Number of nights spent at tourist accommodation establishments challenge

challenge = "TOURISM"

Accommodation statistics are a key part of the system of tourism statistics in the EU and have a long history of data collection. For this indicator, the benchmark will be the official figures on nights spent at tourist accommodation establishments by residents and non-residents.

A night spent is each night a guest/tourist (resident or non-resident) actually spends (sleeps or stays) or is registered (his/her physical presence there being unnecessary) in a tourist accommodation establishment.

Next forecast for a given country

viewof country = Inputs.select(Object.values(country_map), {
  label: html`<b>Select a country:</b>`,
  placeholder: "Enter a country name",
  unique: true
  })

Plot.plot({
  grid: true,
  y: {
    label: "↑ Number of nights spent at tourist accommodation establishments",
    transform: d => d / 1e6
  },  
  x: {
      label: "Year",
      domain: range
    },
  marks: [
    Plot.line(historical, {
        tip: true,
        x: "date", 
        y: "values", 
        stroke: "black",
        title: (d) =>
                `${d.date.toLocaleString("en-UK", {
                  month: "long",
                  year: "numeric"
                })}\n ${d.values / 1e6} millions `
        }),
    Plot.dot(predictions, {
        tip: true,
        x: "date", 
        y: "values",
        fill: "model",
        title:  (d) =>
                `${d.model}\n ${d.date.toLocaleString("en-UK", {
                  month: "long",
                  year: "numeric"
                })} : ${d.values / 1e6} millions `
        })
  ],
  color: {legend: true}
})

dates = {
  const data = historical.map(d => d.date)
  data.push(predictions.map(d => d.date)[0])
  return data  
}

viewof range = offsetInterval(dates, {
  value: [ dates[dates.length-90], dates[dates.length-1] ],
  format: ([a, b]) => htl.html`<span ${{
    style: "display: flex; justify-content: space-between"
  }}>
    ${a.toISOString("en-UK").slice(0, 10)}
    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
    ${b.toISOString("en-UK").slice(0, 10)}
  </span>`
})

Country-specific forecast summary by model

viewof form = Inputs.form({
  model: Inputs.checkbox(models, {value: models}),
  countries: Inputs.select(["All", ...Object.values(country_map)], {multiple: true, value: ["All"], width: 50, size: 1})
})

viewof rows = Inputs.table(summary_table,{
  rows: 25,
  maxWidth: 840,
  multiple: false,
  layout: "fixed"
})

historical = format_historical_data(data, country_iso)

predictions = format_pred_data(pred, country_iso)

summary_table = format_summary_table_data(pred, form.countries, form.model, country_map)

country_map = get_countries_per_challenge(mapping_countries_weights, challenge)

country_iso = Object.keys(country_map).find(key => country_map[key] === country);

models = ["REG-ARIMA", "DFM", "ETS", "XGBOOST", "LSTM"]

import { 
    format_historical_data,
    format_pred_data,
    format_summary_table_data,
    get_countries_per_challenge,
    mapping_countries_weights,
     } from "./utils/utils.qmd"

import {offsetInterval} from '@mootari/offset-slider'

Plot = require("https://cdn.jsdelivr.net/npm/@observablehq/plot@0.6.8/dist/plot.umd.min.js")