viewof daily = Inputs.file({label: "UI Daily"})
raw_daily = daily.csv({typed: true})
viewof clean_daily = aq.from(raw_daily)
.derive({
'Active Jobs': d => +op.replace(d['Active Jobs'], ',',''),
'Exported Jobs': d => +op.replace(d['Exported Jobs'], ',',''),
'Expansion Jobs': d => +op.replace(d['Expansion Jobs'], ',',''),
'Original Jobs': d => +op.replace(d['Original Jobs'], ',',''),
Sponsored: d => +op.replace(d.Sponsored, ',',''),
Actual: d => +op.replace(d.Actual, ',',''),
'Total Applies': d => +d['Total Applies']
})
.derive({
spend_per_job: d => d.Actual / d['Exported Jobs'],
apps_per_job: d => d['Total Applies'] / d['Exported Jobs']
})
.view()
viewof clean_campaigns_tab = clean_base_campaigns_tab
.groupby('Parent Campaign name', 'business_line', 'Status')
.rollup({
active_jobs: d => op.sum(d['Active Jobs']),
exported_jobs: d => op.sum(d.Exported),
spend_goal: d => op.max(d['Spend Goal']),
spend: d => op.sum(d.Actual)
})
.derive({
'Parent Campaign name': d => op.replace(d['Parent Campaign name'], '?', '-'),
})
.derive({
'Parent Campaign name': d => op.replace(d['Parent Campaign name'], '- Paused', ''),
})
.derive({
'Parent Campaign name': d => op.trim(d['Parent Campaign name'])
})
.orderby(aq.desc('Parent Campaign name'))
.view()
viewof clean_base_campaigns_tab = aq.from(raw_campaigns)
.derive({
'Active Jobs': d => +op.replace(d['Active Jobs'], ',',''),
Exported: d => +op.replace(d.Exported, ',',''),
'Spend Goal': d => +op.replace(d['Spend Goal'], ',',''),
Actual: d => +op.replace(d.Actual, ',',''),
})
.derive({
business_line: d => op.includes(op.lower(d.Campaign), 'allied') == true ? 'Allied' :
op.includes(op.lower(d.Campaign), 'school') == true ? 'schools/education' :
op.includes(op.lower(d.Campaign), 'therapy/rehab') == true ? 'therapy/rehab' :
op.includes(op.lower(d.Campaign), 'per diem') == true ? 'per diem' :
op.includes(op.lower(d.Campaign), 'rn') == true ? 'RN' :
op.includes(op.lower(d.Campaign), 'interim') == true ? 'Interim Leadership' :
'Other'
})
.orderby(aq.desc('Campaign'))
.view()
raw_campaigns = campaigns_tab.csv({typed: true})
clean_budgets = aq.from(raw_budgets)
.filter(d => d.Employer == 'Aya Healthcare' || d.Employer == 'Aya Locums' || d.Employer == 'Aya Corporate')
.rename({Campaign: 'segment'}, {'Parent Campaign': 'campaign'})
.reify()
.derive({
campaign: d => d.campaign == null ? d.segment : d.campaign
})
.derive({
'Parent Campaign ID': d => d['Parent Campaign ID'] == null ? d['Campaign ID'] : d['Parent Campaign ID']
})
.groupby('Employer', 'campaign', 'Status')
.rollup({
'Monthly Budget': d => op.max(d['Monthly Budget'])
})
.filter(d => d['Monthly Budget'] != undefined)
.objects()
raw_budgets = FileAttachment("Campaigns-Premium - Campaigns-Premium (4).csv").csv({typed: true})
viewof performance_by_campaign = clean
.groupby('parent_campaign', 'business_line')
.rollup({
clicks: d => op.sum(d.clicks),
applies: d => op.sum(d.applies),
spend: d => op.sum(d.spend),
aco_array: d => op.array_agg_distinct(d.aco_type)
})
.orderby('business_line')
//.filter(d => op.includes(d.parent_campaign, 'Opera') == true)
.view()
viewof clean = aq.from(raw_data)
.filter(aq.escape(d => d.date >= start_date && d.date <= end_date))
.derive({
business_line: d => op.includes(op.lower(d.parent_campaign), 'allied') == true ? 'Allied' :
op.includes(op.lower(d.parent_campaign), 'school') == true ? 'schools/education' :
op.includes(op.lower(d.parent_campaign), 'therapy/rehab') == true ? 'therapy/rehab' :
op.includes(op.lower(d.segment), 'per diem') == true ? 'per diem' :
op.includes(op.lower(d.parent_campaign), 'rn') == true ? 'RN' :
op.includes(op.lower(d.segment), 'interim') == true ? 'Interim Leadership' :
'Other'
})
.derive({
parent_campaign: d => d.business_line == 'per diem' ? d.segment : d.parent_campaign
})
.derive({
segment_type: d => op.includes(op.lower(d.segment), 'low submissions') == true ? 'low submissions' :
op.includes(op.lower(d.segment), 'strategic') == true ? 'strategic' :
op.includes(op.lower(d.segment), 'catch') == true ? 'catch all' :
'Other'
})
.rename({parent_id: 'campaign_id'})
.orderby(aq.desc('parent_campaign'))
.view()
raw_data = file.csv({typed: true})
md `**Dates, etc**`
month_start = d3.utcMonth(new Date())
month_end = d3.utcDay.offset(d3.utcMonth(d3.utcMonth.offset(new Date(), 1)), -1)
month_domain = [month_start, month_end]
days_in_month = d3.timeDay.count(d3.utcDay.offset(month_start, -1), month_end)
days_since_start_of_month = d3.timeDay.count(month_start, new Date())
month_progress = days_since_start_of_month / days_in_month
year = d3.utcYear(new Date()).toISOString()
month = d3.utcMonth(new Date()).toISOString()
my_date = d3.utcParse('%Y-%m-%d')(year.slice(0,4) + '-' + month.slice(5,7) + '-' + days_since_start_of_month.toString())
data = [
{date: my_date}
]
// this is a really cool way of displaying tables. Much more aesthetically pleasing than the defaults of arquero and input.table
import { formatTable } from "@saneef/pretty-tables"
import {toc} from "@nebrius/indented-toc"
function sparkbar(max) {
return x => htl.html`<div style="
background: rgb(255, 155, 119, 0.75);
color: transparent;
width: ${100 * x / max}%;
float: right;
padding-right: 3px;
box-sizing: border-box;
overflow: visible;
display: flex;
justify-content: end;">${x.toLocaleString("en")}`
}
date_parser = d3.utcParse('%m/%d/%Y')
// sample of how to place html blocks in a grid
// html `<div style="display: grid; grid-template-columns: 1fr 1fr 1fr; column-gap: 0px; row-gap: 5px;">
// ${viewof spend}
// ${viewof cpl}
// ${viewof cpc}
// </div>`
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
