I'm a professor of mathematics at the University of North Carolina Asheville. I've also done a fair amount of consulting work over the years focusing on scientific and data visualization.
I'm happy to be part of the first Observable Ambassador's cohort.
Public
Edited
Nov 23
1 fork
1 star
Office staff salaries
rank_choices = [
{ rank: "Professor", id: 1 },
{ rank: "Associate Professor", id: 2 },
{ rank: "Assistant Professor", id: 3 },
{ rank: "Instructor", id: 4 },
{ rank: "All", id: 7 }
]
function make_salary_comparison_bar_plot(cohort, rank, cost_adjust_flag) {
let ids = cohorts.filter((o) => o.cohort == cohort).map((o) => o.UNITID);
let filtered_data = salary_data.filter((o) => ids.indexOf(o.UnitID) > -1);
let tidy_data = get_single_value(rank.rank.toLowerCase());
let avg_data = tidy_data.map(avg);
let plot =
width < 900
? Plot.plot({
y: {
label: null,
domain: d3
.sort(avg_data, (d) =>
cost_adjust_flag ? -d.cost_adjusted_value : -d.value
)
.map((d) => d.UnitID),
tickFormat: (d) => get_initials(d)
},
width: width,
// height: 0.4 * width,
// marginLeft: 70,
marks: [
Plot.barX(avg_data, {
y: "UnitID",
x: cost_adjust_flag ? "cost_adjusted_value" : "value",
fill: (d) => (d.UnitID == "199111" ? "#003DA5" : "lightblue"),
title: "UnitID"
}),
Plot.ruleX([0])
]
})
: Plot.plot({
x: {
label: null,
domain: d3
.sort(avg_data, (d) =>
cost_adjust_flag ? -d.cost_adjusted_value : -d.value
)
.map((d) => d.UnitID),
tickFormat: (d) => get_initials(d)
},
width: width,
height: 0.4 * width,
marginLeft: 70,
marks: [
Plot.barY(avg_data, {
x: "UnitID",
y: cost_adjust_flag ? "cost_adjusted_value" : "value",
fill: (d) => (d.UnitID == "199111" ? "#003DA5" : "lightblue"),
title: "UnitID"
}),
Plot.ruleY([0])
]
});
let nodes = d3
.select(plot)
.selectAll("rect")
.on("pointerenter", function () {
d3.select(this).attr("stroke-width", "2px").attr("stroke", "black");
})
.on("pointerleave", function () {
d3.select(this).attr("stroke", null);
})
.nodes()
.forEach(function (bar) {
let title = d3.select(bar).select("title").text();
tippy(bar, {
content: `${get_name(title)}: $${parseInt(get_salary(title))} ${
cost_adjust_flag ? "(adjusted)" : ""
}`,
theme: "light"
});
});
d3.select(plot).selectAll("rect").select("title").remove();
return plot;
function get_single_value(column_start) {
let columns = Object.keys(filtered_data[0]).filter(
(s) => s.slice(0, column_start.length) == column_start
);
let tidy_data = filtered_data.map(function (d) {
let row = columns.map((key) => ({
year: parseInt(key.match(find_year_re)[0].slice(-4)),
value: parseInt(d[key]),
cost_adjusted_value: cost_adjust(parseInt(d[key]), d.UnitID),
UnitID: d.UnitID
}));
row = d3.sort(row, (o) => o.year);
return row;
});
return tidy_data;
}
function get_salary(uid) {
let row = avg_data.filter((o) => o.UnitID == uid)[0];
if (cost_adjust_flag) {
return Math.round(row.cost_adjusted_value);
} else {
return row.value;
}
}
}
function get_closest(time, value, data) {
let results = [];
data.forEach(function (school_data, i) {
let these_dates = school_data.map((o) => parseInt(o.year));
let these_values = school_data.map((o) => o.value);
try {
let idx = d3.bisect(these_dates, time);
let t1 = these_dates[idx - 1];
let t2 = these_dates[idx];
let p1 = these_values[idx - 1];
let p2 = these_values[idx];
let p = p1 + ((p2 - p1) * (time - t1)) / (t2 - t1);
results.push({
time: time,
value: p,
err: Math.abs(p - value),
id: school_data[0].UnitID
});
} catch {
("pass");
}
});
return results.sort((o1, o2) => o1.err - o2.err)[0];
