d) {
if (_.contains(lastThreeMonths, d.date)) {
if (d.org_id in averages) {
averages[d.org_id] += d.percentile;
} else {
averages[d.org_id] = d.percentile;
}
}
});
var temp = [];
for (var k in averages) {
temp.push({ 'org_id': k, 'percentile': averages[k]});
}
var sortedAvgs = _.sortBy(temp, 'percentile').reverse();
但这非常冗长。有没有更好的方法呢?
理想情况下,我还想以某种方式为每个组织附加已排序数组的原始数据,因为我将在下一步迭代排序数组,并且访问迭代器内部的数据会很方便。
答案 0 :(得分:0)
你可以试试这个:
var sortedAverages = _.chain(data)
.filter(d => _.contains(lastThreeMonths, d.date))
.groupBy('org_id')
.map(eachOrg => {
var average = _.sum(_.pluck(eachOrg, 'percentile'));
return {
org_id : eachOrg.org_id,
percentile : average
};
})
.sortBy('percentile')
.value()
.reverse();
答案 1 :(得分:0)
这可以帮到你:
// Create a hash of allowed dates - much improved performance over arrays for larger data sets
var lastThreeMonthsHash = _.chain(data).pluck('date').uniq().slice(-3).map(function (date) {
return [date, true]
}).object().value();
// filter out older entries
var grouped = _.chain(data).filter(function (monthly) {
return lastThreeMonthsHash[monthly.date];
// group by org_id
}).groupBy('org_id').map(function (values, orgId) {
// reduce each group into a single value which is the average percentile
var percentiles = _.pluck(values, 'percentile');
var sum = _.reduce(percentiles, function (memo, value) {
return memo + value;
}, 0);
return {
org_id : orgId,
percentile: sum / values.length
};
// sort by percentile & reverse
}).sortBy('percentile').reverse().value();