Published
Edited
May 27, 2021
layers = evaluate_layers(show_datapoints, show_boxplot)
evaluate_layers = function(display_datapoints, display_boxplot) {
const layers = [];
if (display_datapoints == "On") {layers.push(vl.markPoint() .encode(
vl.x().fieldN("sampleName"),
vl.y().fieldQ(target),
vl.color().fieldN("sampleName"),
vl.shape().fieldN("organisation"),
vl.tooltip([
vl.fieldN("sampleName"),
{"field": target, "aggregate": "mean", "type": "quantitative"},
]),
))}
if (display_boxplot == "On") {layers.push(vl.markBoxplot() .encode(
vl.x().fieldN("sampleName"),
vl.y().fieldQ(target).scale({zero: false}),
vl.color().fieldN("sampleName"),
vl.shape().fieldN("organisation"),
vl.tooltip([
vl.fieldN("sampleName"),
vl.fieldQ(target),
]),
))}
return layers
}
filtered_data = full_data.filter(function(obj) {
return (obj.Weighting == weighting && obj.Distribution == distribution);
})
full_data = [].concat(...array_of_full_datasets)
array_of_full_datasets = add_metadata_to_datasets(array_of_datasets, array_of_metadata)
function add_metadata_to_datasets(arr_datasets, arr_metadata) {
const new_datasets = [];
for (var i = 0; i < arr_datasets.length; i++) {
const dataset = arr_datasets[i];
const dataset2 = [];
const metadata = arr_metadata[i];
for (var j = 0; j < dataset.length; j++) {
const object = dataset[j];
for (const key in metadata) {
object[key] = metadata[key]
}
dataset2.push(object);
}
new_datasets.push(dataset2);
}
return new_datasets;
}
array_of_metadata = Promise.all(meta_promises)
array_of_datasets = Promise.all(promises)
meta_promises = dataset_ids.map(id => {
const url = api_url + id + "/versions/latest/metadata";
return fetch_metadata(url) })
promises = dataset_ids.map(id => {
const url = api_url + id + "/versions/latest/data";
return fetch_dataset_to_array(url, {}) })
function fetch_metadata(dataset_url) {
return fetch(dataset_url).then(response_dataset => {
if (!response_dataset.ok) throw new Error(response_dataset.status);
return response_dataset.json();}
);
}
function fetch_dataset_to_array(dataset_url, query_options) {
return fetch(dataset_url, query_options).then(response_dataset => {
if (!response_dataset.ok) throw new Error(response_dataset.status);
return response_dataset.json();}).then(json => json.results.map(x => x.data));
}
dataset_ids = [
"e7afa026-f4b0-4914-96e6-f34e064c74a5",
"d858218e-dd47-4b06-9641-e3fdde6e0efb",
"c91d0b9e-d5b8-4707-8382-033b8e41841e",
"5b4f2b06-11bb-4036-b5b7-c120d87bdef0"
]
api_url = "https://data.acenano.douglasconnect.com/datasets/"
import {vl} from "@vega/vega-lite-api"
import {Select, Range, Toggle, Table} from "@observablehq/inputs"
import {render_data_table, table_styles, displayImage, displayCaution} from '@info474/utilities'
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.