}
function get_single_value(column_start, data) {
let columns = Object.keys(data[0]).filter(
(s) => s.slice(0, column_start.length) == column_start
);
let td = data.map(function (d) {
let row = columns.map((key) => ({
year: parseInt(key.match(find_year_re)[0].slice(-4)),
value: d[key],
UnitID: d.UnitID
}));
row = d3.sort(row, (o) => o.year);
return row;
});
return td;
}
function get_name(uid) {
let row = cohorts.filter((o) => o.UNITID == uid)[0];
return row.INSTNM;
}
function avg(a) {
// return a.slice(-3);
let this_avg = Math.round(d3.mean(a.slice(-1).map((r) => r.value)));
return {
value: this_avg,
UnitID: a[0].UnitID,
cost_adjusted_value: Math.round(cost_adjust(this_avg, a[0].UnitID))
};
}
// tidy_data = {
// let ids = cohorts.filter((o) => o.cohort == cohort).map((o) => o.UNITID);
// let filtered_data = salary_data.filter((o) => ids.indexOf(o.UnitID) > -1);
// return get_single_value(rank.rank.toLowerCase());
// function get_single_value(column_start) {
// let columns = Object.keys(filtered_data[0]).filter(
// (s) => s.slice(0, column_start.length) == column_start
// );
// let tidy_data = filtered_data.map(function (d) {
// let row = columns.map((key) => ({
// year: parseInt(key.match(find_year_re)[0].slice(-4)),
// value: parseInt(d[key]),
// cost_adjusted_value: cost_adjust(parseInt(d[key]), d.UnitID),
// UnitID: d.UnitID
// }));
// row = d3.sort(row, (o) => o.year);
// return row;
// });
// return tidy_data;
// }
// }
find_year_re = /\([A-Z]{2,}20\d{2}/
function cost_adjust(value, id) {
let adjuster = cohorts.filter((o) => o.UNITID == id)[0].cost_index;
return (100 * value) / adjuster;
}
function get_initials(uid) {
let row = cohorts.filter((o) => o.UNITID == uid)[0];
return row.INSTNM.split(" ")
.map((s) => s[0])
.filter((s) => s.charCodeAt(0) < 97)
.join("");
}
d3.sort(cohorts.map((o) => +o.cost_index))
cohorts = FileAttachment("updated_cohort_data.csv").csv()
housing_data = FileAttachment("UNCSystemZillow@1.csv").csv()
salary_data = FileAttachment("public_peer_salaries.csv").csv()
compression_ratios = FileAttachment("compression_ratios.csv").csv({
typed: true
})
location_data = FileAttachment("cohort_data.csv").csv()
d3.sort(
office_data.map((o) => ({
name: o.InstitutionName,
salary: o.outlay2020 / o.cnt2020
})),
(o) => -o.salary
)
office_data = FileAttachment("nc_office_staff2.csv").csv()
tippy = require("tippy.js@6")
tippy_style = html`<link rel="stylesheet" href="${await require.resolve(
`tippy.js/themes/light.css`
)}">`
import { map, caption } from "@mcmcclur/unc-system-salary-map"
import { regression_chart } from "cf61f59a18c0635a"
data = d3.sort(
cohorts.filter((row) => row.cohort == "UNC System"),
(o) => -o.cost_index
)
<table>
<thead>
<tr>
<th>Name</th>
<th>CoL Index</th>
</tr>
</thead>
<tbody>
${d3.sort(data, row => -row.overall_col).map(row => htl.html`<tr>
<td>${row["INSTNM"]}</td>
<td>${row["cost_index"]}</td>
</tr>`)}
</tbody>
</table>
{
let ids = cohorts.filter((o) => o.cohort == cohort2).map((o) => o.UNITID);
let filtered_data = salary_data.filter((o) => ids.indexOf(o.UnitID) > -1);
let tidy_data = get_single_value("all", filtered_data).map((A) => A.slice(4));
tidy_data.forEach(function (A) {
let v0 = A[0].value;
A.forEach((o) => (o.value = o.value / v0));
});
return tidy_data;
}
Plot = require("https://cdn.jsdelivr.net/npm/@observablehq/plot@0.6.1")
d3.sort(compression_ratios, (o) => o.ratio).slice(452)
compression_ratios
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.
