Visual Cognition Complete / Interactive Info Vis

UW iSchool Course INFO 474: focused on designing and building visualizations to better understand and communicate about pressing issues.

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Edited

Jan 27, 2021

Fork of Visual Cognition

chart_data = data.map((d, i) => {

return {

x: +d.year,

y: +d.points,

artist: d.artist,

id: i

};

})

// Get a unique set of artists(chart_data, d => d.artist)

artists = d3

.groups(chart_data, d => d.artist)

.map(d => d[0])

.sort((a, b) => (a > b ? 1 : -1))

// Get a unique set of artists(chart_data, d => d.artist)

titles = d3.groups(chart_data, d => d.id)

viewof size = slider({ min: 5, max: 25 })

image_chart = {

let svg, xAxis, yAxis, title;

if (!this) {

//Create the svg

svg = d3

.create("svg")

.attr("width", width)

.attr("height", height);

// Append the x axis

xAxis = svg.append("g").attr("class", "xaxis");

// Append the y axis

yAxis = svg.append("g").attr("class", "yaxis");

// Append the title

title = svg

.append("text")

.attr("class", "chart_title")

.attr("transform", `translate(${width / 2},15)`)

.style("text-anchor", "middle");

}

// Otherwise, define the svg as the cell's value and select the axes and title

else {

svg = d3.select(this);

xAxis = svg.select(".xaxis");

yAxis = svg.select(".yaxis");

title = svg.select(".chart_title");

}

// Update titles and axes

xAxis.call(xAxisFn);

yAxis.call(yAxisFn);

title.text("Chart title");

// Do our data join to manage the circles on the screen

// unselected artists in an array

const unselected_artists = chart_data.filter(d => d.artist !== artist);

const circles = svg.selectAll("image").data(unselected_artists, d => d.id);

circles

.join("image")

.attr(

"xlink:href",

"https://upload.wikimedia.org/wikipedia/commons/thumb/b/b6/12in-Vinyl-LP-Record-Angle.jpg/440px-12in-Vinyl-LP-Record-Angle.jpg"

)

.attr("width", 10)

.attr("height", 10)

.attr("transform", d => `translate(${x(d.x)}, ${y(d.y)})`);

// .transition()

// .duration(500)

// .attr("r", d => (d.artist == artist || artist == "" ? 5 : 1))

// .attr("cx", d => x(d.x))

// .attr("cy", d => y(d.y))

// .attr("opacity", d => (d.artist == artist ? 1 : .3))

// .attr("fill", d => (d.artist == artist ? "green" : "black"));

// Do another data join to show small rectangles for the selected artist

const selected_artist_data = chart_data.filter(d => d.artist == artist);

const rects = svg.selectAll("rect").data(selected_artist_data);

rects

.join("rect")

.attr("x", d => x(d.x) - size / 2)

.attr("y", d => y(d.y) - size / 2)

.transition()

.duration(500)

.attr("width", size)

.attr("height", size);

return svg.node();

}

x = d3

.scaleLinear()

.domain(d3.extent(chart_data, d => d.x))

.range([margin.left, width - margin.right])

y_min = d3.min(chart_data, d => d.y)

y_max = d3.max(chart_data, d => d.y)

y = d3

.scaleLinear()

.domain([y_min, y_max])

.range([height - margin.bottom, margin.top])

xAxisFn = g =>

.attr("transform", `translate(0,${height - margin.bottom})`)

.call(d3.axisBottom(x).tickFormat(d3.format("")))

yAxisFn = g =>

.attr("transform", `translate(${margin.left},0)`)

.call(d3.axisLeft(y).tickFormat(d3.format("")))

import { autoSelect, slider } from "@jashkenas/inputs"

d3 = require("d3@6")

margin = ({top: 20, right: 30, bottom: 30, left: 40})

height = 500

import {

render_data_table,

group_notebook_instructions,

table_styles

} from "@uw-info474/utilities"

data = await d3.csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-04-14/rankings.csv")

table_styles

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