If I have a weather data, which is an array, like this one below.
const weather = [
{date:'2022-07-18', min_temp:15, max_temp:26, type:'clouds'},
{date:'2022-07-18', min_temp:13, max_temp:27, type:'sun'},
{date:'2022-07-18', min_temp:23, max_temp:31, type:'clouds'},
{date:'2022-07-18', min_temp:19, max_temp:28, type:'rain'},
{date:'2022-07-19', min_temp:21, max_temp:25, type:'rain'},
{date:'2022-07-19', min_temp:17, max_temp:29, type:'rain'},
{date:'2022-07-19', min_temp:14, max_temp:38, type:'rain'},
{date:'2022-07-19', min_temp:9, max_temp:30, type:'clouds'}
]
How can I reduce the array, one data/date, with the min and max temperature from the same date, and type should be the most frequently type from the same date. It should look like this one below.
const weather = [
{date:'2022-07-18', min_temp=13, max_temp31, type:'clouds'},
{date:'2022-07-19', min_temp=9, max_temp:38, type:'rain'}
]
You can use reduce to collect the values per date into a map, and then get the values of that map:
const weathers = [
{date:'2022-07-18', min_temp:15, max_temp:26, type:'clouds'},
{date:'2022-07-18', min_temp:13, max_temp:27, type:'sun'},
{date:'2022-07-18', min_temp:23, max_temp:31, type:'clouds'},
{date:'2022-07-18', min_temp:19, max_temp:28, type:'rain'},
{date:'2022-07-19', min_temp:21, max_temp:25, type:'rain'},
{date:'2022-07-19', min_temp:17, max_temp:29, type:'rain'},
{date:'2022-07-19', min_temp:14, max_temp:38, type:'rain'},
{date:'2022-07-19', min_temp:9, max_temp:30, type:'clouds'}
]
const weatherByDate = weathers.reduce((acc, curr) => {
const date = curr.date
const weather = acc[date]
if (weather) {
const copy = { ...weather }
copy.min_temp = Math.min(curr.min_temp, weather.min_temp)
copy.max_temp = Math.max(curr.max_temp, weather.max_temp)
const count = (weather.typeCounts[curr.type] || 0) + 1
copy.typeCounts[curr.type] = count
if(count > weather.typeCounts.max) {
copy.typeCounts.max = count
copy.type = curr.type
}
acc[date] = copy
} else {
acc[date] = { ...curr, typeCounts: { [curr.type]: 1, max: 1 } }
}
return acc
}, {})
const arr = Object.values(weatherByDate).map(({typeCounts, ...rest}) => rest)
console.log(arr)EDIT: Edited to keep most frequent type per date
The idea is first to group by date. This is done using the first reduce. While we do, we store the frequency of each type. and the min/max temp.
Then we take the values of this object as the required array. Only a little housekeeping removing the freq helper object. And setting the type to be indeed the most frequent (amongst that date).
const weather = [
{date:'2022-07-18', min_temp:15, max_temp:26, type:'clouds'},
{date:'2022-07-18', min_temp:13, max_temp:27, type:'sun'},
{date:'2022-07-18', min_temp:23, max_temp:31, type:'clouds'},
{date:'2022-07-18', min_temp:19, max_temp:28, type:'rain'},
{date:'2022-07-19', min_temp:21, max_temp:25, type:'rain'},
{date:'2022-07-19', min_temp:17, max_temp:29, type:'rain'},
{date:'2022-07-19', min_temp:14, max_temp:38, type:'rain'},
{date:'2022-07-19', min_temp:9, max_temp:30, type:'clouds'}
];
var step1 = Object.values(weather.reduce(function(agg, item) {
var {date, min_temp, max_temp, type} = item;
if (agg[date]) {
agg[date].min_temp = Math.min(agg[date].min_temp, min_temp)
agg[date].max_temp = Math.max(agg[date].max_temp, max_temp)
} else {
agg[date] = item
agg[date].freq = {}
}
agg[date].freq[type] = (agg[date].freq[type] || 0) + 1
return agg;
}, {})).map(function(item) {
var most_common = 0;
Object.entries(item.freq).reduce(function(agg, [key, value]) {
if (agg<value) {
agg = value;
most_common = key;
}
}, 0);
delete item.freq;
item.type = most_common;
return item;
})
console.log(step1)