maxIterations = 5000
names = new Map([
[1, {name: "Lisa", maxCount: 4}],
[2, {name: "Jackie", maxCount: 15}],
[3, {name: "Maya", maxCount: 15}],
[4, {name: "Margaret", maxCount: 5}],
[5, {name: "Jane", maxCount: 12}],
[6, {name: "Pam", maxCount: 10}],
[7, {name: "Susie", maxCount: 16}],
[8, {name: "Robin", maxCount: 8}],
[9, {name: "Cindy", maxCount: 10}],
[10, {name: "Karen", maxCount: 10}],
[11, {name: "Carolyn", maxCount: 12}],
[12, {name: "Alison", maxCount: 10}],
[13, {name: "Debbie", maxCount: 4}],
[14, {name: "Gaynor", maxCount: 12}],
[15, {name: "Laura", maxCount: 5}]
])
tennisCombinations = {
const allCombinations = _.range(1, number_of_weeks + 1).map(d => combinations)
const allCombos = new Combinations(allCombinations);
allCombos
.applyFilter([4, 6, 7, 10, 11], "includes", [15])
.applyFilter([1, 2, 3, 5, 8, 9, _.range(13, 38)], "excludes", [15])
.applyFilter([1, 2, 3, 4], "excludes", [1])
.applyFilter(_.range(23, 30), "excludes", [2])
.applyFilter([5, 10, 11, 29, 34], "excludes", [3])
.applyFilter(_.range(1, 24), "excludes", [4])
.applyFilter([3, 12, 23, 32, 34], "excludes", [5])
.applyFilter([13, 14], "excludes", [6])
.applyFilter([24, 32], "excludes", [7])
.applyFilter([20, 24, 32], "excludes", [8])
.applyFilter([3, 5, 6], "excludes", [9])
.applyFilter([4, 10, 17, 24, 29, 32], "excludes", [10])
.applyFilter([6, 10, 13, 17, 21, 22, 26, 27, 28, 29], "excludes", [11])
.applyFilter([1, 2, 3, 4, 5, 6, 7, 8, 12], "excludes", [12])
.applyFilter([34, 35, 36, 37], "excludes", [14])
return allCombos.combinations;
}
spreadsheetView = {
const data = sampleCombinations(tennisCombinations, names);
const players = _.range(1, number_of_players + 1);
const weeks = data.map((d, i) => {
const week = players.reduce((acc, p) => {
let player = names.get(p).name;
let value = "";
if (d != undefined) {
value = d.includes(p) ? "x": "";
}
return {...acc, [player]: value}
}, {});
return week;
});
return weeks;
}
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.