df = await dfd
.readCSV(url)
.then((d) => d.setIndex({ column: "geography" }))
.then((de) => {
var mappings = {};
var cols = de.columns.filter((d) => d.includes(":"));
cols.forEach((d, i) => {
// de = de.asType(d, "int32");
// if (i === 0) {
// mappings[d] = "totals";
// } else {
mappings[d] = /:(.+);/.exec(d)[1];
// }
});
return de
.loc({ rows: de.index.filter((d) => d), columns: cols })
.rename(mappings, { inplace: false });
})
df.$columns
no_sub = {
var cols = df.$columns.filter(
(d) => !(d.includes("count") || d.includes("All usual"))
); //d.includes(":") ||
return df.loc({ columns: cols });
}
percentages = no_sub.div(no_sub.sum(), { axis: 0 })
dfd.toJSON(percentages, { format: "row" })
percentages.$data
View Tables
html`<div id='table' style='height:500px;width:100%;display:block'></div>`
Sanity Plot
html`<div id='plot_div' style='height:600px;display:block'></div>`
percentages.plot("plot_div").bar()
df
// viewof search = Inputs.search(data)
// Inputs.table(search, {
// format: {
// Year: d3.format("d") // format as "1960" rather than "1,960"
// }
// })
dfd = require("https://cdn.jsdelivr.net/npm/danfojs@1.1.0/lib/bundle.min.js").catch(
() => {
window.dfd.Series.prototype.print = window.dfd.DataFrame.prototype.print = function () {
return print(this);
};
return window.dfd;
}
)
html`
<style>
p{
color:steelblue;
}
</style>`
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