Public
Edited
Feb 2, 2023
tmpq6k6kydy.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
rawData = FileAttachment("tmpq6k6kydy.csv").csv({typed: true});
rawData
// Import the vega-lite api
import {vl} from '@vega/vega-lite-api-v5'
import {printTable} from '@uwdata/data-utilities'
// have a look at the first 10 rows of data
printTable(rawData.slice(0,10));
dateSet = new Set();
// reformat data to {year/Month: {morning: number, afternoon: number, night: number}}
data = rawData.map(d => {
const timeStamp = d["DateTime_Measured"];
const electricityUsage = d["Total_Demand_KW"];
const year = timeStamp.slice(0, 4);
const month = timeStamp.slice(5, 7);
const hour = parseInt(timeStamp.slice(11, 13));
let timePeriod = null;
// check if it is morning[4-12pm), afternoon[12-8pm) or night[8-4am)
if (hour >= 4 && hour <12 ){
timePeriod = 'morning';
}else if (hour >= 12 && hour < 20){
timePeriod = 'afternoon';
}else{
timePeriod = 'night';
}
const date = new Date(year, month);
dateSet.add(date);
return {date, timePeriod, electricityUsage}
})
// group the objects together with the same date and timePeriod in data
groupData = new Object;
dateSet.forEach(date => groupData[date] = {morning: 0, afternoon: 0, night: 0});
groupData
data.forEach(d =>{
groupData[d['date']][d['timePeriod']] += d['electricityUsage'];
});
// have a look at the groupData
groupData
df = []
Object.entries(groupData).forEach(([key, value])=>{
// df.push({date: key, ...value, total: value['morning']+value['afternoon']+value['night']})
df.push({date: key, type: 'morning', electricityUsage: value['morning']});
df.push({date: key, type: 'afternoon', electricityUsage: value['afternoon']});
df.push({date: key, type: 'night', electricityUsage: value['night']});
})
df
// visualiza the data using vega-lite stacked bar chart
vl.markBar().width(900).height(600).data(df).encode(
vl.y().aggregate('sum').title('KW').field('electricityUsage'),
vl.x().timeUnit('yearmonth').field('date').title('Date'),
vl.color().field('type')
).render()
// visualize the data using vega-lite grouped bar chart
vl.markBar().data(df).encode(
vl.column().field("date").timeUnit('yearmonth').header({'orient': 'bottom'}),
vl.y().field('electricityUsage').type('quantitative'),
vl.x().field('type').axis(null),
vl.color().field('type')
).render()
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