@kriztean
Published
Edited
Aug 28, 2022
1 star
import {
chartHisto,
chart,
chart_stacked,
multi_series
} from "@kjgarza/vega-charts"
chart(issues)
chartHisto(pub, "publication_year")
chartHisto(histo, "created")
chartHisto(registered, "registered")
registered = d3.csv(
"https://raw.githubusercontent.com/kjgarza/datasets/main/contributorTypes/registered_client_20220718_v0.csv"
)
z = require("https://bundle.run/zebras@0.0.11")
calculate_growth_rate = function (data, date) {
z.sortByCol("publication_year", "asc", data);
var caca = z.gbSum(
"Count",
z.groupBy((d) => d.publication_year, data)
);
var growth = z.getCol("sum", caca);
var zdata = z.pctChange(growth);
return z.addCol("growth", zdata, caca);
}
multi_series(calculate_growth_rate(pub, "publication_year"))
calculate_growth_rate(z.slice(2, 1000, registered), "publication_year")
registered
registered
Inputs.table(pub, {
layout: "auto",
columns: ["publication_year", "contributorType", "Count"],
format: {
html_url: (html_url, i, data) =>
htl.html`<a href="${html_url}">${data[i].number}</a>`,
user: (user) => user.login,
created_at: (created_at) => d3.timeFormat("%x %X")(new Date(created_at))
}
})
chart_stacked(issues, "contributorType")
chart_stacked(issues, "keyword")
software_data = d3.csv(
"https://raw.githubusercontent.com/kjgarza/datasets/main/contributorTypes/software_client_20220718_v0.csv"
)
chart_stacked(
software_data.filter((element) => {
return element.software != "__missing__";
}),
"software"
)
chart_stacked(software_data, "software")
publisher = d3.csv(
"https://raw.githubusercontent.com/kjgarza/datasets/main/contributorTypes/publisher_registered_20220718_v0.csv"
)
chart_stacked(publisher, "publisher")
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